NISTIR 8124
 

OAGi/NIST Workshop on Open 

Cloud Architecture for Smart 

Manufacturing 

Nenad Ivezic 

Boonserm Kulvatunyou 

Yan Lu 

Yunsu Lee 

Jaehun Lee 

Albert Jones 

Simon Frechette 

This publication is available free of charge from: 

http://dx.doi.org/10.6028/NIST.IR.8124 
 

 

NISTIR 8124
 

OAGi/NIST Workshop on Open 

Cloud Architecture for Smart 

Manufacturing 

Nenad Ivezic 

Boonserm Kulvatunyou 

Yan Lu 

Yunsu Lee 

Jaehun Lee 

Albert Jones 

Simon Frechette 

Systems Integration Division 

Engineering Laboratory 

This publication is available free of charge from: 

http://dx.doi.org/10.6028/NIST.IR.8124 

April 2016 

U.S. Department of Commerce 

Penny Pritzker, Secretary 

National Institute of Standards and Technology 

Willie May, Under Secretary of Commerce for Standards and Technology and Director 
 

 

 

 

 

Abstract 

This report summarizes the results from the OAGi/NIST Workshop on Open Cloud Architecture 

for Smart Manufacturing, which was held at the National Institute of Standards and Technology 

on May 5, 2015. The workshop was a forum for manufacturers and providers of IoT 

technologies, Cloud platforms, and manufacturing services to share their visions, and identify 

and prioritize barriers to adoption of Cloud-enabling capabilities and technologies, forming a 

basis for future follow-on events. The report (1) includes summaries as well as full presentations 

delivered at the workshop; (2) identifies and prioritizes technical issues; (3) summarizes the 

discussions that took place during the workshop; and (4) provides the conclusions that emerged 

from the presentations and discussions. 

Acknowledgement 

Authors would like to thank Mr. Christopher Peters for his many helpful suggestions during 

organization of the workshop and for reviewing the final report. 

Any mention of commercial products is for information only; it does not imply recommendation 

or endorsement by NIST. 

Keywords 

Smart Manufacturing, Cloud Architectures, Internet of Things, Standards Development, 

Standards Adoption, Digital Manufacturing, Industry 4.0 

Acronyms 

API – Application Programming Interface 

B2B – Business-to-Business 

B2MML – Business to Manufacturing Markup Language 

BOD – Business Object Document 

BPMN – Business Process Model and Notation 

CC – Cloud Computing 

CEO – Chief Executive Officer 

DMDII – Digital Manufacturing and Design Innovation Institute 

EAI – Enterprise Application Integration 

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HTTP – Hyper Text Transfer Protocol 

IoT – Internet of Things 

IIoT – Industrial Internet of Things 

ISA – The International Society of Automation 

ISV – Independent Software Vendor 

IT – Information Technology 

JSON – Java Simple Object Notation 

LIMS – Laboratory Information Management System 

LOL – Land O’ Lakes 

MES – Manufacturing Execution System 

MQTT – Message Queuing Telemetry Transport 

NIST – National Institute of Standards and Technology 

NRT – Near-Real-Time 

OAGi – Open Applications Group Incorporated 

OAGIS – Open Applications Group Integration Specification 

ODM – Original Design Manufacturer 

OEM – Original Equipment Manufacturer 

PLM – Product Lifecycle Management 

REST – Representational State Transfer 

R&D – Research and Development 

RT – Real-Time 

SaaS – Software as a Service 

SCOR – Supply Chain Operations Reference 

SDO – Standards Development Organization 

SMLC – Smart Manufacturing Leadership Coalition 

SME – Small- to Medium-sized Enterprise 

SOA – Service-oriented Architecture 

UCLA – University of California, Los Angeles 

XML – Extensible Markup Language 

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List of Contributors 

Presenter Position Affiliation 

Jim Davis Vice Provost IT UCLA & SMLC 

Denis Gagne CEO Trisotech 

Shelley Gretlein Director Product Marketing, Platform 

Software & Customer Education 

National Instruments 

Gregory Harris Program Manager DMDII Department of Defense 

Ian Hedges Vice President, Platform at E2open E2open 

Jon Hirschtick Founder and Chairman Onshape 

Matt Johnson Senior Director Oracle 

Pawan Joshi Vice President Strategy E2open 

Chris Monchinski Director, MES Automated Control 

Concepts 

Scott Nieman Enterprise Integration Architect Land O'Lakes 

Dave Noller Manager, SWG Industrial Sector 

Strategy & Integration 

IBM 

Dennis Pegden CEO Simio 

Jon Siudut MESA International 

Kirk Smith Solutions Architect, Industrial and 

Energy Solutions Division, IoT Group 

Intel 

Dan Trout Automated Control 

Concepts 

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Executive Summary 

While Smart Manufacturing identifies potential great promise in the rapid development of 

today’s technologies, such as Cloud computing and the internet of things, there also is great peril. 

As the variety of systems development approaches and structures proliferate, so too do the risks 

associated with trying to manage and control many disparate systems. Addressing these 

challenges through standards and industry collaboration improves interoperability and helps 

reduce an organization’s risks and costs. 

In May of 2015, the National Institute of Standards and Technology (NIST) held a workshop of 

industry, government, and academia leaders to begin addressing these challenges. This document 

consolidates and highlights the issues raised in the workshop and articulates the value of 

overcoming those issues. The intent is to raise awareness of leadership across government 

agencies as well as industry executives with regards to the workshop findings. It is hoped that 

future plans for technical work to achieve Smart Manufacturing objectives at government 

agencies and in industry will address these issues. 

The workshop participants agreed that the Cloud-enabled technological advances present an 

unprecedented opportunity as well as new, very significant issues to the manufacturing 

community on its way to achieving Smart Manufacturing systems. The following key issues 

emerged from the workshop: 

•	 Existing standards are inadequate to enable the Cloud-based services needed for Smart 

Manufacturing. 

•	 Standards adoption is severely impeded by confusion, complexity, and the lack of
 

efficient tools.
 

•	 We need new architectures to enable service-oriented Smart Manufacturing. 

•	 We need new standards development and standards management processes to support the 

rapid evolution of Smart Manufacturing. 

•	 Cloud platforms can provide the infrastructure needed to implement Smart
 

Manufacturing Enterprises, but challenges remain.
 

The workshop participants expressed belief that addressing the above issues is valuable to the 

manufacturing industry. Value of overcoming the issues includes the following: 

•	 Reduced costs and time to market for manufacturers. 

•	 Increased supply chain interoperability, enabling supply chains to be formed and reconfigured with greater efficiency. 

•	 Enabled new business models that result in greater agility and customization. 

Detailed analyses of these and other issues will be the focus of the follow-on workshops, which 

are planned in collaboration among industry, government, and academic organizations. 

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The next steps include a series of follow-up events and technical activities, including technical 

workshops that will lay out a roadmap with target goals and needed research and development 

(R&D) activities, focused technical projects that will address key research issues, and industryled assessment activities that will provide evaluation and feedback to the technical activities. 

These next steps will have as a common objective to help coordinate public and private efforts in 

developing a next generation of open Cloud solutions to address the identified issues on the path 

to Smart Manufacturing. 

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1 Introduction 

Right now, the emerging digital world of information technologies is a little like the Old West – 

Semi-controlled chaos! This is certainly what manufacturers are finding as they attempt to take 

advantage of technologies such as Mobile Computing, Software-defined Networks, Data 

Analytics, and Internet of Things (IoT), among others. One of those others, and the focus of this 

report, is Cloud Computing (CC). Conceptually at least, CC can be thought of as an ecosystem 

with heterogeneous information-based services. Manufacturers are looking to use such services 

to improve the management and control of their factories and supply chains. These services used 

to be provided only by established software vendors in their large, expensive, bundled, 

monolithic software applications installed on premise. No longer! Both established and new 

vendors have entered the market with new generation of solutions. These vendors are providing 

the same services in unbundled “apps”, which could be significantly much easier and less 

expensive to use. Why? Because, they live in the “Cloud,” which carries the promise of more 

manageable, accessible, and cheaper services that are composed from these apps. 

Depending on the problem to be solved, however, bundling and integrating heterogeneous 

Cloud-based services in the form of apps is not always an intuitive job. Management and control 

are two problem areas The difficulty stems from the fact the solutions to these problems require 

manufacturers to “mix-and-match” several individual service apps. Fair to say, as the number of 

apps required to solve these problems increases, the ability to “mix-and-match” them becomes 

harder. That ability is hampered further because these apps are now being provided by multiple 

CC platforms. Clearly, there is a need for service vendors, Cloud vendors, manufacturers, and 

other stakeholders to work collaboratively to reduce the effort needed to “mix-and-match” the 

apps. That work will require the development of technologies and standards for easier discovery 

and easier integration of services based on improved interoperability and composability. With 

such technologies and standards, we can at least minimize the chaos. 

Open Applications Group, Inc. (OAGi) and NIST put together a workshop to bring these 

stakeholders together to discuss the best approaches, from their individual perspectives, to 

initiate such a development. Stakeholders at the workshop represented two groups: 

manufacturers and vendors. Manufacturers were given an opportunity to identify their 

requirements for integration technologies and interface standards to meet their business needs 

and close their technical gaps. They did this by answering a number of questions sent to them 

before the workshop. Vendors were given the opportunity to demonstrate their current, and 

discuss their future plans for, product development. Both groups were given opportunity to 

exchange ideas about (1) how best to align the requirements and the plans; and (2) what 

technologies and standards were needed to achieve that alignment. 

In this document, we summarize the presentations, discussions, priorities, and findings from this 

workshop. Section 2 presents workshop objectives and the charges to the participants. Section 3 

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summarizes workshop presentations and discussions. Section 4 prioritizes, based on difficulty 

and urgency, the issues discussed in those presentations. Section 5 provides concluding results. 

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2 Workshop Objectives, Charge to, and Response from the Workshop Participants 

In this section, we summarize the initial workshop announcement, including the charge provided 

to the workshop participants, and their responses to that announcement. 

2.1 Workshop Objectives 

The objectives for the workshop were to collect information and publish a report detailing the 

following: 

•	 CC services needed by manufacturing companies and their potential impacts. 

•	 Current and planned offerings of Cloud, services, and IoT providers. 

•	 Strategic and high-level Cloud architectural approaches to match needs with
 

offerings.
 

•	 Needs, gaps, and opportunities for integration technologies and standards. 

2.2 Charge to Workshop Participants 

As part of their charge, we asked participants to answer two questions to help them frame their 

thoughts and prepare for to the workshop. 

Q1: What is the vision for manufacturing to be supported by the IoT, Cloud, and service 

providers? We asked participants to share their answers, from the perspective of their own 

organizations in a presentation of 10 to 15 slides, with the following focuses: 

•	 Manufacturers were expected to explain their vision for how they plan to use Cloud services 

to support their needs. 

•	 Cloud-platform vendors were expected to explain their vision of why and how their offerings 

will support manufacturing needs. 

•	 Cloud-service vendors were expected to explain their vision for how they plan to use Cloud 

platforms to provide the apps needed to provide the required manufacturing functionality. 

Q2: What’s preventing these visions from becoming reality? To answer this question, we 

asked participants to describe what they, and their organizations, thought were the top few 

priority issues. Our intent behind the workshop was to produce a prioritized list of issues, based 

on all of those issues presented by the participants. Second, we also asked them to present 

arguments for why their issues should be on that final list. 

In the course of their presentations, we guided the participants to address as many of the 

following questions as possible. (We also provided guidance in the form of example 

presentation summaries): 

•	 Manufacturing Use Case: What are the manufacturing business needs you are addressing? 

•	 Business Challenge: What is the mismatch between the business needs and your current 

business capabilities? 

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•	 Business Benefit: What are cost savings and other quantifiable benefits following from 

addressing the business challenge and meeting the need? 

•	 Open Cloud Opportunity: Where can open Cloud help address the business challenge and 

help meet the manufacturers’ needs? 

•	 Technical Issues and Initiatives: What technical issues deny the open Cloud opportunity from 

addressing the business challenge? 

•	 Standards Role: What is the potential role for standards to address the technical issues? 

As noted above, we intended to compile a final, prioritized list from the presentations and 

subsequent discussions. To do this, we asked the participants to prioritize all issues by voting for 

their top 6 favorites. We discuss the results of the prioritization in Section 4. 

2.3 Responses from Workshop Participants 

The participants responded to the charge in varied ways. Some were interested only in solving 

specific technical problems. Some were interested in establishing languages and infrastructures 

needed to address those technical problems. Others were more interested in addressing the larger 

organizational issues that Cloud Computing brings to manufacturing. The following sections 

summarize the participants’ contributions and discuss the outcome of their prioritization efforts. 

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3 Presentation Summaries 

In this section, we provide summaries of participants’ submissions in the form of presentations 

made at the workshop. (The summaries are based on abstracts or summaries of the actual 

presentations, which are provided in full in the appendix.) We organize the summaries 

chronologically, within the session in which they took place. Within each session, summaries 

are followed by discussions that took place within the session. 

3.1 Position Statements & Issues Identification – Session 1 

The following table summarizes presentations included in the first session of the workshop. 

Presenter 

Name, 

Company 

Scott Nieman, 

Land O’ Lakes 

Matt Johnson, 

Oracle 

Pawan Joshi, 

E2open 

Denis Gagne, 

Trisotech 

Presentation Title 

Integration 

Challenges 

with Lab Information 

Management Systems 

and Manufacturing 

Process Control 

Systems 

Enabling Contract 

Manufacturing in 

the Cloud 

Orchestrating 

End-to-End 

Supply Chain 

& 

Manufacturing 

IoT Aware 

Business Processes 

Enabling Smart 

Manufacturing 

Vision 

Cloud-enabled 

enterprise applications: 

MES and LIMS 

systems 

End-to-end Cloud 

solutions for 

manufacturing value 

chain 

MultiEnterprise 

Manufacturing 

Management on 

the Cloud 

IoT devices 

integrated with 

multitude of 

enterprise systems 

Perspective Manufacturing 

Enterprise 

Cloud Platform 

Vendor & 

Manufacturing 

Services Vendor 

Manufacturing 

Service Vendor 

Manufacturing 

Systems Modeler 

Key Issues 

Technical 

interoperability issues 

of connecting an onpremise system to 

Cloud-enabled LIMS 

and MES 

Heterogeneous 

enterprise messaging 

and communication 

issues; highly 

variable, proprietary 

manufacturing and 

logistics processes 

MES vendors 

lacking 

interface 

standards 

How to integrate 

and translate huge 

amounts of data into 

relevant information 

and knowledge 

3.1.1 Integration Challenges with Lab Information Management Systems and 

Manufacturing Process Control Systems 

Scott Nieman, Enterprise Integration Architect, Land O'Lakes 

At Land O'Lakes Lab, management and control functions are implemented in two systems: 

Laboratory Information Management Systems (LIMS) and Manufacturing Process Control 

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Systems, respectively. Each system interacts with hardware using Programmable Logic 

Controllers or dedicated computers. These interactions often require solutions to a variety of 

integration problems that arise because many equipment manufacturers still use proprietary data 

formats such as comma-separated-value (CSV) files. Such formats require integration solutions 

to be implemented using bi-directional, point-to-point, integration-design patterns. It has been 

proven many times over that such design patterns are not sustainable over time. This creates a 

huge problem: new integration solutions must be found, many times over. 

Switching to Cloud-based services will not solve this problem directly. Some vendors currently 

use what are called “code-first” web service Application Programming Interfaces (APIs) such as 

Representational State Transfer (REST) and OData for software integration. Despite being a 

step forward, these types of APIs change with each new release of the software, thus recreating 

the sustainability problems discussed above. Other vendors use “wrapper-based” web services 

APIs as their user interface. This approach leads to “chatty” integration processes with multiple 

Hyper Text Transfer Protocol (HTTP) round-trips to perform a single transaction. 

What is needed is a new breed of controller software that includes a hardware-specific “frontend” to pass instructions and data back and forth. This new breed would use standardized 

“contract-first” APIs such as OAGIS and B2MML to facilitate integration and reduce chattiness. 

It would also leverage IoT paradigms for securing API access using HTTP security protocols 

such as OAuth2.0 and OpenID Connect, which are needed when coming directly from the Cloud 

into an enterprise’s “trusted zone”. 

Using standards-based APIs and IoT strategies would have three major benefits. First, it would 

open the doors for Small- to Medium-sized Enterprises (SMEs) to use “pay-as-you-go” Cloud 

solutions. Second, it would allow Original Equipment Manufacturers (OEMs) to reduce the cost 

of replacing aging monolithic software systems. Third, it would provide a foundation for 

developing a set of standard integration practices. 

To help demonstrate the potential for these benefits, an open, integration test bed should be 

developed. As part of that testbed, methods and measurement tools should be developed as a 

basis for either a self-certification or third-party-certification process. 

3.1.2 Enabling Contract Manufacturing in the Cloud 

Matt Johnson, Senior Director, Oracle 

Cloud-based solutions must treat both contract manufacturers and third-party logistics providers 

as part of an end-to-end, life-cycle manufacturing process. A significant number of high-tech 

manufacturing companies already employ both of them to produce and deliver their products. 

However, communication among these companies and their suppliers are both intermittent and 

non-standardized. This has resulted in greater supply volatility and longer manufacturing cycle 

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times. Even a small improvement in the manufacturing cycle time or of third-party process 

reliability would have an enormous positive impact. 

Cloud-based platforms offer a way to get that improvement because they allow trading partners 

to access a consolidated set of manufacturing application features on a uniform platform. This 

platform eliminates many of the functional gaps and party variations that often create huge 

barriers. Moreover, independent companies can still use different in-house solutions that (1) 

communicate using a variety of methods and message standards; and (2) implement 

manufacturing and logistics processes with variations in the number and sequence of steps. 

By using Cloud services, companies can use flexible, standards-based connectors to 

communicate more efficiently with contract manufacturers. To enable that, however, Cloudbased-manufacturing service providers should agree upon (1) messages for coordinating 

onboarding and profile management among their client communities; (2) a common Business-tobusiness (B2B) messaging standard (OAGIS) that all B2B service providers can support; and (3) 

standard message choreographies based upon the Business Process Model and Notation (BPMN) 

for contract manufacturing. 

3.1.3 Orchestrating End-to-End Supply Chain & Manufacturing 

Pawan Joshi, Vice President Strategy, E2open 

More and more supply chain partners of many OEMs reside in countries outside the United 

States. At the same time, the OEMs themselves operate largely digitally within their own silos, 

communicating with the partners using only spreadsheets and faxes. However, the increasingly 

large quantities of data being exchanged between them are making those paper-based tools 

obsolete. So, OEMs and supply partners must agree on new methods and tools they will use to 

deal with the flood. E2open’s goal is to provide both of them. 

Currently, E2open is focused on methods and tools for the macro-supply chain. The strategy of 

E2open is to enable one version of “truth”, and to enable three shared capabilities: visibility, 

management-by-exception, and empowered decision-making. OEMs need these three 

capabilities most critically during introduction of new technologies and products. These are the 

times when the company owns the design but manufacturing is distributed - more often than not, 

around the globe. There are two challenges whose resolution requires those three capabilities. 

How can the OEM keep track of the inventories and shop floor status of their partners when they 

are scattered around the globe? And, how do the partners provide this information but retain 

flexibility to prioritize customized products? 

From the perspective of E2open, success will depend on how much our products help 

manufacturers answer these questions. We believe that an opportunity exists to wrap standards 

around the whole workflow-driven approach. There is however, a big barrier: no standards exist 

in the MES area. E2open typically has to deal with proprietary flat files, which are very specific 

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and quite different from one MES system to another. Things just go wrong all the time with this 

approach. We need a better way to be able to communicate with these systems, particularly 

when dealing with exceptions in manufacturing processes. Standards development 

organizations, such as OAGi, should establish working groups for definitions of new 

nouns/Business Object Documents (BODs) and revisit these nouns for their applicability in the 

Smart Manufacturing era. 

3.1.4 IoT Aware Business Processes Enabling Smart Manufacturing 

Denis Gagne, CEO, Trisotech 

Smart Manufacturing will require manufacturing enterprise systems to interface with IoT 

devices, third-party logistics, procurement, and ordering, among others. To achieve this, 

business process management (BPM) will play a key role. BPM provides the means to (1) 

manage end-to-end, IoT-aware processes; and (2) orchestrate the way enterprise systems take 

part in them. 

Business Process Modeling Notation (BPMN) includes many of constructs needed for modeling 

BPM-related manufacturing processes. In addition, independent software vendors (ISVs) have 

recently started to include and demonstrate that BPMN modeling capabilities can take into 

account IoT. For example, SAP demonstrated a coordinated solution for modeling oil-pipeline 

sensor data with PLM data and communicating that data to a technician’s iWatch. Another 

company, W4, showed fall-sensing capability in monitoring assisted living spaces. This required 

managing two layers of business processes: one coordinating sensor information and the other 

coordinating people activities. 

In both cases, however, the best way to integrate and translate the increasingly larger amounts of 

data into the relevant information and knowledge is not clear. There are three areas where 

critical advances are needed. The first involves the semantics and analytics needed to ensure that 

we are collecting only relevant data. The second involves the robust connectivity to ensure that 

relevant business events are gathered, The third involves the IoT-related ontologies to ensure 

that better reasoning and better decisions can be made based on current event data. 

3.1.5 Discussion 

Scott Nieman pointed it was easy to model “the happy path” of process execution but much 

harder to model “the unhappy paths” of which there are many. Matt Johnson suggested 

compensatory models as a way to address that issue. Matt Johnson stated that current practice in 

supply-chain visibility is largely based on portals and spreadsheets. 

Pawan Joshi stated that MES vendors typically do not use interoperability standards; instead, 

they use proprietary flat files specific to the vendor. He made the point that a new, collaborative 

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initiative (supported by adequate NIST involvement) could be started to enable MES vendors to 

know about and use the desired integration capabilities out of the box. 

Denis Gagne pointed at CMMN (Case Management Model and Notation), which is a sibling of 

BPMN, to address and handle exceptions to the “happy path.” Serm Kulvatuntyou asked how to 

use business processes with smart devices? Pawan Joshi stated business processes will still be 

needed to orchestrate smart devices, but they will not be prescriptive. Rather they must be 

abstract, parametrized, and flexible; they must also allow for real-time monitoring and reactive 

system behavior. 

3.2 Position Statements & Issues Identification – Session 2 

The following table summarizes presentations given in the second session of the workshop. 

Presenter 

Name, 

Company 

Jim Davis 

UCLA & SMLC 

Jon Hirschtick, 

Onshape 

Dennis Pegden, 

Simio 

John Siudut, 

MESA 

International 

Presentation Title 

Smart 

Manufacturing 

Leadership 

Coalition 

Full-Cloud 3D CAD: 

An Open Platform 

For Faster Design 

and Manufacturing 

Executing 

Simulation 

Experiments on 

the Cloud 

Introduction to 

MESA 

International 

Vision 

Smart Manufacturing 

enterprise, value 

chains, and 

ecosystems 

Full-Cloud 3D CAD 

Systems 

Cloud-enabled 

manufacturing 

simulation 

execution 

Automated 

integration of 

manufacturing 

enterprise 

systems/services 

Perspective 

Manufacturing 

Enterprise; Value 

Chain; Ecosystem 

Manufacturing 

Services Vendor 

Manufacturing 

Services Vendor 

Manufacturing 

Enterprise, 

Manufacturing 

Services Vendor 

Key Issues 

Orchestration of 

workflows; Data 

management; Apps 

Access & Execution; 

Ecosystem 

management 

Lack of solutions for 

compatible, complete 

design & 

manufacturing 

ecosystem 

Data Integration 

Lack of method to 

automate 

integration; Lack 

of bottom-up 

modeling methods 

to use proprietary 

efforts that could 

serve as model 

3.2.1 Smart Manufacturing Leadership Coalition (SMLC) 

Jim Davis, Vice Provost IT, UCLA & SMLC 

Smart Manufacturing enterprises, value chains, and ecosystems have the potential to (1) be more 

value oriented and responsive to demands of dynamic markets; (2) achieve substantially 

increased productivity, performance, and innovation agility; (3) accelerate the adoption of new 

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physical and cyber technologies; (4) radically improve environmental sustainability, material 

waste, and energy productivity; and (5) approach zero field failures and incidents. 

Business challenges that must be overcome to achieve that potential include (1) new types of 

business models and metrics that emphasize business agility, asset management, and supplier 

integration; (2) the realization that everyone’s returns on investment are interdependent but 

motivated differently; (3) new collaboration models that provide incentives, other than cost 

reduction, for OEMs to invest in advanced technologies for their SME partners; and (4) new 

market drivers that favor the use of interoperability standards, inter-system cyber security, lowcost scaled infrastructure and low-complexity technology solutions. 

The open Cloud provides a number of opportunities to address these challenges. It will increase 

the availability of—and lower the risk, the cost, and the barriers to— real-time data, information, 

analytics, and metrics across the supply network. This will improve access to integrated patterns 

of operation, untapped performance, productivity, and optimization opportunities. It will also 

improve cyber security and accelerate smart-system development, deployment, performance, and 

reuse. The Cloud has the capability to manage provider-neutral, trusted-marketplace access to 

data, apps, and deployment services for manufacturers. Finally, using the Cloud enables 

manufacturers to retrofit existing service-based control and automation systems. 

To make use of those opportunities, several technical issues must be resolved. Dynamic 

orchestration of decision/action workflows in heterogeneous environments without losing control 

of state is still not possible. Data contextualization, modeling support, uncertainly handling, 

synchronization, and human-in-the-loop are just now becoming important issues. There is an 

emerging view of apps as code layers associated with application environments. Accessing and 

executing this view in the Cloud is just beginning now. 

Standards will play key roles in addressing these technical issues by enabling (1) standards-based 

structure for apps and composite apps regardless of function; (2) composability at workflow 

level, customization at app parameter level, and functional abstraction; (3) co-existing 

commercial, open products/services, public/private resources, R&D software, and code 

certifications; and (4) open vendor agnostic architecture, open access, open marketplace, open 

data, and managed specification. 

Successfully addressing all of the aforementioned challenges would enable (1) real-time, 

enterprise-wide, data analytics and asset optimization; (2) configurable modeling and data 

analysis; (3) scale-up of IT infrastructure across the entire supply base; (4) increased productivity 

and more efficient use of resources and suppliers; (5) sustained growth in manufacturing base. 

3.2.2 Full-Cloud 3D CAD: An Open Platform For Faster Design and Manufacturing 

Jon Hirschtick, Founder and Chairman, Onshape 

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Originally, three-dimensional (3D) CAD systems were architected with a single designer in 

mind. Their major output was CAD files written to the designer’s local computer disk. Today, 

design is performed in global teams that are distributed, fragmented, and constantly changing. 

As a result, these original CAD systems, even with the aid of file management tools, are slowing 

down design. Problems include (1) difficulty locating the latest version of the design data; (2) 

locking and unlocking files for check in and check out restricted team productivity; and (3) 

exchanging files from one computer to another, even using the same CAD system, was 

expensive and time consuming. 

A new generation of Cloud-based 3D CAD systems is envisioned to fix these problems. 

Everyone on the design team can work together using the full 3D CAD system on any browser, 

phone, or tablet. The single instance containing the CAD system data and the master CAD data 

resides in one place in the Cloud and is never copied anywhere. All users look at and edit the 

same data at the same time. The result is that teams can design products better and faster. And, 

perhaps they can even have more fun doing it. 

Standards are needed to realize this vision. Such standards would include formats for design 

data exchange (for example: JT format), and standards for REST APIs and associated data in 

JSON, XML, or other text formats. The combination of full-Cloud 3D CAD with these 

standards would enable design teams to integrate and link complete, Cloud-based toolchains. 

3.2.3 Executing Simulation Experiments on the Cloud 

Dennis Pegden, CEO, Simio 

Cloud computing provides a powerful new platform for running manufacturing software. For the 

first time, it is now possible to rapidly scale up to a large number of virtual processors on an asneeded basis. Manufacturing software applications that have a large number of parallel 

execution streams can exploit this capability to execute in a fraction of the time that would be 

normally required on a traditional, non-scalable platform. 

One of the application areas that is particularly well suited for Cloud computing is simulation 

applied to both design and operation of manufacturing systems. In these applications, there is 

typically a need to run many different simulation scenarios, and also replicate each scenario 

many times using different random number streams. With Cloud computing, the entire 

simulation experiment can be run simultaneously across all scenarios and all replications. This 

means that the complete experiment can be run in the time that it would normally take to execute 

a single replication within the experiment. 

This presentation discussed the application of Cloud computing to manufacturing simulation 

applications. Specifically, this presentation discussed the use of the Simio Portal for executing 

large-scale simulation experiments on the Microsoft Azure platform. 

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3.2.4 Introduction to MESA International 

Jon Siudut, MESA International 

MES independent software vendors (ISVs) face challenges of integration among disparate 

Cloud-solution providers whenever they interface with other MES providers. Ease of systems 

interface/integration is a big business opportunity and challenge. Reduction by 20% of 

integration cost may be possible. 

The Open Cloud Opportunity consists of three major services: data, analysis, and authoring. 

Data services including storage and format translation. Analysis services include asynchronous 

statistical correlation. Authoring services can be applied to document and file viewers. 

However, the major technical issue remains: no current method exists to help automate the 

integration. 

From the MES end-users perspective, integrating with external suppliers and their own IT 

business systems is still a major problems. Here, too, ease of systems interface/integration is a 

big business opportunity and challenge. Reduction by 20% of integration cost may be possible. 

The Open Cloud Opportunity involves definition of supply-chain, and interface definitions based 

on standards such as Supply Chain Operations Reference (SCOR) model among systems. These 

interface definitions, however, must be augmented with supply-chain data exchanges needed for 

controlled communications tied to contracts between the supplier tiers. In addition, Identity 

Verification Services are needed to ensure person/machine authorization. 

A role for standards could include leading interface-specification methods and tools to aid 

automation. 

3.2.5 Discussion 

Jim Davis took a very broad view of the Smart Manufacturing enterprise. In that view, the Smart 

Manufacturing enterprise is at the intersection of agile, demand-driven supply chains, sustainable 

and safe production, and plant-wide optimization. He stated the need and opportunity to reduce 

the cost of implementing modeling and simulation of Smart Manufacturing systems by 80%. He 

pointed that “micro-services” are a novel, potentially influential way to deliver manufacturing 

functions. The question was raised about whether these micro-services would be more prevalent 

in the Cloud of the future than monolithic applications. Jon Hirschtick stated the need for 

graphics software that runs well in the browser. 

Dennis Pegden stated the need to drive Cloud computing as a new, scalable platform, which 

could make it easy to add and provide services to new manufacturing-software users. He also 

expressed the need for Cloud-based, 3D animation environments and for easy access to 

distributed model data. Matt Johnson stated a need to learn about the current state of standards 

12
 
 

 

 

 

 

 

 

 

for (1) representing distributed simulations for outsourced supply chains; (2) protocols for 

federating those simulations; and (3) managing the heterogeneity of data, models, and platforms. 

Jon Siudut focused on issues facing MES ISVs and end users. He also introduced the concept of 

component-as-a-service (CaaS). In MESA’s view, John stated, CaaS has the potential to 

revolutionize application design and delivery by allowing composition of functions and 

components to meet needs of the customers. 

John Siudut pointed at the need for meta-data modeling and high-level process modeling, master 

data management and data definitions for the business process, and transactional data modeling – 

dropping transactions into the data and at different process levels. 

3.3 Position Statements & Issues Identification – Session 3 

The following table summarizes the presentations of the third session of the workshop. 

Presenter 

Name, 

Company 

Dave Noller, 

IBM 

Gregory 

Harris, 

DoD 

Shelley 

Gretlein, 

National 

Instruments 

Chris Monchinski 

& Dan Trout, 

Automated Control 

Concepts 

Kirk Smith, 

Intel 

Presentation Title 

Manufactur 

ing in the 

Age of IoT 

and Cloud: 

Opportunit 

y and 

Challenge 

DMDII 

(Digital 

Manufactu 

ring and 

Design 

Innovation 

Institute) 

Industrial 

Internet of 

Things: The 

Opportunities 

and 

Challenges for 

Engineers and 

Scientists 

Enabling 

Integration of 

Manufacturing 

Operations to the 

Cloud 

Smart 

Manufacturing 

Architectures, 

Implementatio 

ns, and the 

Internet of 

Things 

Vision 

Cloud, 

Mobile, IoT 

for 

Manufacturi 

ng 

Connected 

& Protected 

Digital 

Manufacturi 

ng 

Enterprise 

IoT-Enabled 

Manufacturing 

Enterprise 

Cloud-to-OnPremise Integration 

of Mfg Enterprise 

and Real Time 

Factory Floor 

Integrated 

Solutions and 

Architectures 

for Smart 

Manufacturing 

and IoT 

Perspective Technology 

Provider 

Government 

Agency and 

Manufacturi 

ng 

Enterprise 

SW/HW 

Platform and 

Manufacturing 

Services 

Vendor 

Manufacturing 

Standards 

Development 

Organization 

Cloud Platform 

and 

Manufacturing 

Services Vendor 

13
 
 

 

 

 

 

 

 

 

 

 

Key Issues 

Role, 

management 

& life cycle 

of industry 

standards 

Noninteroperabl 

e enterprise 

models for 

manufacturi 

ng software; 

infrastructur 

e gap 

Incomplete 

technical 

definitions and 

need for 

flexible 

networks of 

systems 

Collaborations 

among industry 

groups and SDOs 

need to be ensured; 

knowledge 

management for 

effective 

integration; vendor 

adoption of 

integration 

standards 

Security, device 

discovery & 

provisioning, 

data 

normalization, 

analytics 

infrastructure, 

new business 

model 

infrastructure 

3.3.1 Manufacturing in the Age of IoT and Cloud: Opportunity and Challenge 

Dave Noller, Manager, SWG Industrial Sector Strategy & Integration, IBM 

The rapid advance of new applications and application-integration models, based on emerging 

technologies such as Cloud, Mobile, and IoT, presents manufacturing with new opportunities, 

but also presents new challenges. These technologies promise lowered support costs, accelerated 

deployment times, simplified creation of “composite applications” (such as those described 

formerly by Manufacturing 2.0 and now by Industry 4.0), and mobile communications. The 

challenges, on the other hand, include increasing dependence on technology provided and (in 

many cases) supported by others, security, and new models for application deployment and 

development. 

The role of industry standards, both for the technology stack as well as for application 

interoperability, is morphing (by necessity) away from approaches such as Enterprise 

Application Integration (EAI) and Service-oriented Architecture (SOA). 

Like other technology providers, IBM is evolving by developing and acquiring new technology 

to respond to the changing environment and needs. In the case of IBM, this evolution is based 

on a strategy of supporting and embracing open-source initiatives (e.g., Open Stack) and 

releasing products based on those technologies and initiatives. The next logical steps are (1) for 

vendors, standards organizations, and manufacturers to agree on what needs to be done to update 

the old notions of industry standards (such as OAGIS) and EAI, or even SOA; and (2) apply 

them to the new, composite, IoT-enabled applications being realized today in the Cloud. 

3.3.2 DMDII (Digital Manufacturing and Design Innovation Institute) 

Gregory Harris, Program Manager DMDII, DoD 

14
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

We need a protected and connected digital enterprise, secure digital thread, secure enabling 

environment, including handheld devices that we use for multiple activities (similar to financial 

industry). The challenges we are facing include: (1) Lack of means enabling access and 

utilization of the unconnected systems in use today; (2) Lack of digital manufacturing business 

solutions; (3) Lack of platforms on which the digital manufacturing business solutions are hosted; 

and (4) Cyber security risks (both perceived and real) that keep manufacturers from trusting 

systems. 

Benefits of addressing these challenges include: (1) New businesses will be created, including 

those providing manufacturing data analysis; (2) Reestablishment of the US industrial base as the 

world leader in efficient and agile manufacturing; (3) Restoration of a robust American middle 

class; and (4) Large savings from the efficient transfer of data between disparate systems. 

Open Cloud opportunities include the following: (1) Open Cloud allows disruption to occur in 

manufacturing industry with “apps.” In the future, manufacturing software solutions will be 

small, inexpensive, and user-friendly; (2) Interoperability issues can be addressed broadly instead 

of on a point-solution basis; (3) Access to tools and capabilities that the Small and Medium 

Enterprises do not have access to today; (4) Opportunity for Supply Chain growth through 

collaboration tools; and (5) Enabling plug-and-play digital functionality across the entire digital 

thread. 

Technical issues that need to be addressed include: (1) Enterprise models for manufacturing 

software are proprietary and not interoperable; (2) Methods ensuring that credentialed 

identification is accessible, transferrable, and retrievable; (3) From a government perspective, there 

is a serious infrastructure gap, particularly with the Organic Industrial Base; and (4) Processes 

and procedures to reuse data in multiple points throughout the life cycle of a system. 

Roles of standards are the following: (1) Standards are necessary to bring order to the Wild, Wild, 

West of Digital Manufacturing and Design that we are experiencing today; and (2) There are gaps 

and overlaps in standards today that must be bridged and harmonized to bring about 

interoperability and ease of function for efficient data exchange. 

3.3.3 Industrial Internet of Things (IIOT): The Opportunities and Challenges for 

Engineers and Scientists 

Shelley Gretlein, Director Product Marketing, Platform Software & Customer Education, 

National Instruments 

The IIoT concept implies a vast number of connected industrial systems that are communicating 

and coordinating their data analytics and decision-making to improve industrial performance and 

benefit society as a whole. Applying this concept to factories and machines will facilitate new 

solutions to production and logistics problems in ways that were previously inconceivable, 

thereby improving and increasing innovation considerably. 

15
 
 

 

 

 

 

 

 

 

However, as innovation grows, so does the complexity. This means that implementing the IIoT 

concept will spawn new challenges that no company can address on its own. For example, IIoT 

adds strict requirements to its local networks for latency, determinism, and bandwidth. At the 

machine level, such requirements are necessary because precision machines can fail if the timing 

of communications is off even by a millisecond. At the supply-chain level, timing is rarely a 

serious problem, but security is a problem of paramount importance. Global communication 

networks link supply chain partners, often over vast geographical distances. IIoT systems use 

these networks to transmit vital information among those partners. Maintaining security is 

difficult because these systems need to be continually modified and maintained to meet everchanging functionality and system-maintenance requirements. As more capabilities are added, 

new security needs can arise. This means that IIOT systems have to be tracked routinely to 

ensure that they meet those needs. 

Open Cloud presents a way forward that involves a platform-based approach. This approach is 

based on a single, flexible, hardware architecture that is deployed across many applications. 

This architecture removes a substantial amount of hardware complexity and it makes security 

and update problems primarily software challenges. 

The only way to meet the needs of today and tomorrow is by deploying a network of systems 

flexible enough to evolve and adapt. The ongoing design of the IIoT represents a massive 

business and technology opportunity. Engineers and scientists are already implementing systems 

on the leading edge of the IIoT, but many things still need to be defined and much work needs to 

be done. 

3.3.4 Enabling Integration of Manufacturing Operations to the Cloud 

Chris Monchinski & Dan Trout, Automated Control Concepts 

Integration between Level 4 Systems and Real Time Factory Floor Automation is being made 

possible with ISA 95 Cloud-to-On-Premise Integration of Manufacturing Enterprise and Real 

Time Factory Floor. 

Four major business challenges make this integration difficult. First, integrating new, Cloudbased, hybrid architectures is increasingly challenging. Security, protection of intellectual 

property, customer data, and system robustness are all of paramount importance. Second, 

manufacturers are adopting business-level systems that are increasingly moving toward Cloudbased architectures (software-as-a-service, software rentals, third party contracts and off-site 

systems). Third, manufacturing systems and IT assets remain fixed assets with real-time 

requirements (near zero latency) and high availability. Fourth, evolving adoption of “TwoTiered” systems requires both Cloud-based and locally hosted solutions increasing integration 

demands. 

16
 
 

 

 

 

 

 

 

Business benefits of addressing the challenges will accrue to both Cloud providers and Cloud 

users. Reducing the risk and cost of integration between Cloud-based assets and fixed assets will 

benefit both providers and users. Reduced asset costs, increased flexibility, increased reliability, 

and robust security are all benefits to users. Without the Cloud, typical software projects took 1‐

2 years and had success rates under 50 %. Using Cloud, typical software projects take 2 months 

to 4 months and have greater than 90 % success rates. 

Standards such as ISA 95 (Control to Enterprise Integration) are facilitators that will allow 

manufacturers to “plug in” to business-based systems hosted in the Cloud. As such, ISA95 will 

enable flexible integration and collaboration, both of which will reduce risk and increase speed 

of implementation and adoption rates of Cloud-based technologies. Finally, ISA 95 provides 

models and definitions of application boundaries based on function. This allows architects to 

define hybrid systems using Cloud and fixed-asset systems, as necessary. 

To enable standards to fulfil their facilitator role, national and international standards groups 

need to continue to collaborate and present a unified voice to manufacturers and to platform and 

service vendors. Once new standards are developed, it is necessary to demonstrate that they 

actually do enable integration. In addition, the experience gained from these demonstrations 

must then turn into toolkits, guidelines, best practices, and industry-specific technical reports. 

Collectively, they will be “key” to facilitating flexible integration strategies that enable 

manufacturing assets to leverage Cloud technology. Adoption by vendors of integration 

standards will be a key to reducing risks associated with interoperability among enterprise 

service vendors. 

Here are a few examples. The guidelines and practices outlined in ISA 99 / 62443 will facilitate 

“integrated” security and best practices for robust integration. ISA 95 / 62264 helps system 

architects define logical boundaries between systems. This allows manufacturing systems to 

integrate with Cloud-based systems, thereby exchanging data reliability and securely. B2MML 

(Business to Manufacturing Markup Language) is an open-source initiative maintained by 

MESA and is an instantiation of the ISA 95 standard in XML and the Web Services Description 

Language (WSDL). 

3.3.5 Smart Manufacturing Architectures, Implementations, and the Internet of Things 

Kirk Smith, Solutions Architect, Industrial and Energy Solutions Division, IoT Group, Intel 

Manufacturing has entered the big-data era, with potential access to more information that can be 

used to increase throughput, boost yields, improve efficiency, and reduce downtime. But for 

many manufacturers, machine tools and processing areas operate in relative silos, without such 

access. So, it is still a major challenge to collect, analyze, and act on data generated across the 

factory floor. IoT is expected to address this challenge. 

17
 
 

 

 

 

 

 

 

 

 

Enabling IoT for industrial environments requires integrated solutions and architectures that 

address a number of key issues, including security, automation, normalization, analytics, and 

infrastructure. World-class security is the foundation for connectivity and traversal of 

manufacturing and enterprise-service-bus domains. Methods to automate discovery and 

provisioning of edge devices will ease deployment and management of devices integrated into an 

IoT architecture. Data normalization, through protocol abstraction, is needed to improve 

interoperability across Sensor-to-Cloud pathways. Broad analytics infrastructure from Edge-toCloud is needed to gain actionable insights and scale quality-of-service across factory, enterprise, 

and Cloud networks. Infrastructure to monetize hardware, software, and data management from 

Edge-to-Cloud will enable new, and extend existing, business models. 

On-Premise, off-premise, and hybrid solutions will need to extend the levels of interoperability 

of today’s co-mingled architectures to realize longer term value propositions. In this 

presentation, we discussed the current areas of focus for bringing IoT Platforms to reality across 

System Integrator and ODM/OEM supplier landscapes. We also discussed the issues of 

immediate focus that warrant increased levels of attention by industry. 

3.3.6 Discussion 

Discussion included the topic of bandwidth availability and need to study its impact on the 

manufacturing Cloud. Also, Dave Noller discussed three possible roles for NIST: to help 

understand why standards are often not adopted, to develop easier-to-use standards, and come up 

with light-weight APIs like MQTT and JSON. To adopt new technology such as IOT and Cloud 

manufacturing, open standards for real interoperability are needed. However, the problem is not 

the lack of such standards. In fact, there are many existing vertical and horizontal integration 

standards. Two questions arise, according to Dave: Are these standards adequate for the new 

technologies? If so, what holds us back from adopting them? A deep analysis is necessary. 

Also, he stated that MES tends to be trying to act as the vertical integration layer today, but is not 

well suited to “out of the box” integration needed to support “Industry 4.0” type initiatives. It 

would be easier if it could be treated as a set of capabilities easily integrated through APIs 

(services). 

Greg Harris suggested that the link between design and manufacturing is still broken, despite 

years of standards development aimed at forging that link. Often in practice, we need to deal 

with loss of data, which means it must be recreated. Worse, key data is often not even captured. 

From DoD’s perspective, if it is not explicitly written into a contract, the data is not provided. 

Even if it is in contract, we frequently don’t know how to use it. Manufacturing software exist in 

silos right now. Product qualification methods are problematic. 

Shelley Gretlein pointed at the need for light-weight APIs and light-weight standards for timing. 

Chris Monchinski and Dan Trout stated it is not clear if and how much of MES functionality 

should be moved into the Cloud. 

18
 
 

Kirk Smith pointed at challenges of collecting, analyzing, integrating, and acting on data 

generated across the factory floor. One such approach was Software Defined Data Analytics, 

which may include plug-and-play devices. Another topic was the kind of 

gateway/communication standards needed to connect the various levels of ISA 95 to Clouds. 

Kirk also pointed at the need to simplify network traversal across Manufacturing Service Bus 

(MSB) and Enterprise Service Bus (ESB) network architectures. Also, he stated importance of 

improving co-existence of near-real-time (NRT) and real-time (RT) networks. 

19
 
 

 

 

 

 

 

 

 

 

4 Issue Identification and Prioritization 

In this section we presents results of the voting that identified top issues considered most 

challenging or urgent by the participants. 

4.1 Top Issues 

Participants identified a number of significant issues in their presentations. (Appendix A 

enumerates these issues. ) The following table shows results of the voting on top issues by the 

participants. 

Issue 

Rank Technical Issue Description Proposing Organization 

1 

There are gaps and overlaps in standards today that must be 

bridged and harmonized to bring about interoperability and 

ease of function for efficient data exchange DoD 

2-3 

Take a hard look at what is inhibiting adoption of standards 

today IBM 

2-3 Establish working group for the definition of new nouns/BODs E2open 

4 

Semantics and analytics to ensure that only relevant data are 

collected from devices to generate business events Trisotech 

5 Vendors to create standards-based APIs/application adapters LOL 

6 

Simplify network traversal across MSB and ESB network 

architectures. Improve co-existence of NRT and RT network 

processing Intel 

7 

Cloud-based manufacturing solution providers should agree 

upon several conditions Oracle 

8-12 Interoperability Test Bed LOL 

8-12 

Data contextualization, modeling support, uncertainty handling, 

synchronization, human in the loop UCLA & SMLC 

8-12 

Composability at workflow level; customization at app 

parameter level; functional abstraction UCLA & SMLC 

8-12 

MES tends to be trying to act as the vertical integration layer 

today IBM 

8-12 Adoption by vendors of integration standards 

Automated Control 

Concepts 

20
 
 

 

 

 

 

 

 

 

 

4.2 Discussion 

Scott Nieman stated that the overlap among standards causes confusion with vendors on exactly 

where to invest money by implementing specific standards. Denis Gagne suggested that NIST 

might support standards analysis and capability identification effort as an unbiased party. Dave 

Noller agreed it would be useful to identify overlaps and gaps in existing standards. Mike 

Rowell suggested that Dave Noller’s graph showing overlaps among standards may be useful for 

an analysis of standard overlaps and capabilities. Chris Monchinski noted that NIST could be 

gathering industry representatives together to analyze and address the current state of standards. 

Matt Johnson pointed out that there are reference models defining capabilities that can be used 

for standards gap analysis. 

Yan Lu pointed out that NIST is working on a landscape of standards relevant to Smart 

Manufacturing and will publish a report to document this landscape. NIST is planning to get 

input from SDOs about use of the standards. Denis Gagne mentioned this would be interesting 

for the quality standards adoption. Scott asked whether this would be a living document? Serm 

Kulvatunyou also added that NIST has another document analyzing standards for digital 

manufacturing (factory planning). 

Scott Neiman pointed at the need for manufacturers to have means to capture overarching 

business process models. He asked whether we should reuse certain capabilities in existing 

standards or should we start afresh from specs. Also, he noticed that security has not been 

captured among the issues and was wondering why that was the case. 

Matt Johnson suggested that the community could invite vendors to talk about how they use 

standards, and to identify many variations that are taking place in manufacturing. He identified 

the need to understand better Cloud impact on manufacturing standards. Greg Harris agreed that 

we need to engage vendors in identifying ways to fix the issues with standards adoption for 

manufacturing. Scott Neiman wants to get a better understanding regarding what it takes to 

move into the Cloud. Matt Johnson suggested that, if we assume there are half a dozen Cloud 

manufacturing systems implementers, it would be feasible to see what the vendors provide in 

standards-based capabilities and what they provide for manufacturers to have Cloud presence. 

21
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

5 Conclusions 

The Cloud-enabled technological advances present an unprecedented opportunity as well as new, 

very significant challenges to the manufacturing community on its way to achieving Smart 

Manufacturing systems. This OAGi/NIST Open Cloud Architectures for Smart Manufacturing 

workshop brought a variety of organizations from public and private industry sectors to identify, 

discuss, and prioritize these challenges. Speakers included manufacturers, enterprise architects, 

integration architects, strategists, system developers, and researchers. The following are key 

conclusions that emerged from the workshop. 

1. Existing standards are inadequate to enable the Cloud-based services needed for Smart 

Manufacturing 

The state of standards for Smart Manufacturing is not ideal, to say the least. Greg Harris stated 

that gaps and overlaps in standards today must be bridged and harmonized to bring about 

interoperability and ease of function for efficient data exchange (3.3.2). Denis Gagne pointed that 

a critical area where advances are needed involves capturing standards semantics and analytics to 

ensure only relevant data are collected (3.1.4). Jim Davis pointed that composability at the 

workflow level, customization at the app parameter level, and functional abstraction will need to 

be enabled by standards for Smart Manufacturing (3.2.1). Dave Noller asked for a deeper 

analysis to find out whether current standards are adequate for the new technologies and, if so, 

what holds us back from adopting them (3.3.6). Matt Johnson and Pawan Joshi asserted a need 

to find about the current state of standards for (1) representing distributed simulations for 

outsourced supply chains; (2) protocols for federating those simulations; and (3) managing the 

heterogeneity of data, models, and platforms (3.2.5). Shelley Gretlein pointed at the need for 

light-weight APIs and light-weight standards for timing (3.3.6). 

2. Standards adoption is severely impeded by confusion, complexity, and the lack of 

efficient tools 

Many participants emphasized the importance of adoption and use of standards by ISVs who 

develop their applications and services for Smart Manufacturing systems. Scott Nieman pointed 

that standardized “contract-first” APIs, such as OAGIS and B2MML, should be adopted by ISVs 

(3.1.1). Chris Monchinski and Dan Trout stated that adoption by vendors of integration 

standards will be a key to reducing risks to interoperability among enterprise service vendors 

(3.3.4). Matt Johnson pointed that a key to standards adoption is that the Cloud-basedmanufacturing service providers agree upon (1) messages for coordinating onboarding and 

profile management among their client communities; (2) a B2B messaging standard (OAGIS) 

that all B2B service providers can support; and (3) standard message choreographies based upon 

BPMN notation for contract manufacturing (3.1.2). Pawan Joshi asserted that MES vendors 

typically do not use interoperability standards, instead, they use proprietary flat files specific to 

22
 
 

 

 

 

 

 

 

 

 

 

the vendor. He made the point that a new, collaborative initiative could be started to enable the 

MES vendors to know about and use the required integration capabilities out of the box (3.1.5). 

3. We need new architectures to enable service-oriented Smart Manufacturing 

Presentations and discussions identified a number of challenges and gaps in the knowledge 

within the manufacturing community for architecting Smart Manufacturing systems. Dave 

Noller stated that manufacturing execution systems (MES) tend to be trying to act as the vertical 

integration layer today, but is not well suited to “out of the box” integration needed to support 

“Industry 4.0” type initiatives (3.3.6). Jim Davis states that synchronization and human-in-theloop are just now becoming important architecture issues (3.2.1). Matt Johnson stated that 

current practice in supply-chain visibility is largely based on dated solutions, including portals 

and spreadsheets (3.1.5). Jim Davis pointed to “micro-services” as a novel, potentially 

influential way to deliver manufacturing functions, which needs to be explored further (3.2.5). 

CaaS architecture style has the potential to revolutionize application design and delivery by 

allowing composition of functions and components to meet needs of the customers (3.2.5). Chris 

Monchinski and Dan Trout pointed at the need for research in Smart Manufacturing since it is 

not clear if and how much of MES functionality should be moved into the Cloud (3.3.6) 

4. We need new standards development and standards management processes to support 

the rapid evolution of Smart Manufacturing 

Presentations and discussions at the workshop pointed that current standards development and 

management processes are inadequate for enabling the desired agility, flexibility, and capabilities 

of Smart Manufacturing systems. Pawan Joshi points out that standards development 

organizations, such as OAGi, should establish working groups for definitions of new 

nouns/BODs and revisit these nouns for their applicability in the Smart Manufacturing era 

(3.1.3). Jim Davis stated that data contextualization, modeling support, and uncertainly handling 

are just now becoming important issues to take into account in standards development (3.2.1). 

Scott Neiman proposed that to demonstrate benefits of Cloud solutions for Smart Manufacturing, 

an open, integration test bed should be developed. As part of that testbed, methods and 

measurement tools should be developed as a basis for either a self-certification or third-partycertification process (3.1.1). Scott Nieman pointed it was easy to model “the happy path” of 

process execution but much harder to model “the unhappy paths” of which there are many 

(3.1.5). Denis Gagne pointed at CMMN, which is a sibling of BPMN, to address and handle 

exceptions to the “happy path” (3.1.5). Pawan Joshi stated that business processes that 

orchestrate smart devices will not be prescriptive. Rather they must be abstract, parametrized, 

and flexible, and they must also allow for real-time monitoring and reactive system behavior 

(3.1.5). Jim Davis stated the need and opportunity to reduce cost of implementing modeling and 

simulation of Smart Manufacturing systems by 80% (3.2.5). John Siudut pointed at the need for 

meta-data modeling and high-level process modeling, master data management and data 

definitions for the business process, and transactional data modeling (3.2.5). 

23
 
 

 

 

5. Cloud platforms can provide the infrastructure needed to implement Smart 

Manufacturing Enterprises, but challenges remain 

Cloud platforms need to ensure that the Smart Manufacturing systems requirements can be met. 

Dennis Pegden asserted the need to drive Cloud computing as a new, scalable platform, which 

could make it easy to add and provide services to new manufacturing-software users. He also 

expressed the need for Cloud-based, 3D animation environments and for easy access to 

distributed model data (3.2.5). Jon Hirschtick stated the need for graphics software that runs 

well in the browser (3.2.5). Kirk Smith pointed at challenges of collecting, analyzing, 

integrating, and acting on data generated across the factory floor. He also pointed to the need to 

simplify network traversal across MSB and ESB network architectures, as well as to improve coexistence of NRT and RT networks (3.3.6). 

24
 
 

 

Appendix A – Issues identified by the workshop participants 

The following table summarizes the issues identified by the presenters in their submissions, 

which were provided as input for the voting process to identify top priority issues. 

No. Technical Issue Description 

Proposing 

Organization 

1 Vendors to create standards-based APIs/application adapters LOL 

2 

Pushing API Gateway capabilities to a more federated IoT model is 

extremely challenging LOL 

3 Interoperability Test Bed LOL 

4 Independent companies still use different solutions in-house Oracle 

5 

Cloud-based manufacturing solution providers should agree upon 

several conditions Oracle 

6 N/A OAGi 

7 Feedback on fit/non-fit with your architecture E2open 

8 

Semantics and analytics to ensure that only relevant data are collected 

from devices to generate business events Trisotech 

9 

Robustness of connectivity to ensure relevant business events are 

provided Trisotech 

10 

Ontologies of IoT sensor and actuator data so we can reason over the 

provided events Trisotech 

11 

Dynamic orchestration of decision/action workflows in heterogeneous 

environments without losing control of state UCLA & SMLC 

12 

Data contextualization, modeling support, uncertainty handling, 

synchronization, human in the loop UCLA & SMLC 

13 

Apps as code layers associated with application environments accessed 

and executed in the Cloud UCLA & SMLC 

14 

Strong data ownership, security and cyberattack protocols, managed 

community sharing and marketplace UCLA & SMLC 

15 

Standards based structure for apps and composite apps regardless of 

function UCLA & SMLC 

16 

Composability at workflow level; customization at app parameter level; 

functional abstraction UCLA & SMLC 

17 

Co-existing commercial, open products/services, public/private 

resources, R&D software, code certifications UCLA & SMLC 

18 

Open vendor agnostic architecture, open access, open marketplace, open 

data, managed specification UCLA & SMLC 

19 

Lack of solutions to ensure compatibility and enable complete design 

and manufacturing ecosystem Onshape 

25
 

 

 

 

 

 

20 

Standards would include formats for data that could be imported and 

exported with the Cloud system (example: JT format), and standards for 

REST APIs and associated data in JSON, XML, or other text formats Onshape 

21 

The combination of full-Cloud 3D CAD plus these standards would let 

design and manufacturing teams integrate and link complete Cloudbased toolchains Onshape 

22 Data Integration Simio 

23 No current method to help automate integration 

MESA 

International 

24 

Supply Chain Data Exchanges for controlled communications tied to 

contracts between the supplier tiers 

MESA 

International 

25 Identity Verification Services to ensure person/machine authorization 

MESA 

International 

26 Lead interface specification methods 

MESA 

International 

27 Solutions enabling layered, distributed architecture 

MESA 

International 

28 Identify the issue places along the digital thread, integration standards 

MESA 

International 

29 

Interoperability standards are still not widely adopted, so “mapping” still 

has to occur somewhere and is difficult IBM 

30 

Interoperability standards today are “heavy”, and do not lend themselves 

to easy usage for “agile” creation of applications (e.g., for mobile) in 

the “integration Cloud” IBM 

31 MES tends to be trying to act as the vertical integration layer today IBM 

32 Take a hard look at what is inhibiting adoption today, and so on IBM 

33 

Enterprise model for manufacturing software is proprietary and not 

interoperable DoD 

34 

Methods ensuring that credentialed identification is accessible, 

transferrable and retrievable DoD 

35 

From a government perspective, there is a serious infrastructure gap, 

particularly with the Organic Industrial Base DoD 

36 

Processes and procedures to reuse data at multiple points throughout the 

life cycle of a system DoD 

37 

Standards are necessary to bring order to the Wild, Wild, West of 

Digital Manufacturing and Design that we are experiencing today DoD 

38 

There are gaps and overlaps in standards today that must be bridged and 

harmonized to bring about interoperability and ease of function for 

efficient data exchange DoD 

39 N/A 

National 

Instruments 

26
 

 

40 

Collaboration with several industry-specific standard groups has 

facilitated adoption of ISA 95 in a wide variety of industries 

Automated 

Control 

Concepts 

41 

National and International Standards groups need to continue to 

collaborate and present a unified voice to the manufacture and 

software/service vendors 

Automated 

Control 

Concepts 

42 The ability to leverage the standards and models 

Automated 

Control 

Concepts 

43 Adoption by vendors of integration standards 

Automated 

Control 

Concepts 

44 

Promotion and adoption of practices outlined in the ISA 99 / 62443 

standard 

Automated 

Control 

Concepts 

45 

The ISA 95 / 62264 Control to Enterprise Integration standard helps 

system architects define logical boundaries between systems 

Automated 

Control 

Concepts 

46 

B2MML (Business to Manufacturing Markup Language is an open 

source initiative maintained by MESA and is an instantiation of the ISA 

95 standard in XML and WSDL 

Automated 

Control 

Concepts 

47 Facilitate best practices and increase manufacturing “nimbleness” 

Automated 

Control 

Concepts 

48 Ease/cost of accessing proprietary networks Intel 

49 Protocol abstraction or translation for IoT use cases Intel 

50 Expertise, legacy components, engineering expense Intel 

51 Connect one-way to hardware roots of trust at both ends of the wire Intel 

52 Long timelines likely for system and network migration Intel 

53 

Simplify network traversal across MSB and ESB network architectures. 

Improve co-existence of NRT and RT network processing Intel 

54 

Remote connectivity, data normalization, model, interoperability, 

maintenance models Intel 

55 

Improve interoperability and scalable access to analytics at the edge and 

Cloud for E2E systems Intel 

56 Establish working group for the definition of new nouns/BODs E2open 

27
Appendix B – Complete Presentations by Workshop Participants 

28
29

Moo-ving to the Cloud ­

LIMS and Process Control System 

Integration Challenges and Opportunities 

Scott Nieman 

Enterprise Integration Architect 

Agenda 

 Introduction to Land O’Lakes 

 Integration Challenges 

 LIMS Model 

 MES Process Control Models 

 Opportunity to move to the Cloud 

 Challenges to overcome 

 Top Priorities 

Copyright © 2013. All rights reserved. 

Land O’Lakes, Inc. today An operating company with three diversified businesses 

 ~10,000 employees  3 diversified businesses 

 3,200 direct producer-members and 1,000  Annual revenue +$14 billion 



member-cooperatives 

Serve +300,000 agricultural producers 

 Goal to double revenues and increase 

international growth in the next 10 years 

Agriculture services, crop inputs Animal nutrition and feed Dairy foods 

 300+ facilities in the U.S. 

Copyright © 2013. All rights reserved. Copyright © 2013. All rights reserved. 

File-based integration challenges 

 Unique, proprietary formats increase implementation costs 

 Extremely prevalent 

 Manually interaction by personnel; very error prone 

 Polling for files requires trigger (watch) files to ensure data file 

completeness 

 Folder change events (trapping OS callback interfaces) across 

WAN is very inconsistent 

 Considered “Anti-pattern #1” at Land O’Lakes 

Copyright © 2013. All rights reserved. 

‘Code-First’ Web Services Challenges 

	 Code-First interfaces are web services (SOAP/ REST) that reflect low 

level implementation (interface) classes 

 Often very chatty 

	 Current LIMS vendor’s API requires 27 round-trips just to integrate one 

TestMaster ‘transaction’; compensatory approach also required 

	 Process Control System vendor implements OData / REST but exposes 

internal ‘entity’ model; each software build to address work-center needs 

required middleware code changes, retest, and redeployment 

 Unique, proprietary formats increase implementation costs 

 Fastest way to achieve N-Square integration problem (Anti-pattern #2) 

Copyright © 2013. All rights reserved. 
30

‘Contract-First’ Standards-Based APIs 

 Presents an opportunity to insulate internal code changes from 

middleware; APIs do not change 

 Requires vendor to expose OAGIS or B2MML based web 

services 

 Requires vendor to provide implementation guidelines, 

specifically how to map data to API 

 Reduces complexity of middleware to pure messaging 

 Improved lifecycle / governance; e.g., more controlled upgrade 

path to newer release of standard 

Copyright © 2013. All rights reserved. 

MES/ LIMS Cloud Opportunities 

 Reduced footprint in corporate data center 

 Multi-tenancy 

 Ability to take software patches if no customizations 

 Distributed, granular capabilities across multiple cloud providers 

 Cloud to Cloud integration when opportunity presents itself 

 Cloud vendor may offer responsibility to certify specific 

equipment, process control systems 

 ‘Pay-as-you-go’ model for Small Manufacturers, who could not 

afford large ERP implementation 

Copyright © 2013. All rights reserved. 

MES in the 

Cloud 

•	 Similar Cloud 


Architecture
 

• Most complex 

integrations 

•	 Requires use of 

API Gateway 

•	 Equipment 

Capabilities vary 

significantly 

•	 JDE Shop Floor 

reduced our 

footprint 

Standards-Based APIs: Current Challenges 

 Large documents: kitchen-sink, need the ability to quickly 

define subsets (contextual); CAM and GEFEG are options 

 Semantics sometimes unclear; generic terms aim to solve 

multiple use cases; even documentation loosely defined 

 Lack of real life implementation guidelines describing specific 

use cases, including data mapping examples 

 Lack of vendor support; ideally these are their application APIs 

 Lack of vendor mappings from internal APIs to standards 

 Implementations ‘bake-in’ specific version of standard 

Copyright © 2013. All rights reserved. 

LIMS in the 

Cloud 

•	 Standards-based 


LIMS APIs
 

•	 Requires use of 

API Gateway 

•	 AuthN, AuthZ, 

Audit (AAA) 

•	 Content 

Protection (CP) 

•	 Distributed 

Denial of 

Service (DDOS) 

Copyright © 2013. All rights reserved. 

Cloud Challenge 

 Connectivity to/from trusted zone (green zone) 

–	 Some plants are in remote rural areas; limited bandwidth and redundancy 

–	 File transfer based approaches are painful; folder change events, polling 

 API Gateways provide trusted access from Cloud to On-Premise 

–	 Authentication, Authorization, and Audit (AAA) required but aging systems have old security 

protocols (NTLM, Kerberos) 

–	 Content Protection; large files, embedded scripts; distributed denial of service (DDOS) 

–	 Technical capability may be best served using a distributed model 

 Internet of Things model with localized API Gateway capabilities 

	 OpenID Connect Client Discovery specification could enable new equipment 

configuration and establish trust as ‘service provider’ 

Copyright © 2013. All rights reserved.	 Copyright © 2013. All rights reserved. 
31

Evolution to the Internet of Things 

• Remove API Gateway? 

Push to device? 

Can we realistically put 

CP and DDOS 

capabilities in a sensor? 

Copyright © 2013. All rights reserved. 

Treating Instruments /Equipment as a Printer 

 Need more modern equipment configuration capabilities 

 Plug-in model required 

 Standard APIs for binding 

 Auto-Discovery of Equipment 

– Metadata tags about the equipment and version of embedded 

system software 

– Equipment capabilities via reference URIs 

 Auto-Configuration; wizard-approach to configure endpoints 

(Cloud URIs, On-prem UNC paths, etc.) 

Copyright © 2013. All rights reserved. 

Test Bed Opportunity Test Bed Inter-operability Platform 

 Integration Simulation 

– Send InspectionOrder, receive simulated TestResults 

– Send Work order, receive signal that work-center job is complete,
 

and receive simulated Ingredient issued messages
 

 Product Certification similar to Drummond Group 

 Inter-operability tests for Basic Profile and Optional Profiles 

 Customers could swap equipment out without significant work 

Copyright © 2013. All rights reserved. Copyright © 2013. All rights reserved. 

Priority of technical issues to address 

 Vendors to create standards-based APIs/application adapters 

– All business application vendors; MES, LIMS, Process Control, ERP 

– Provide Implementation Guidelines that reflect functional capabilities Thanks! – Concern: vendor reliance on Professional Services revenue impedes progress 

 Standard metadata for instrument/device discovery and configuration 

 Pushing API Gateway capabilities to a more federate Internet of Things 

model is extremely challenging 

– Choice of silicon chips or SSD 

– Option must include attack prevention updates 

 Inter-operability Test Bed 

Copyright © 2013. All rights reserved. Copyright © 2013. All rights reserved. 
 

 

 

 

 

 

 

 

 

 

 

Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | 

Enabling Contract Manufacturing in the Cloud 

Open Cloud Architectures for Smart Manufacturing Workshop 

National Institute of Standards and Technology 

May 5, 2015 

Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | 

Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | 

Today’s distributed supply chains increase demands on B2B 

Collaboration and visibility crosses multiple supply chain tiers 

CPU 

Packaging 

Wafer 

Fabrication 

Component 

Assembly 

System 

Assembly 

Design (Schematics / BOMs / Item Specifications / ECOs ) 

Planning (Forecasts / Commitments / Production Schedules) 

Manufacturing (Work Orders / WIP / Resource Status) 

Procurement (RFQs / Quotes / Purchase Orders / Invoices / Payments) 

Logistics (Ship Notice / Shipping Instructions / Receipts / Proof of Delivery) 

Today’s distributed supply chains increase demands on B2B 

Example: Delivering Oracle SuperClusters to our customers 

System 

Assembly 

Component CPU Wafer 

Assembly Packaging Fabrication 

Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | 

• Design next-generation applications 

around B2B best practices 

• Coordinate B2B transactions with a 

common process framework 

• Streamline supplier onboarding and 

communication with B2B service 

providers 

• Offer a world-class user experience 

to external partners 

The Opportunity 

Unify Internal and Contract Manufacturing Processes in a Cloud Solution 

Oracle 

Cloud 

(Other 

B2B 

Cloud) 

(Other 

B2B 

Cloud) 

Oracle 

Supplier 

Network 

Other 

Protocols 

RosettaNet 

EDI 

Challenge 

Communications among partners are intermittent and non-standardized, 

resulting in greater supply volatility and longer manufacturing cycle times 

EDI 

RosettaNet 

OAGIS 

Flat 

files 

Proprietary 

APIs 

Database 

updates Legacy

Application 

B2B Typical

Integration Enterprise 

Flat 

files 

Proprietary 

APIs 

Database 

updates Legacy

Application 

Typical

Enterprise 

The following is intended to outline our general product direction. It is 

intended for information purposes only, and may not be incorporated 

into any contract. It is not a commitment to deliver any material, code, 

or functionality, and should not be relied upon in making purchasing 

decisions. 

The development, release, and timing of any features or functionality 

described for Oracle’s products remains at the sole discretion of 

Oracle. 

32
 

 

 

 

 

Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | 

Cloud-based Manufacturing, Collaboration and Visibility 

Oracle’s Strategy 

(Other 

B2B 

Cloud) 

(Other 

B2B 

Cloud) 

B2B Process 

Orchestration 

B2B 

Interfaces 

B2B-Enabled 

Applications 

Portal 

Messaging 

Web Services 

Oracle 

Cloud 

Supply Chain Collaboration 

Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | 

Cloud-based Manufacturing, Collaboration and Visibility 

Oracle’s Strategy 

(Other 

B2B 

Cloud) 

(Other 

B2B 

Cloud) 

B2B Process 

Orchestration 

B2B 

Interfaces 

B2B-Enabled 

Applications 

Portal 

Messaging 

Web Services 

Oracle 

Cloud 

Planning and Manufacturing Cloud 

Applications* 

out-of-the-box contract manufacturing 

*0-12 month planning cycle 

Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | 

Discrete Manufacturing Cloud 

An Integral Part of the Oracle Supply Chain Management Cloud 

Idea to 

Commercialize 

Order to 

Cash 

Plan to 

Produce 

Procure to 

Pay 

Social Network Tablet & Mobile Analytic KPIs 

& Dashboards 

Flexible Rules 

& Work Defs 

22 

Drop Shipments, Configured Products, Contract Manufacturing 

Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | 

Cloud-based Manufacturing, Collaboration and Visibility 

Oracle’s Strategy 

(Other 

B2B 

Cloud) 

(Other 

B2B 

Cloud) 

B2B Process 

Orchestration 

B2B 

Interfaces 

B2B-Enabled 

Applications 

Portal 

Messaging 

Web Services 

Oracle 

Cloud 

Supply Chain Orchestration* 

drop-ship and back-to-back 

order process coordination 

*0-12 month planning cycle 

Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | 

Order 

Management 

Orchestration 

Supply Chain 

Orchestration 

Supply Chain 

Financial 

Orchestration 

Orchestrate Multi-Company Business Processes 

 Internal Orders 

Configured Orders 

Back to Back Orders 

Outsourced Mfg Orders 

 Internal Drop Shipments 

 Tax Efficient Revenue 

Recognition 

Customer Shipments 

 External Drop Shipments 

Coordination of Goods & 

Services 

11 Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | 

Cloud-based Manufacturing, Collaboration and Visibility 

Oracle’s Strategy 

(Other 

B2B 

Cloud) 

(Other 

B2B 

Cloud) 

B2B Process 

Orchestration 

B2B 

Interfaces 

B2B-Enabled 

Applications 

Portal 

Messaging 

Web Services 

Oracle 

Cloud 

Supplier Portal, 

Collaboration Messaging Framework, 

B2B Web Services 

33
 

Oracle 

Cloud 

B2B 

(O 

B2B 

acle 

r 

ocols 

(

Cl d

O

t k

o B2

r B2

 

 

Copyright © 2015, Oracle and/or i s affilia es All righ s ese ved 

 

 

 

 

 

 

 

 

 

 

 

 

 

Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | 

Diverse 

Transport

Protocols 

Process 

Variations 

Multiple 

Messaging

Standards 

Proprietary

Metadata 

Technical Issue Standards Opportunities for Cloud Service Providers

Expectations vs. Reality of Cloud-Based B2B Solutions 

1) Messages to coordinate RosettaNet 

onboarding and profile 

management among client 

communities 

2) A common B2B messaging 

standard (OAGIS) that all B2B 

service providers can support Interoperability

Issues 3) Standard BPMN-based 

contract manufacturing Expectation Reality message choreographies 

Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | 

(Other 

Cloud) 

ther 

Cloud) 

Or 

Supplie 

Network 

Other 

EDI Prot B2B 

ud 

he 

B2B 

Clo 

rac (Ot

pplier 

Other 

to 

Oracle 

Cloud 

cle 

plie 

ocols 

Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | t t . t r r . | 

Manufacturing Use Case 

(A Need Description) 

Contract manufacturing: Cloud-based manufacturing solutions need to accommodate contract 

manufacturers and third party logistics providers as part of an end-to-end process. 

Business Challenge A significant number of high tech companies employ contract manufacturers and 3rd party 

logistics providers to produce and deliver their products, yet communications among these 

partners are intermittent and non-standardized, resulting in greater supply volatility and longer 

manufacturing cycle times. 

Business Benefit of 

addressing challenge 

Unknown, but even a small improvement in the cycle time or reliability of 3rd party processes 

would have an enormous impact. 

Open Cloud Opportunity Cloud solutions offer a way for trading partners to access a consolidated set of manufacturing 

application features on a uniform platform, eliminating many of the functional gaps and 

variations the parties faced in the past. 

Technical issues & 

Initiatives 

Issue: Independent companies still use different solutions in-house, which 1) communicate using 

a variety of methods and message standards, and 2) implement manufacturing and logistics 

processes with variations in the number and sequence of steps. 

Initiative: Companies use cloud service providers to communicate more efficiently with contract 

manufacturers via flexible, standards-based connectors. 

Standards Role Cloud-based manufacturing solution providers should agree upon: 

1) Messages for coordinating onboarding and profile management among their client 

communities 

2) A common B2B messaging standard (OAGIS) that all B2B service providers can support 

3) Standard message choreographies based upon BPMN for contract manufacturing 

Focus Point: B2B Process Choreographies 

• Potential to expand BPMN 

examples into standard template 

processes for the industry 

• The Smart Manufacturing Working 

Group may elaborate scenarios 

(buy-sell collaboration, WIP 

tracking, etc.) 

Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | 

Barriers 

• Distributed denial of service attacks can impede access to IoT devices 

• Social networks do not interoperate 

• Analyst firms do not appreciate or promote standards 

• No standards for transaction forwarding for multi-tier visibility 

• Standards funding is inadequate 

• Current environment does not favor standards mandates 

34
C o

E2OPEN CONFIDENT AL | © 2015 E2open, Inc. 1

 

 

 

 

f

E2open 

Business Network

ativ iCo b rati e ec io

I 

Uncovering Needles in the Clouds 

Orchestrating End-to-End Supply Chain & Manufacturing 

Pawan Joshi 

Vice President Strategy, E2open 

OAGi/NIST Workshop on Open Cloud Architectures for Smart Manufacturing 

Gaithersburg, MD 

May 5th, 2015 

E2OPEN CONFIDENTIAL | © 2015 E2open, Inc. 2 

Safe Harbor Statement 

The information contained in this presentation is confidential and proprietary to the Company and is being provided to 

you with the express understanding that you will not release this information, discuss the information contained herein, 

or make reproductions of or use the information contained herein for any purpose other than evaluating the Company. 

This presentation does not constitute an offer to sell or a solicitation of an offer to buy shares of the Company. 

This presentation contains “forward-looking” statements that involve risks, uncertainties and assumptions. If the risks or 

uncertainties ever materialize or the assumptions prove incorrect, the Company’s results may differ materially from 

those expressed or implied by such forward-looking statements. All statements other than statements of historical fact 

could be deemed forward-looking, including, but not limited to: any projections of financial information; any statements 

about historical results that may suggest trends for the Company’s business and results of operations; any statements 

concerning the Company’s plans, strategies or objectives; any statements of expectation or belief regarding future 

events; and any statements of assumptions underlying any of the foregoing. These statements are based on estimates 

and information available to the Company at the time of this presentation and are not guarantees of future 

performance. Actual results could differ materially from the Company’s current expectations as a result of many factors, 

including but not limited to: fluctuations in the Company’s business and results of operations; the Company’s ability to 

address market needs and sell its products and services successfully; the effects of competition; market factors; and 

general economic conditions. These forward looking statements should not be relied upon as representing our views as 

of any subsequent date and the Company neither assumes an obligation nor intends to update forward-looking 

statements to reflect events or circumstances after the date they are made. Nothing contained herein is, or should be 

relied on as, a promise or representation as to the future performance of the Company. 

Logos and trademarks herein are the property of their respective owners. 

E2OPEN CONFIDENTIAL | © 2015 E2open, Inc. 3 

Managing the Extended Business Network 

Suppliers 

iguration & 

Pack (PRD) 3PL Logistics 

• Configuration 

• Packing 

• Break Bulk 

• Cross Dock 

• Holds component 

inventory 

• Builds Base Assemblies 

• Creates Shipment 

Operator / 

Retailer 

Suppliers 

uring Customer DCs 

• Receives PO 

• Confirms PO 

• Ship components 

• Freight Forwarding 

• Customs Clearance 

• Consolidation 

Contract 

Manufacturer Distributor 

Con

Manufactur Ct DC 

PL L i i 

Configuration 

Arrival Departure 

Arrival Discharged 

Departure 

Arrival 

Direct Ship 

Purchase Order On-hand 

Ground 

Transport 

Ground / Air 

Transport 

re Arriv 

Goods 

Receipt 

Component 

Inventory 

SKU Level Sell-Out, 

Inventory info 

Forecast, 

Sales Orders 

Inventory Inventory 

FGI Inventory, WIP 

Inventory • Receives 

• Holds Inventory of New 

& Returned Goods 

• Dispatch to Retailers

Distributors 

Information Flow 

Material Flow 

In-Premise Systems 

System of Record 

All demand/supply chain transactions 

Planning systems 

Supply: OEM, CMs, 

Suppliers 

Demand: Carrier 

Replenishment 

Fax Fax 

Fax Fax Fax 

Demand you can’t predict 

with Supply you don’t control 

E2OPEN CONFIDENTIAL | © 2015 E2open, Inc. 4 

How do you manage what you can’t see? 

The Challenge 

E2OPEN CONFIDENTIAL | © 2015 E2open, Inc. 5 

Collaborative Planning & Execution 

Collabor e Execution Shortage Forecast / 

Commit Inventory PO / 

Rece pts 

ASN / 

Intransit 

CoODM/EMS ollabor Drop Ship or ative Ex Customer 

VMI 

Ex ec Sell In / cution Sell Out 

Manage by Exception 

Empowered Decision Making 

One Version of Truth 

Shared Visibility 

E2OPEN CONFIDENTIAL | © 2015 E2open, Inc. 6 

Accelerate your Design Chain 

Enable closed loop NTI & NPI process 

Product 

Requirements 

(Sales & Marketing) 

Product 

Design* 

(R&D ) 

New Manufacturing Technology 

Introduction (NTI) 

(Product Engineering) 

Manufacturing Design 

New Product Introduction (NPI) 

(Product Engineering) 

Dev Eng Qual 

Production Manufacturing 

(Operations) 

(Yield Improvement, Cost Reduction, CT 

Reduction) 

*Product Design is performed in 

3rd party tools (SPICE, CAD, ...), 

Market Introduction & 

Distribution Planning 

(Planning + Sales & Marketing) 

Manufacturing and 

Test Specification's. 

ECO’s, Hardware 

Configurations 

Manufacturing 

Results, Test Results 

Quality & Compliance – closed loop 

35
36

emb

n

Asse

al

T

Di ibution i istri bound s

Su lie

N-TierSu e N -Critic l - Fina

Improve Quality High-Definition Visibility and Traceability 

Automated Manufacturing & Compliance Validation Efficient recall, quarantine and analysis

Assembly Process Transformation Logistics Fulfillment
 

Actuals Tracking Actuals Tracking Actuals Tracking Actuals Tracking
 

CAD 

Designs 

0 

BOM, Test, 

Specification 

Process Authoring 

& 

Collaboration 

1 

Master Data 

Synchronization 

Multi Enterprise 

ECO 

M 

2 

Track Actuals 

Analytics 

3 

Validate 

Actuals 

Against 

Specifications 

4 5 

Deviation 

Alerts & 

Response 

Workflows 

DT-108.1 

DT-108.2 

SUB-X7a 

SUB-X7b 

DT 108 1 

A1 

B1 

A2 

B2 

C3 

Actual Setup 

E4 

D4 

SKU 

FG HUB 

W1 

W3 

W4 

W2 

3PL UPS 

3PL GXP 

Fulfillment History 

Order A 

Order B 

Order C 

Order D 

SUB-X7c Test Temp105C 

Assembly 

Specs 

Cloud B2B 

Network 

Manufacturing 

Actuals + Test 

Results 

Specification 

Collaborative 

Decision Workflows 

Assembly History 

Load Board WINWAY 

Socket X91-133 

Handler Seiko-Epson 

Test Program T-AOP-992 

W6 W5 

Shipment & Location Shipment & Location 

History 

Process 

Recipes 

Test Specs 

Suppliers 

3PL + Warehouses 

Internal & External Factories 

Deviation 

Detection 

Bin Lot 

Cancel FG Ship 

Consume Lot 

Consume Material 

Manufacturing History 

File History (test files...) 

Hold Lot 

Move Lot 

Receive Lot 

Reject Lot j 

Return Lot 

Rework Lot 

Status Update 

Test Results 

Forward + Backward 

Genealogy & Traceability 

Actual Change Lot Name g Create Lot Open Lot p Release Lot Scrap Lot Terminate Lot 

Close Lot Crush Lot Part NameChange Release Lot PO Ship Lot Transfer Lot 

Combine Lot FG Ship Peg Lot Reposition Lot p Split Lot p Transfer Owner 

Complete Lot p Fulfill From Qty Adjust Resource Start Stage Move g UnPeg Lot

Material Move Material Owner Material Return Resource Stop Start Lot Release for Pay 

E2OPEN CONFIDENTIAL | © 2015 E2open, Inc. 7 E2OPEN CONFIDENTIAL | © 2015 E2open, Inc. 8 

Multi-Enterprise Manufacturing Management on the Cloud Supporting Ongoing Supply Chain Evolution 

Gartner’s Five-Stage DDVN Model (2013) 

9 New Product Introduction (NPI) Stage 1 Stage 2 Stage 3 Stage 4 Stage 5 9 New Technology Introduction (NTI) React Anticipate Integrate Collaborate Orchestrate 9 Compliance and Quality Control 

9 ECO management Quality Control Profitable shared value Business unit revenue Integrated supply chain Profitable demand9 Supply chain functional creation through Yield, BIN and Cycle Time management focus, but achieving decision making, with driven fulfillment Outcome performance innovation across 9 Closed Loop Manufacturing Compliance misaligned and/or siloed early connections to through internal and improvements internal and external 9 As Built + As Tested Validation objectives product and/or sales external collaboration networks Operations 9 Multi Enterprise Collaboration 

9 Multi Site Synchronization Integrated supply chain Value-based metrics Functionally specific, Outside-in metrics across 9 Planning Model Generation Metrics Business-unit-specific metrics used to manage aligned across the competing metrics the extended value chain trade-offs ecosystem 9 Manufacturing Spec Generation Procurement Integration across the Network- and solution- Revenue focus; Scaling and cost- Functional excellence; Master BOM & extended value chain to centric decisions; Process Focus firefighting with no efficiency within each integration across core Schedule Updates make profit-driven translating innovation Project Scheduling Manufacturing centralized analysis function supply chain processes Engineering decisions into execution

Data Control Innovative technology Technologies to support Technology that enables tools to enable Disparate transactional end-to-end supply trading partner ERP & Planning Push for integration of networkwide value

Manufacturing systems of record with chain processes; connectivity and Technology systems of record; siloed creation, risk limited functional improved data supports mature functional solutions management and support rationalization and processes in the scenario analysis for 

ECAD / MCAD integration capability extended supply chain profitable trade-offs 

Functional leaders Cross-functional within business units, Head of supply chain Manufacturing & Dominance of the sales decision making across Head of supply chain regions or participates in corporate In ernal Factories ter Test Specifications Customers Organization or manufacturing groups internal supply chain; shapes corporate manufacturing; strategy as end-to-end in decision making process-focused COEs to strategy emergence of centers of process owner enable the business Suppliers & CMs Su excellence (COEs)

9 10 E2OPEN CONFIDENTIAL | © 2015 E2open, Inc. CONFID E2OPEN CONFIDENTIAL | © 2015 E2open, Inc. 

Collaborative Planning & Execution Mapping via an OAGIS canonical format 

Reference Systems Architecture Accelerates onboarding, promotes reuse & simplifies map asset maintenance 

Enterprise ERPs Transportation Order Design/PLM MESs Systems (Sys of Record) Management Fulfillment 

Real-time Data E2 Collaboration Center & Exceptions 

E2 Process Managers Analytics: Execution Dashboards| Business Intelligence 

Collaborative

Planning

& Execution

Microsoft Excel E2openE2 Cloud Connectivity Planning & Response: Supply Planning | Demand Planning | S&OP Trading Tenant Partner Process Management: Demand Mgmt | Multi-Tier Mgmt | Supply Mgmt | Manufacturing Mgmt 

OAGIS TPs Cloud Connectivity: Foundation | Connect | Community OAGIS 

Oracle 

Fusion*
 PIP RosettaNet 

Design, Mfg. Instructions, Capacity, Forecast, Commits, Orders, Responses, Shipments, Receipts, Invoices, Inventory, etc. XML TPs 

WIP, Build Plans, Allocations, Move Requests, Re-Routes, Transfer Orders, Expedites, etc. 

X12 American 

EDI TPs 

IDOCs or 

Product Maps Product Maps

Service Defs 

Product Maps Pro 

E2open

aps 

OAGIS 

Canonical 

Definitions 

SAP European EDIFACT Critical MFG EDI TPs Component N Tier- N Tier (Internal) Last/Final Last/Final Distribution Di tsr ibution N-Tier Suppliers Inbound Hubs nbound H ub Hs ub Last/Final Las /Fina istributio Cu tsomer DCs T

ast/Final Distribution Distribution Customer DC C tusom C er DCs N-Tier Suppliers Suppliers I bnound Hubs bound H ubs Last/Final Touch Hubs Touch Hubs Distribution Hubs C tusom Cer DC stomer DCs Suppliers Non-Critical Non-Critical Suppliers Non Critical Inbound Hubs Final Touch Hubs Touch Hubs Hubs Customers XML, Suppliers Non-Critical Non Critical Final Touch Hubs Hubs C ent Assembl Assembly Other Non-Critical Component As embl TPs Flat File, etc. C Assem y Component Com Component Suppliers Suppliers Suppliers

n Assembly AsMFG (External) (External) Ex Payloads C A

A p Component l Assembly ( CoS ers (E t (E xerna Suppliers Suppliers (Exter (External)nal) Suppliers Other 

Future JSON Future 11 12 E2OPEN CONFIDENTIAL | © 2015 E2open, Inc. E2OPEN CONFIDENTIAL | © 2015 E 2open, Inc. 2open I nc
o

o

p

E2OPEN CONFIDENT AL | © 2015 E2open, Inc. 15 E2open Confidential / 15

Validate Transform

Exception

Transform Validate

Transform

Collaborate

Validate

Exception

E2OPEN CONFIDENT AL | © 2015 E2open, Inc. 17

E2OPEN CONFIDENTIAL | © 2015 E2open, Inc. 13 

B2B Layer 

Customer Infrastructure 

Backend EAI Layer

Systems 

Customized 

or Native 

Formats 

Proprietary 

Connectivity 

Network 

OAGIS 

Canonical 

Definition 

Product Maps

Format C 

Format D 

Format B 

Connectivity 

Custom

Maps

C Customerspecific 

Maps 

OAGIS 

Canonical 

Definition D 

C Customerspecific 

Maps 

C 

D 

Standard 

Connectivity 

OAGIS 

Canonical 

Definition 

C 

D 

Customers are moving t Co

E2open / Oracle moving t E2o

Maps 

Maps OAGIS 

Canonical 

Definition 

Standard 

Connectivity Maps 

Trading 

Partners 

Maps 

Custom

Maps

Format A 

n Inc 

TPs are asking to use our canonical 

E2open has observed some trends with our large 

enterprise customers and trading partners 

E2OPEN CONFIDENTIAL | © 2015 E2open, Inc. 14 

B2B Layer Messaging WSDL 

Leverages Open Standards for ISV-to-Cloud 

Connectivity 

Network 

EAI and 

Mapping ISV App 

Menu of 

Protocol & 

Payload 

Options 

ISV AppISV App 

Network 

Connector Provisioning WSDL 

i

E2open Firewall 

Customer Firewall

Internet 

OAG 

BODs 

Trading Partner Directory 

Product 

Maps 

p 

Messaging

WSDL ISV 

Connector Provisioning WSDL 

OAG 

BODs 

Survey

Register

Self TestE2E Test

Promote

Live 

pp

pp 

E2open Firewall

Configure 

ISV users requests TP 

onboarding 

TP Performs their onboarding 

to the network 

Business Analyst receives updates on 

TP’s progress in their ISV App 

• Out-of-the-box combined offering from ISV 

and E2open 

• Self service tools, product maps, reuse of 

network of TPs 

• Standardized ISV Connector 

• OAGIS BODs as payload 

• OASIS WS* as protocol 

• Evaluating moving to AS4 

ISV (Cloud or On Premises ) mises 

Your name here 

I 

Issue Collaboration (not email alerting) requires an 

open standard definition of an issue and a resolution 

B2B Layer 

Customer Infrastructure 

Backend EAI Layer

Systems 

Network 

Trading 

Partner Transport Transport

Validate Transform

Exception 

Neg Ack 

Trading 

Partner Transform Validate 

Transform 

Transport 

Collaborate 

Validate 

Load 

Exception 

Neg Ack Transport Email 

Alert 

Email 

Alert 

OAGIS 

Canonical 

Definition 

OAGIS 

Canonical 

Definition 

abo 

• Work together to resolve issues 

• Structured Issue information 

• KB articles 

• History of previous resolutions 

Neg Ack 

| p, 

Problem: All ISVs and standard specs define their own exception structures making it difficult for 

companies to work together to resolve issues affecting both parties, esp. with private process issues E2OPEN CONFIDENTIAL | © 2015 E2open, Inc. 16 

Our Ask Today... Again -

• Enterprises 

• Give us feedback on fit/non-fit with your Architecture 

• Adoption hurdles 

• Applications Vendors (ISV’s), specifically MES providers 

• Join us to develop native support for open cloud interoperability 

• OAGi 

• Establish working group for the definition of new nouns/BODs 

• Revisit the manufacturing nouns and BODs for applicability in the 

smart manufacturing era 

• Consider Issue / Exception Handling Standards 

I 

Q & A 

37
 

i

 

 

 

The Digital Enterprise
	

Where strategies come to life! 

IoT Smart Manufacturing Intelligent Manufacturing Industry 4.0 Smart Factory Industrial Internet 

Mobile Cloud Social IoT Big Data & 

Analytics 

Semantic 

Technology 

Customer Centricity 

Knowledge Centricity 

Process Centricity 

Innovation Centricity 

Where strategies come to life! 

Digital Enterprise Suite 

Intelligent BPM Business process mining Agent based execution Goal oriented BPM 

Powered by the Digital Enterprise Graph 

Graph theory Semantic web science

Content and models across the Digital Enterprise are populating the 

Digital Enterprise Graph 

EA Tools BA Tools Frameworks Ontolog es 

Accelerators Accelerators Accelerators Accelerators 

Meaningful interconnection of all business artifacts from different application sources 

Smart 

Manufacturing 

http://www.techrepublic.com/article/how-iot-big-data-will-transform-manufacturing-automation/ 

Devices 

Sensors & Actuators 

Internet 

Network & Big Data 

Enterprise 

People & Processes 

The Internet of 

Things connects 

billions of devices 

such as every day 

consumer objects

and industrial 

equipment 

These networked 

devices produce 

increasing amounts 

of data over the 

internet This information is 

combined for better 

decision making

and increased 

efficiency 

IoT brings the physical world into play 

38
the pr

Business Pr

provide the 

to or

BPM acts as

f

r

er man

 

 

 

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110010100101010001001011011010100100101001001000100100010

1100101001010100010010110110101001001010010010001001000100010010101001001001000101010100101010101010010

1010101010010010101001110101010110010111110010100100110101010111010101010101010010101010101010101111001

0100111001001010101010101001010101001001001001111001010101011101001001001111101101001001010101011010010

1001010100101001001001010100101001010010010101001010101010010101010101000101010101010101010110010100101

0100010010110110101001001010010010001001000100010010101001001001000101010100101010101010010101010101001

0010101001110101010110010111110010100100110101010111010101010101010010101010101010101111001010011100101

0101010101010010101010010010010011001010010101000100101101101010010010100100100010010001000100101010010

0101010101010010101010010010010011001010010101000100101101101010010010100100100010010001000100101010010

Business Process Management 

(BPM) 

BPM acts as a central nervous system that manages

ocess from a holistic “end to end” perspective. 

ocess Management Suites (BPMS) can 

required business oriented environment 

chestrate sensor based technology, along with 

other manufacturing, logistics, procurement, order, 

and other systems 

the process 

Business Pro 

provide the 

to orchestrat 

oth uf 

The Business Process 

Model & Notation 

(BPMN) 

Already possesses a lot of the constructs 

(e.g. events, data objects, etc.) needed for

the purpose of orchestrating smart

manufacturing. 

http://jimsinur.blogspot.ca/2015/03/bpmnext-2015-state-of-union.html 

bpmNEXT 2015 

SAP & W4 demoed IoT 

aware business process. 

SAP demonstrated an oil 

pipeline problem with a 

dispatched service person 

with the proper pump 

replacement. 

W4 demonstrated a fall 

sensing capability for 

managing folks who are 

living alone without help. 

BPMN 

OAGIS 

BUSINESS 

INTERACTION 

BPMN4OAGIS

Smart Manufacturing Workgroup 

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1100101001010100010010110110101001001010010010001001000100010010101001001001000101010100101010101010010 

1010101010010010101001110101010110010111110010100100110101010111010101010101010010101010101010101111001 

0100111001001010101010101001010101001001001001111001010101011101001001001111101101001001010101011010010 

1001010100101001001001010100101001010010010101001010101010010101010101000101010101010101010110010100101 

0100010010110110101001001010010010001001000100010010101001001001000101010100101010101010010101010101001 

0010101001110101010110010111110010100100110101010111010101010101010010101010101010101111001010011100101 

0101010101010010101010010010010011001010010101000100101101101010010010100100100010010001000100101010010 

0101010101010010101010010010010011001010010101000100101101101010010010100100100010010001000100101010010 

Volume 

Velocity 

Variety 

How to integrate and translate all this data into relevant knowledge 

39
101010101001001010100111010101011001011111001010010011010101011101010101010101001010101010101010111100101001110010010101010101010010

101010010010010011110010101010111010010010011111011010010010101010110100101001010100101001001001010100101001010010010101001010101010

010101010101000101010101010101010110010100101010001001011011010100100101001001000100100010001001010100100100100010101010010101010101

101010101001001010100111010101011001011111001010010011010101011101010101010101001010101010101010111100101001110010010101010101010010

101010010010010011110010101010111010010010011111011010010010101010110100101001010100101001001001010100101001010010010101001010101010

010101010101000101010101010101010110010100101010001001011011010100100101001001000100100010001001010100100100100010101010010101010101

001010101010100100101010011101010101100101111100101001001101010101110101010101010100101010101010101011110010100111001010101010101010

010101010010010010011001010010101000100101101101010010010100100100010010001000100101010010010101010101001010101001001001001100101001

0101000100101101101010010010100100100010010001000100101010010

101010101001001010100111010101011001011111001010010011010101011101010101010101001010101010101010111100101001110010010101010101010010 

101010010010010011110010101010111010010010011111011010010010101010110100101001010100101001001001010100101001010010010101001010101010 

010101010101000101010101010101010110010100101010001001011011010100100101001001000100100010001001010100100100100010101010010101010101 

10101010100100101010011101010101100101111100101001001101010101110101010101010100101010101010101011110010100111001001010101010 1010010 

101010010010010011110010101010111010010010011111011010010010101010110100101001010100101001001001010100101001010010010101001010101010 

010101010101000101010101010101010110010100101010001001011011010100100101001001000100100010001001010100100100100010101010010101010101 

001010101010100100101010011101010101100101111100101001001101010101110101010101010100101010101010101011110010100111001010101010101010 

010101010010010010011001010010101000100101101101010010010100100100010010001000100101010010010101010101001010101001001001001100101001 

0101000100101101101010010010100100100010010001000100101010010

Heterogeneity Quality of Information Data Congestion 

Challenges 

010100010010110110101001001010010010001001000100
 

01010001001011011010
 

Smart Execution 

• We need semantics and analytics to 

ensure that only relevant data are 

collected from devices to generate 

business events 

• We need robustness of connectivity 

to ensure relevant business events are

provided 

• We need Ontologies of IoT sensor 

and actuator data so we can reason 

over the provided events 

40
Smart Manufacturing 

Leadership Coalition 

www.smartmanufacturingcoalition.org 

 

 

 

 

 

-

 

 

 

 

NIST Workshop on Open Cloud Architectures 

for Smart Manufacturing 

May 5, 2015 

Jim Davis UCLA & SMLC 

Building Infrastructure 

Powering Smart Decisions 

SMLC Partnerships What is Smart Manufacturing

 Internal & External Value Chain 

Networked-Based Manufacturing 

Smart Manufacturing 

Data 

When it is needed 

Where it is needed 

In the Form it is needed 

Throughout the 

Manufacturing Ecosystem 

American Council for an Energy 

Efficient Economy (ACEEE) 

AMP Socal 

Alcoa 

American Institute of Chemical 

Engineers (AIChE) 

American Society of Quality 

ARC 

Association of State Energy 

Research and Technology Transfer 

Institutions (ASERTTI) 

Corning 

Department of Energy (DOE) 

Emerson 

Electric Power Research Institute 

General Dynamics 

General Electric 

General Mills 

General Motors 

Manufacturing Enterprise 

Solutions Association (MESA) 

MT Connect 

National Association of State 

Energy Officials (NASEO) 

North Carolina State University 

Nimbis Services 

NIST 

National Science Foundation (NSF) 

OSISoft 

Owens Corning 

Pacific Northwest National Laboratory 

Pfizer, Inc. 

Praxair 

Purdue University 

Rensselaer Polytechnic Institute 

Rockwell Automation 

Rutgers 

Savigent Software 

Schneider Electric 

Society of Manufacturing Engineers 

Southwest Research Institute - SWRI 

Sustainable Solutions 

Texas A&M Engineering Experiment Station 

Tulane – PolyRMC 

United Technologies Research Center (UTRC) 

University of California, Berkeley 

University of California, Irvine 

University of California, Los Angeles 

UCLA IS Associates 

University of Texas - Austin 

West Virginia University 

EDI transaction 

Supply Chain Distribution Center 

Customer 

Business 

Systems, ERP 

Smart Grid 

Smart Small Medium and 

Large Manufacturers 

• Configurable high fidelity/statistical modeling and analytics 

• Dynamic plant configuration and readiness 

• Dynamic product component/material configuration 

• Faster changeovers & more variable order sizes 

• Dynamic inventory minimization & management 

lot & quality 

certifications 

Tracking & 

traceability 

More customer freedom 

To customize 

Minimum just in case inventory & 

corrective actions thru entire system 

Chain of custody 

Order adjustment 

Reduce premium 

shipments 

Use Cases Mike Yost – MESA International 

©SMLC, Inc. All Rights Reserved. 

Smart Manufacturing: Multi-Layered 

Seams, Time, Data & Action 

Machines – People Materials Dynamic Manufacturing Ecosystem 

Design

Data 

In 

Service 

Macro Layer 

Meso Layer 

1000s Micro Layer 

control loops 

Time - minutes 

100s 

control loops 

Time -hours 

10s 

control loops 

Time – days 

Focus: 10x Multiple 

Pass Variability 

Reduction; Supply 

Chain Information 

Business Systems 

1 

c 

T 

Control & Automation 

Focus: 100x Event 

Variability/Tradeoff 

Adjustment; Dynamic 

Performance Mgmt.; 

Integrated Metrics 

Focus: Insertion, 

Qualification, ICME, High 

Fidelity Dynamic 

Operations 

©SMLC, Inc. All Rights Reserved. 

Smart Manufacturing based on 

ISA 95 

41

Product 

Manufacturing 

Materials & 

Process Tech Prototype Qualification 
 

 

 

Data

 

 

 

 

 

Technical and Business Drivers for 

Shared Infrastructure 

Smart Manufacturing & Vendor 

Products 

SM 

Achievable Meaningful Use Goals and A Set of Issues Beyond Individual Company 

Magnitude of Impact • ROI constrained or prohibitive
 

•	 Demand-driven efficient use of resources and supplies in - Requires broader infrastructure investment to scale 

more highly optimized plants and supply - Incremental investment difficult 

– 25% reduction in safety incidents - Requires IT investment with 70% of cost non-value 

– 25% improvement in energy efficiency - Depends on other companies - supply chain 

- Need 80% reduction in cost of implementing 

modeling and simulation – 10% improvement in overall operating efficiency 

– 40% reduction in cycle times - 10x reduction in the cost of sensors and sensor – 40% reduction in water usage	 infrastructure 

• Product safety	 • ROI opportunity comprehensive 

– Multiple systems – Product tracking and traceability throughout the supply – Integrated global performance metrics •	 Sustainable production processes for current and future – Aggregating data critical industries • Installed base of serviceable manufacturing facilities – 10x improvement in time to market in target industries – $60 B in IT investment – 25% reduction in consumer packaging – Retrofit 

• Maintain and grow existing U.S. industrial base • Risk – Environment for broad innovation – Major change & New business model – 25% revenue in adjacent industries – Uncertain about technology, security & IP – 25% revenue in new products and services 

– 2x current SME䇻s addressing total market • Organization 

– IT capability lacking or IT not talking to operations – More highly skilled sustainable jobs created – Workforce skills 

– Collaboration ©SMLC, Inc. All Rights Reserved. 

Smart Manufacturing Platform 

Bridging Seams Extending the Real Time 

Infrastructure across Value Chains 

Applications 

Context 

In-production 

performance 

Smart grid 

Interoperability 

Smart machine 

operations 

Sustainability 

& Safety 

Open Platform & Marketplace 

For Industrial Data, Modeling,

 & Metric Applications 

• For contributors and users 

•Accessible Affordable, Flexible to 

SMMs 

SM Value Proposition 

Event Data Real-Time Data 

Data 

Mapping 

Value chain 

Interoperability 

©SMLC, Inc. All Rights Reserved. 

Secure I, P and SaaS 

Secure Data Highways 

Data & Device Integration & 

Orchestration 

Smart Factory Manufacturing 

Smart Enterprise 

Manufacturing 

Manufacturing 

Health & Sustainability 

Collective 

Innovation & 

Practice 

Converting Data 

to Information 

Converting Information 

to Knowledge 

Converting Knowledge to 

Wisdom 

Data Valuation 

Collective vs. 

Proprietary 

Practice Valuation 

Collective vs. Proprietary 

The Business 

of Data, Quality, 

Personalization, 

Performance, 

Sustainability & Time 

g 

IoT 

Big Data 

Smart 

Collective Wisdom 

The Business of 

Open Architecture 

Market, Data Valuation 

& Innovation 

©SMLC, Inc. All Rights Reserved. 

Production Calibration & Sensor 

Models Maintenance Data 

42
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44
 

 

 

Cloud computing 

Facility Design Example: Facility Design 

Executing Simulation Experiments 

in the Cloud 

C. Dennis Pegden, CEO 

Simio LLC 

www.simio.com | Copyright 2014 Simio LLC | All rights reserved. 1 

Cloud Manufacturing 

X Cloud-based manufacturing paradigm based on Internet 

of Things (IoT) and virtualized/service oriented 

technologies. 

X Encompasses the life cycle of a product – design, 

simulation, production, test, maintenance. 

X Cloud-based simulation for both facility design and 

production planning/scheduling. 

www.simio.com | Copyright 2014 Simio LLC | All rights reserved. 3 

X Allow 3D animated simulation models to be built and run 

in the cloud for improving system design. 

 Model building 

 Data integration 

 Animation 

 Experimentation 

www.simio.com | Copyright 2014 Simio LLC | All rights reserved. 5 

X Avoid infrastructure costs. 

X Focus on value added activities. 

X Shorten development time. 

X Less maintenance, easier to 

manage. 

X Scale resources to changing 

demand. 

www.simio.com | Copyright 2014 Simio LLC | All rights reserved. 

Cloud Computing Drivers 

1. Mobile and shared information. 

2. Scalable demand. 

3. Scalable (parallel) computation. 

Most applications leverage 1 and 2. 

Simulation applications leverage all three. 

www.simio.com | Copyright 2014 Simio LLC | All rights reserved. 

www.simio.com | Copyright 2014 Simio LLC | All rights reserved. 

45

2 

4 

6 
 

 

 

Experimentation Cloud Challenges/Opportunities 

X Models are used to compare alternative designs, or 

optimize design parameters. 

X Randomness requires that each scenario is replicated. 

X During experimentation animation is not required. 

X Multiple processes allow scenarios and replications to be 

run in parallel. 

www.simio.com | Copyright 2014 Simio LLC | All rights reserved. 

Working within the existing limitations Planning and Scheduling 

X Models are built using desktop software. 

X Data is first integrated into the model – the project 

(model + data) is then uploaded to the cloud. 

X Experimentation can leverage the full scalable processing 

power of the cloud (e.g. 25 replications of 10 scenarios 

simultaneously executed). 

www.simio.com | Copyright 2014 Simio LLC | All rights reserved. 

www.simio.com | Copyright 2014 Simio LLC | All rights reserved. 11 

X Cloud-based 3D animation environments don’t exist. 

X Model data is dispersed and not easily accessed. 

X Experiments can be executed in parallel. 

Data interfacing is the highest 

priority issue limiting the 

vision. 

7 www.simio.com | Copyright 2014 Simio LLC | All rights reserved. 8 

X Allow simulation-based scheduling systems to be 

executed in the cloud, and the results deployed across 

the enterprise. 

 Deterministic model used to generate schedule. 

 Interface to ERP/MES data. 

 Evaluate alternative scenarios (expediting jobs, overtime, etc.). 

 Analyze delivery risks by replicating the schedule with 

uncertainty and unplanned events. 

 Publish the selected plan to mobile devices for execution. 

9 www.simio.com | Copyright 2014 Simio LLC | All rights reserved. 

Example: Planning and Scheduling Risk Analysis 

X Deterministic plans assume away uncertainty/unplanned 

events – they provide optimistic results. 

X By replicating the plan with variation/uncertainty added 

into the model we can estimate schedule risk. 

X Multiple processes allow replications for risk analysis to be 

executed in parallel. 

46

www.simio.com | Copyright 2014 Simio LLC | All rights reserved. 

10 

12 
 

 

Cloud Challenges/Opportunities Working within the existing limitations 

X Cloud-based modeling environments don’t exist.	 X Models are built using desktop software. 

X Model data is dispersed and not easily accessed.	 X Data is first integrated with model – the project (model + 

comparisons of alternative schedules and risk analysis. X Experimentation can leverage the full scalable processing 

power of the cloud (e.g. 25 replications of 10 scenarios 

simultaneously executed). 

X Experiments can be executed in parallel, providing quick 

Data interfacing is the highest 

priority issue limiting the 

vision.	 

data) is then uploaded to the cloud. 

X Risk analysis can leverage the full scalable processing 

power of the cloud. 

www.simio.com | Copyright 2014 Simio LLC | All rights reserved.	 13 www.simio.com | Copyright 2014 Simio LLC | All rights reserved. 14 

Top Priority is Data Integration 

X Cloud manufacturing solutions will initially be hybrid 

environments (e.g. ERP cloud, MES on premise). 

X Solutions must interface to dispersed data – some on 

premise – some in the cloud. 

X Data integration between cloud and on premise 

components (e.g. ERP, MES, IoT, custom data sources) 

needs to be simple and seamless. 

www.simio.com | Copyright 2014 Simio LLC | All rights reserved.	 15 

47
 

Advancing. Manufacturing. IT. 

 

– 

 

Advancing. Manufacturing. IT. 

 

 

 

 

Advancing. Manufacturing. IT. 

 

 

 

 - - 

 

 

 

 

 

 

 

 

 

 

Advancing. Manufacturing. IT. 

OAGi/NIST Workshop on 

Open Cloud for Smart 

Manufacturing 

Jon Siudut 

Advancing. Manufacturing. IT. 

Introduction to MESA International 

Speaking with the 

Voice of Industry’s 

Practitioners 

Peer 

-toPeer 

Global 

Education 

Program 

Points 

-ofView 

MESA International: 

Building Bridges-of-Understanding 

from the Plant to the Enterprise 

Advancing Manufac 

S 

V 

P 

MES Content Providers MES End Users 

Manufacturing Enterprise 

Solution Content Providers 

MES ISVs Need means to interoperate amongst cloud 

platforms 

Business Challenge Integration with disparate cloud solution providers 

Interface with other MES providers 

Business benefit Ease of systems interface/integration . Reduction by 1X ( 

~20%) integration cost 

Open Cloud Opportunity Data Services including Storage, format translation , 

repository ( large data) 

Analysis services include asynchronous statistical correlation 

Document authoring and File Viewers ( ex. CAD formats) 

Technical Issues & Initiatives No current method to help automate integration 

Proprietary efforts could serve as a model 

Standards Role Lead interface specification methods 

Derive tool to aid automation 

Manufacturing Enterprise End Users MES End Users – Need means to integrate with 

manufacturing and business systems 

Business Challenge Integration through manufacturing supply chain 

Integration within own IT business systems 

Business benefit of addressing challenge Ease of systems interface/integration . 

Reduction by 1X ( ~20%) integration cost 

Open Cloud Opportunity Define supply chain SCOR like interfaces 

amongst systems 

Technical Issues & Initiatives Supply Chain Data Exchanges for controlled 

communications tied to contracts between the 

supplier tiers 

Identity Verification Services to ensure 

person/machine authorization 

Standards Role Lead interface specification methods 

Derive tools to aid automation 

Manufacturing Use 

Case (A Need 

Description) 

Based On MESA White Paper “Leveraging Cloud Services for Smart Manufacturing Systems”: 

Need effective ways to create information threads for complete business processes across 

departments that do not depend on manual translation of information. 

This includes any use case that involves manufacturing operations that require deeper visibility 

into the supply chain for availability or compliance and tracking & multi component, multi location 

assembly processes. 

Business Challenge • We currently run many interdepartmental business process via paper, email, and with many 

manual interpretations and translations of data inputs to outputs along the way. These manual 

interdepartmental business processes are error prone and cannot scale to handle higher 

volume of transactions 

Business Benefit of •	 New functionality and integration options enabled by cloud-enabled platforms, exchanges and 

addressing challenge; marketplaces. 

estimated •	 The availability of quality cloud component services that are easy to assemble into a custom 

quantification of application will change the future of the Information Technology (IT) department. 

benefit 

Open Cloud • Leverage cloud computing-enabled component-as-a-service (CaaS) model. 

Opportunity •	 CaaS that are easy to assemble into a custom application 

•	 Enterprise departments assembling CaaS in IT-provided UI, workflow, computation, integration 

frameworks. 

•	 IT departments providing guidelines and frameworks for assembling applications from CaaS, 

SaaS, ... 

•	 Interoperable app-based, customized, (reconfigurable) mfg systems 

Technical Issues & Solutions enabling layered, distributed architecture: 

Initiatives •	 enterprise-level bpm & work-flow orchestration 

•	 integration mechanism to exchange information across layers from equipment to plant to 

supply chain 

•	 multiple data layers with different persistency requirements 

•	 role-specific, enterprise specific customizations of apps including mfg. supervision, control, 

operation, quality inspection 

Standards Role •	 Identify the places along the digital thread where we need standards for exchange of 

48
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i l l l l

 

l l l l

Agenda 

1. Background Mfg in the Age of IoT and Cloud:
 

Opportunity and Challenge 2. IBM Approach
 

© 2015 IBM Corporation © 2015 IBM Corporation 

3. Role of Industry Standards 

Mfg in the Age of IoT and C oud: Opportunity and Chal enge 2 

Dave Noller 

IBM Industrial Sector Strategy & Integration 

nollerd@us.ibm.com 

“Mfg 2.0” defined the need for “MES by Composition” (System of Insights from 

Systems of Record) and paved the way for Industry 4.0 

© 2015 IBM Corporation 

Source: Manufacturing 2.0: Service and Collaboration-Based Architectures for Manufacturing Right First 

Time—on demand - AMR Research, 2007 

3 Mfg n the Age of IoT and C oud: Opportunity and Chal enge 

“Industrie 4.0” describes a Reference Architecture for connecting IoT to IoS 

The introduction of IoT into the manufacturing environment is ushering in a 

fourth Industrial Revolution 

Industry 4.0 Characteristics: 

© 2015 IBM Corporation 

z Dynamic business and engineering processes enabling last-minute changes to production 

z Personalized, local production and mass customization 

z Creating value opportunities through services 

6 Mfg in the Age of IoT and C oud: Opportunity and Chal enge 

Agenda 

1. Background 

2. IBM Approach 

© 2015 IBM Corporation 

Source: Recommendations for implementing the strategic initiative INDUSTRIE 4.0 

Final report of the Industrie 4.0 Working Group, April, 2013 

Mfg in the Age of IoT and C oud: Opportunity and Chal enge 8 © 2015 IBM Corporation 

3. Role of Industry Standards 

Mfg in the Age of IoT and C oud: Opportunity and Chal enge 10 

49
010011

-

10 00110101

l l

 

l l

 

 

 

 

 

 

 

 

 i 

 

i i 

 

 

 

l l

Industry-specific Solutions

Design & 

Engineer Operate Manage

Analyze and Optimize

 

l l

 

 

 

l l l l

Control and secure the 

data streaming from 

your instrumented 

devices 

Analyze data to extract 

insight, applying them 

where they matter 

most 

Drive product and service innovation with 

foresight 

1 2 

Deliver operational improvement and 

efficiency from insight 

3 

101011101110 10110 0 1010011010 0100110101 0100110101001 01001101010 010011010 01001101010 010011010 01001101010 01001101010 001101010010101 0 

IBM’s Approach: build better solutions with open technologies (aka 

“Open Plus”) The first step is IoT applied to manufacturing devices 

Driving innovation of tomorrow from insights today API economy 

Intelligent 

Internet of 

Things 

Insight 

Interconnected Innovation 

Cloud operating https://get.docker.io my_docker_container: type: DockerInc::Docker::Conta

NOVA	 

with 

environment	 

HEAT 

VMInstance 

OS 

inerdocker_endpoint: { get_attr: [my_instance, first_address] } Instrumented Improvement image: cirros 

Compute node 

Software defined 

environments 

Baremetal 

OS 

Baremetal 

OS 

Mfg in the Age of IoT and C oud: Opportunity and Chal enge © 2015 IBM Corporation 12 © 2015 IBM Corporation 

Operate, Analyze, Innovate, Transform 

Mfg in the Age of IoT and C oud: Opportunity and Chal enge 13 

IoT value creation will be led by Makers and Operators IBM Internet of Things Foundation: what is it? 

I operate and use a collection of 

things to provide a product or service. 

I care about integrating a collection of 

things and making sure they work 

cohesively together to deliver customer 

satisfaction 

I have to work with things built by 

others, understand how they fit together, 

and the data they generate 

I make invent, design products and 

services. 

I care about innovating things that 

matter and delivering seamless user 

experience 

I can choose the things I build, the 

technologies I adopt and the depth of my 

analytics 

Design products with customer relevant 

features quickly and effectively 

Create services that generate new value, 

drive loyalty and increase market share. 

Use analytics to improve product, service 

and customer interaction in real-time 

Improve efficiency and streamline operation 

to reduce cost 

Integrate diverse applications and business 

data across heterogeneous environments 

Derive new value and insight from 

connections and system interactions 

Innovate, prototype and develop faster w th 

IBM Continuous Engineering 

Compose IoT appl cat ons with IBM Bluemix 

and scale to production with IBM Cloud 

Generate insights from data in motion with 

IBM Stream Computing and explore big data 

with IBM Big Data Platform 

Transform into a predictive maintenance 

enterprise with IBM Asset Management and 

IBM Predictive Analytics solutions 

Manage your complex business infrastructure 

in real-time with IBM Business Process 

Management 

Convert operational and connectivity data 

into actionable insights with IBM Business 

Analytics 

Industry specific Solutions 

Design & 

Engineer Operate Manage 

Analyze and Optimize 

Products, 

Assets, 

Infrastructure 

Protocols & Gateways 

Secure 

Connect, Collect and Store 

Connect, Collect and Store 

information from a range of 

things with range of volume, 

variety and velocity 

A new offering within IBM’s Bluemix PaaS offering that 

allows Internet-connected devices to be integrated directly 

into Bluemix solutions 

Mfg in the Age of IoT and C oud: Opportunity and Chal enge © 2015 IBM Corporation 14 Mfg in the Age of IoT and C oud: Opportunity and Chal enge © 2015 IBM Corporation 15 

IoT as a Composable Business Multiple cloud models exist, but “Hybrid” seems to be best suited to 

Manufacturing 

IoT end-to-end solutions 

Connected appliance solutions, Smarter home solutions...	 

Firms will need to build across traditional cloud boundaries to maximize investment 

Hybrid Cloud	 

API economy 

IoT Foundation 

Secure Device Registration, Scalable Device Connectivity, Historian, Visual wiring Cloud operating 

environment 

Private Cloud	 Dedicated off- Shared offpremise cloud premise cloud 

Software defined Devices & Gateways	 environments 

IoT-related Bluemix services 

Rules, Push, Geo location, Analytics, Asset management, Predictive Maintenance... 

Mfg in the Age of IoT and C oud: Opportunity and Chal enge © 2015 IBM Corporation 16 © 2015 IBM Corporation 19 19 Mfg in the Age of IoT and C oud: Opportunity and Chal enge 

50
t t t

 

l l l l

i l l

 

Plant Floor Integration

 

 – 

 

 / i

l l

i l l

 

 

 

 

 

l l

Gold Sponsors 

success... 

IBM has 19 core contributors 

y 

ss... 

19 

IBMers working on OpenStack – from formation of the +400 Foundation to Code Quality & New Function

IBMers are active developers in 

OpenStack projects 

2 

OpenStack Participant Growth 

IBM is #2 in contributions to 

OpenStack integrated projects 

+100 

Platinum Sponsors 

Bluemix leverages CloudFoundry, Docker and OpenStack as key 

elements 

Continuing our history of embracing and extending Open Source 

Building on open from the ground up enables IBM to maximize client investment 

© 2015 IBM Corporation 

IaaS 

PaaS 

SaaS 

OAuth 

Mfg in the Age of IoT and C oud: Opportunity and Chal enge Mfg in the Age of IoT and C oud: Opportunity and Chal enge © 2015 IBM Corporation 22 

Private Cloud Hybrid Cloud Off-premises cloud 

20 

Smarter Manufacturing – IBM view Control 

Center 

ERP,
 

EAM, 

SCM, Enterprise Systems 

Direct & Indirect 

Material Management 

SRM 

Logistics & Distribution Inventory Management 

Quality & Traceability 

Pl t Fl I t

Asset Monitoring & 

Maintenance ti

Part Pick / Kitting / 

Labeling MES / ALC 

In

Procurement 

MRO 

Mgmt. 

BOM Management Performance Analysis & 

Reporting Financial Control 

SCM 

Create Sequenced 

Production Schedule 

Demand / Supply Planning & 

Scheduling Labor Management 

Management Production Planning 

Finished Goods 

Management EAM 

Plant Floor Systems 

Line Sequencing / 

Re-sequencing 

Broadcast 

Buffer Control 

(PBS, WBS) 

WIP Tracking 

Order Status / 

Management Data Collection 

Pl Flow Control Reporting and Analysis t Fl 

SCM 

Final Finish 

Error Proofing Material Management 

Track & Trace Quality Management

Plant Floor Integration Plant Floor Integration Integration Bus Manufacturing Pack/Gateways 

Integrated 

Operations 

MDM Information Model Data Warehouse 

Business Rules Modeling / Simulation Predictive Analytics Optimization & Decision Mgmt 

GIS Services 

Streaming Data 

p Integration Bus File Transfer Adapters

Business 

Process 

Mgmt 

Role Based 

Visualization Workflow 

Alarms Alerts Realtime V sualization 

Reports 

Remote 

Monitoring PLM 

Mobile Advanced Access Analytics
 

Optimization
 

Data Services
 

Data Acquisition
 

Maintenance 

MES, 

CNC,
 

PLC
 Equipment 

Operator 

Data Acquisition 

Printers 

Devices Robots 

PLCs / 

Controllers 

Material Handling 

Barcode 

Scanner 

RF Antenna 

& Tags 

Production 

Engineer 

© 2015 IBM Corporation 25 Mfg n the Age of IoT and C oud: Opportunity and Chal enge Mfg in the Age of IoT and C oud: Opportunity and Chal enge © 2015 IBM Corporation 26 

Agenda IBM participates in, and supports, Open Standards efforts –

for example, IBM is working to accelerate OpenStack 

success 

1. Background 

Because an open interoperable Cloud is critical 2. IBM Approach Mar 

2013 

Jan 859 2015 Contributors 

3148

Exponential growth 

8,500 Members 

Contributors 

18152 Members 

for flexible cloud deployment and customer 

3. Role of Industry Standards 

Mfg n the Age of IoT and C oud: Opportunity and Chal enge © 2015 IBM Corporation 27 Mfg in the Age of IoT and C oud: Opportunity and Chal enge © 2015 IBM Corporation 28 

51
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l l

“ 

 

 

 

52

15926 

Vertical and Horizontal integration standards (content exchange and IT standards, e.g. MQTT - open connectivity for Mobile, M2M and IoT 

information/analytics models) – too many options! IT Systems High volumes of data/events 

F O U N D A T I O N 

Lossy or 

Inter-Company Operations Constraine 

d Network 

Commands or Data Visualisation 

Monitoring & 

Analytics 

Server 

OAGIS 

SPEC Level 4 

2000/ 

STEP 

Business 

Logistics ISA-95 / 

B2MML MIMOSA A lightweight publish/subscribe protocol with predictable bi-directional message delivery Maintenance 

In the era of a Smarter Planet, open source 

and standards are essential 

2013 – MQTT Technical 

Committee formed

Engineering

OPC UA SPEC

2000 PLM Level 3 

Services Manufacturing 

Operations PLCS/ PLCS/ AP 239 AP 239 Level 2	 ISA-88 / ISO Cimetrics, Cisco, Eclipse, dc- SCADA BatchML ISO 15926	 Square, Eurotech, IBM, INETCO 2011 - Eclipse PAHO MQTT 

open source project Landis & Gyr, LSI, Kaazing, OPC DA/HDA M2Mi, Red Hat, Solace, Telit Level 0/1 

Process Control Comms, Software AG, TIBCO, 

ISA 95 

hierarchy
 

29 Mfg in the Age of IoT and C oud: Opportunity and Chal enge © 2015 IBM Corporation 

How can industry standards efforts help? 

F O U N D A T I O N 

Do canonical object models for interoperability (e.g. ISA-95, OAGIS, OMG PLM 

services) really matter? After all this time, to what extent are they really being adopted? 

If not, why not? These standards do not seem to come up much in “real life” projects. 

Assuming the answer is “yes”: 

Consider new forms that are more web and programming tool friendly, e.g. 

JSON vs XML 

Continue to work on rationalizing overlap so that choices are more clear 

Today’s interoperability standards are “heavy”, consider developing lightweight 

versions aimed at IoT integration (e.g. MQTT) 

31 Mfg in the Age of IoT and C oud: Opportunity and Chal enge © 2015 IBM Corporation 

2004 MQTT.org open community WSO2 

1999 Invented by Dr. Andy Stanford-Clark (IBM), 

Arlen Nipper (now Cirrus Link Solutions) Evolution of an open technology 

30 Mfg in the Age of IoT and C oud: Opportunity and Chal enge © 2015 IBM Corporation 

Manufacturing Use 

Case (A Need 

Description) 

Business Challenge 

Business Benefit of 

addressing 

challenge; estimated 

quantification of 

benefit 

Open Cloud 

Opportunity 

Technical Issues & 

Initiatives 

Standards Role 

IoT and Cloud Support through migration”, not “Big Bang”: Adoption of IoT and Cloud 

needs to consider existing “brownfield” environments in a secure way. 

•	 Manufacturers wanting to adopt new, innovative technologies such as IoT and Cloud (or 

the vision of Industry 4.0) need a way to migrate gradually with support of existing 

systems 

•	 Manufacturers want flexible systems that can react to change and minimize vendor lockin. 

•	 Evolving existing manufacturing systems today (through upgrades) is very costly and 

time consuming. New technologies can, potentially, lower the time and cost of bring up 

new systems or changing existing systems. 

•	 Cloud based systems based on open standards and technology have the potential to 

address both of the business challenges mentioned above. For manufacturing, however, 

security concerns and the need for “brown field”, or “hybrid” systems must be 

addressed. 

•	 Interoperability standards are still not widely adopted, so “mapping” still has to occur 

somewhere and is difficult. 

•	 Interoperability standards today are “heavy”, and do not lend themselves to easy usage 

for “agile” creation of applications (e.g. for mobile) in the “integration cloud”. 

•	 MES tends to be trying to act as the vertical integration layer today, but is not well suited 

to “out of the box” integration needed to support “Industry 4.0” type initiatives. Would 

be easier if it could be treated as a set of capabilities easily integrated through APIs 

(services). 

•	 Take a hard look at what is inhibiting adoption today (for customers and vendors) 

• Try to simplify the picture vendors and customers who would like to adopt the © 2015 IBM Corporation 

interoperability standards 

© 2013 IBM Corporation 
i 

- 

- 

l 

i

l 

“ ” i

i 

i i 

i

–

 

 

 

 

 

 

 

 

 

 

 

 

 

 

I

 

 

1 

There is broad alignment for several 

problems to solve Top priority for DMDII 

Secondary priority for DMDII 

Integration of the 

digital thread 

Leadership/ 

organization 

capabilities 

Theme Sub-theme 

Top ranked problem to solve for: 

Big data 

Standard data format and machine 

communicat on 

Cyber Security 

Make design link 

Articu ation of business case for 

dig tal 

Optimization across va ue chain 

Real time supplier vis bility 

Commercialization of lab 

technolog es 

Workforce train ng/availabil ty 

Barriers to user adoption 

Enabl ng of mass-customization 

Tracking product performance in 

the field 

Other 

Industry Academia Government 

© The Digital Manufacturing and Design Innovation Institute not for distribution 2 

Summary of value drivers from digital across groups 

Industry 

• Growth vs. cost story: 

• A new era post-commoditization 

with suppliers 

• Need to rebuild bridges 

• Drive supplier collaboration 

• Move from cost-focus to: 

• Growth/NPI focus 

• To get to market faster 

• Connected customer; real-time 

data/new business model; selling 

services (miles vs. tire) 

• Time to market; data re-use; quality 

• Ability to change/agility 

• Reduce non-value added 

change/rework 

• Execute value-add change 

• Allow experimentation 

• Proactive 

measurement/adaptability 

• Enable other institutions to build on 

innovations and start to believe that 

bold change is possible 

• Drive economic growth and capability 

building for US manufacturing base 

• Improve the brand value of products 

made in US 

SOURCE: DMDII workshop, May 2014 

Academia 

• Feedback loops back to design 

• Make-design link 

• Data from product performance 

feeds new product innovation 

• Supplier collaboration 

• “Real time” access to production 

information 

• Ability to adapt to system perturbations 

• Improved macro forecasting 

• Downtime reduction between 

product families 

• Respond to changes in customer 

preferences 

• Reduced design/manufacturing 

constraints 

• Improved customer service/brand 

loyalty 

• Address potential field failures 

proactively 

• Reduced time to market 

• Rapid prototyping 

• Reduced qualification time (virtual 

testing) 

Government

• Focus on design for: 

• Manufacturing 

• Maintainability (long lifecycle) 

• Affordability through lifecycle (inc. 

up-front price and maintenance) 

• Commercialization of technology 

through collaboration (both 

competitive and pre-competitive) 

• 3D design capability reducing cost in 

the design-make link and improved 

quality 

• Big data definition/standards, new 

interoperable platforms, analytics, and 

best practice standards), to drive 

efficiency and response time (months 

Æ days) 

• Improving national security through 

cyber security standards in 

manufacturing 

• Shorten supply chain to reduce costs 

(e.g., 3D print parts on the battlefield) 

• Reduce design/purchasing risk by 

testing technology earlier and cheaper 

• Improve US manufacturing 

competitiveness to create jobs and 

economic development 

3 

Key barriers to capturing value from digital were cited 

across the groups BARRIERS TO VALUE CAPTURE 

Strategy & 

innovation 

barriers 

Execution barriers 

Talent & 

organization 

barriers 

Technology 

barriers 

• Poor access to technology/best practices 

• Lack of a collaborative environment/culture across the value chain 

• Require a paradigm shift in manufacturing (‘material flow’ to ‘info flow’ systems) 

• Limited financing/bus. cases for digital manufacturing and design technology 

• Lack of IT infrastructure (bandwidth, storage, processing), especially for SMBs 

• Managing obsolescence of legacy systems (hardware and software) 

• Current manufacturing industry software model 

• Lack of 3D design and manufacturing capability 

• Software/modeling constraints – need more data availability, open IP 

• Skills (software/digital) are needed for manufacturing workforce and leadership 

• Lack of cross-functional ways of working (silo structures) 

• Organization design lacking in manufacturing IT leadership 

• Change aversion related to new tools 

Detailed description of each barrier (common themes across groups) 

Data barriers 

• Ensuring data is captured, standardized, with embedded manufacturing logic 

• Cyber security needs to be put in place for manufacturing 

• Lack of usable information available to product designers 

SOURCE: DMDII workshop, May 2014 4 

Summary of barriers to value capture from digital across 

groups 

Industry 

• Trust needed across supply base 

• Skills (software/digital) 

• Not found in manufacturing 

leaders 

• Lack of cross-functional ways of 

working 

• Poor access to technology/best 

practices 

• Change aversion related to adopting 

new tools 

• Lack of financing for innovation (for 

SMEs) 

• IT infrastructure 

• Bandwidth 

• Storage 

• Processing power 

• ORG design (e.g., IT) 

• Manufacturing industry software 

model 

• Needs to change (still using 20-

year old model) 

• Proprietary technology prevents 

innovation 

• Need more of an ‘app’ based 

environment 

SOURCE: DMDII workshop, May 2014 

Academia 

• “Over the wall mentality” 

• Lack of a collaborative culture/ 

environment across value chain 

• Lack of usable information available 

to product designers 

• Software/modeling constraints 

• Greater data availability would help 

refine models; IP/infrastructure 

constraints 

• Require a paradigm shift in 

manufacturing 

• Moving from a “material flow” 

systems design to an “information 

flow” design 

• Skills (software/analytical) 

• Education an issue 

• Requirement standardization 

• Intelligent models that integrate 

wide variety of requirements (e.g. 

UL, company-specific) 

• Data collection and extraction 

• Ensuring that the right data is 

captured 

• Data standardization 

• Embedding tolerance information 

• Managing obsolescence of legacy 

systems (hardware and software) 

Government 

• Key data not captured if not in DOD 

contract (e.g., 3D data not required, 

only 2D) 

• Ownership of data is often proprietary 

and held by supplier/not shared with 

DOD 

• Tech data is often separate from tech 

package 

• Lack of 3D design and manufacturing 

capability within the DOD supply base 

• Conversion of legacy systems/data 

(TDP) slows down progress 

• Organizational silos are still major 

barriers 

• Small/medium businesses lack 

infrastructure to adapt to these new 

technologies 

• Workforce gaps exist relative to new 

tech (but government is uniquely 

positioned to help) 

• Business case demonstrations are 

needed to overcome issues with 

leadership will to act 

• Cyber security issues in manufacturing 

must be tackled 

5 

Industry, academia, and government groups also 

offered several examples of different problems that 

DMDII could help solve EXAMPLES: Problems that DMDII could help solve 

8 Standard data formats and machine communications

2 Manufacturing software business model

5 Reducing cost of qualification

6 Improved access/quality/use of data in product dev.

7 Big data management for manufacturing

3 Optimizing across the value chain

4 Workforce training and availability

1 Articulation of business case for digital

SOURCE: DMDII workshop, May 2014 

Capability 

Dimensions 

Talent and 

Organization 

Strategy and 

Innovation 

Data 

Technology 

Execution 

6 

Organizations believe that digital design and 

manufacturing is an important driver for growth, cost, 

and quality 

Most critical 

Important 

Very important 

Little/no importance 

From a business 

metric perspective 

(e.g., cost, 

revenue), how 

important a driver 

is digital design 

and 

manufacturing in 

each of these 

areas? 

43 

42 

35 

31 

32 

32 

32 

27 

26 

29 

27 

20 

11 

10 

-15 

-16 

-15 

-24 

-29 

-27 

-26 

-4 

-4 

-7 

-5 

-6 

-10 

-13 

Manufacturing and 

supply chain cost 

Revenue expansion of 

existing business 

Operations agility 

Time to market for new 

products 

Product quality 

Service levels (on time 

delivery; data accuracy) 

Product innovation 

© The Digital Manufacturing and Design Innovation Institute 

53
– –

–

 

–

 

–

l 

 

 

 

–

7 

SOURCE: DMDI Survey, Q11, Q13 

Despite the recognition of importance for digital design 

and manufacturing, most participants believe their 

organizations lack capability 

14% 

81% 

Organizations 

with "high" 

digital 

capability 

today 

Participants indicating 

digital is a top 10 driver 

of future 

competitiveness 

• There is 

widespread 

recognition of the 

importance of 

digital design and 

manufacturing to 

future company 

success 

• Most participants 

believe this 

organizations lack 

mature digital 

capabilities 

© The Digital Manufacturing and Design Innovation Institute not for distribution 8 

Organizations realize that technology 

creates no value – on its own 

Capability 

Dimensions 

Skills and structure to develop solution 

and extract value 

Talent and 

Organization 

Clear strategy, plan to drive 

competitive advantage 

Strategy and 

Innovation 

Information assets and associated 

management Data 

Devices, apps and platforms to deliver 

Digital initiatives Technology 

Cascade strategy into a well-resourced 

plan, with aligned metrics & 

accountability 

Execution 

© The Digital Manufacturing and Design Innovation Institute not for distribution 

9 

Majority of senior leaders agree that digital is a 

priority, but few have a clear bold vision and 

strategy 

34 

29 

53 

Our digital efforts are 

innovative/bold 

We have a strategy for how 

digital will enable competition 

Digital is a senior 

leadership priority 

Percent of respondents who “agreed” or “strongly agreed” 

People, culture 

and leadership 

elements related 

to 

implementation 

of digital design 

and 

manufacturing 

© The Digital Manufacturing and Design Innovation Institute not for distribution 10 

Translating strategy to clear action is a 

clear gap in a majority of organizations 

Percent of respondents who “agreed” or “strongly agreed” 

People, culture 

and leadership 

elements related 

to 

implementation 

of digital design 

and 

manufacturing

16 

24 

20 

We have well defined metrics/KPIs 

There is clear communication from 

leadership on digital strategy 

Digital strategy is translated 

to specific initiatives 

© The Digital Manufacturing and Design Innovation Institute not for distribution 

11 

Several capabilities identified as 

key for AME, IM, and AA 

Top themes on capabilities for DMDII to help solve 

AME IM AA 

 Collaborative design 

 Design for producability – 

‘DFX’ 

 Modeling and simulation 

 Production flow and 

intelligent networks 

 Advanced analytics to drive 

diagnostics and prognostics 

for asset productivity 

oManufacturing equipment 

oProduct lifecycle 

• Capture data 

• Analytics to use data for 

prognosis/diagnosis 

 Design optimization and 

concept selection 

oVirtual prototyping (multiphysics) 

oDFM / should cost 

oReliability modeling 

oModeling & simulation as a 

learning tool 

 Intelligent network design 

 Develop common data 

standards including 

communication/interchange 

logic 

 Create a supporting open 

platform and architecture 

that can span the full 

value/supply chain using the 

common data formats 

 Launch virtual and physical 

test-beds to commercialize 

feedback/control technology 

 Create an analytics library for 

wider use 

© The Digital Manufacturing and Design Innovation Institute not for distribution 12 

Key barriers to capturing value from digital 

were cited across the groups BARRIERS TO VALUE CAPTURE 

Strategy & 

innovation barriers 

Execution barriers 

Ta ent & 

organization barriers 

Technology barriers 

• Poor access to technology/best practices 

• Lack of a collaborative environment/culture across the value chain 

• Require a paradigm shift in manufacturing (‘material flow’ to ‘info flow’ systems) 

• Limited financing/bus. cases for digital manufacturing and design technology 

• Lack of IT infrastructure (bandwidth, storage, processing), especially for SMBs 

• Managing obsolescence of legacy systems (hardware and software) 

• Current manufacturing industry software model 

• Lack of 3D design and manufacturing capability 

• Software/modeling constraints – need more data availability, open IP 

• Skills (software/digital) are needed for manufacturing workforce and leadership 

• Lack of cross-functional ways of working (silo structures) 

• Organization design lacking in manufacturing IT leadership 

• Change aversion related to new tools 

Detailed description of each barrier (common themes across groups) 

Data barriers 

• Ensuring data is captured, standardized, with embedded manufacturing logic 

• Cyber security needs to be put in place for manufacturing 

• Lack of usable information available to product designers 

SOURCE: DMDII workshop, May 2014 

© The Digital Manufacturing and Design Innovation Institute not for distribution 

54
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13 

Issues and Technology Gaps from DoD 

perspective 

• Data interoperability 

o Can we focus on processes and be tool/software agnostic? 

o Day to day operational and legacy data interoperability issues result in 

significantly increased costs, schedule delays, and decreased quality for 

weapons systems. 

o The interoperability gap between OEMs and their suppliers negatively 

impacts nearly every DoD weapons system  Increases acquisition and sustainment (life cycle) costs 

 Significant delays in acquisition and sustainment cycle times 

 Frequent first-article quality issues 

o Inability of most small to medium suppliers to seamlessly exchange product 

data with larger DoD primes. 

• Cultural barrier of “not invented here” and “my product is unique.” 

• Lack of Infrastructure 

• Manufacturing processes not included in the weapon system TDP 

o TDPs missing for legacy platform data 

14 

Issues and Technology Gaps from DoD 

perspective 

• Integration of Product Data with Metadata and trusting that it will be available 

throughout the product’s lifecycle. 

• Contractual issues: IP/Data Rights, product structure annotation & definitions. 

• Engineering analysis and design intent of individual parts is not available for 

sustainment procurement. 

• Engineering and manufacturing product information is re-created repeatedly across a 

products lifecycle. 

• Cyber security for data systems. 

• Getting the Product Data sync with as Designed, as Produced, and as Maintained 

Configurations to support the platform thru the total lifecycle, so that it is 

reuse/repurposed instead of recreated. 

• Long manufacturing lead times, high cost of manufacturing and inspection 

• Getting data to the right user at the right time in the right format so that parts can be 

delivered to the warfighter at the right place, right price, and on time. 

15

Future Manufacturing 

• Digital link between design and fabrication 

• Connected machines, factories, and supply chains 

• Transparency and visibility into supplier factories 

• Data aggregation, analysis, and action across the 

product lifecycle 

• Leverage the power of data analytics and 

networks to do more with existing resources 

Manufacturing Use 

Case (A Need 

Description) 

Greg Harris: 

Protected and connected digital enterprise, secure digital thread, enabling mostly secure 

environment, including handheld devices that we use for multiple activities (similar to financial 

industry) 

Business Challenge • Lack of means enabling access and utilization of the disconnected systems in use today 

• Lack of digital manufacturing business solutions available 

• Lack of platforms on which to place and use the digital manufacturing business solutions 

• Cyber security risks (both perceived and real) that keep manufacturers from trusting systems 

Business Benefit of •	 New businesses will be created, including those enabling manufacturing data analysis 

addressing challenge; •	 Reestablishment of the US industrial base as the world leader in efficient and agile 

estimated manufacturing 

quantification of •	 Restoration of a robust middle class America 

benefit •	 Large savings from the efficient transfer of data between disparate systems 

Open Cloud 

Opportunity 

•	 Open cloud allows disruption to occur in manufacturing industry with "apps." In the future, 

manufacturing software solutions will be small, inexpensive, and user-friendly. 

•	 Interoperability issues can be addressed broadly instead of a point solution basis 

•	 Access to tools and capabilities that the Small and Medium Enterprises do not have access to 

today 

•	 Opportunity for Supply Chain growth through collaboration tools 

•	 Enabling plug-and-play digital functionality across the entire digital thread 

Technical Issues & • Enterprise model for mfg. software is proprietary and not interoperable 

Initiatives •	 Methods ensuring that credentialed identification is accessible, transferrable and retrievable 

•	 From a government perspective there is a serious infrastructure gap, particularly with the 

Organic Industrial Base 

•	 Processes and procedures to reuse data in multiple points throughout the life cycle of a system 

Standards Role •	 Standards are necessary to bring order to the Wild, Wild West of Digital Manufacturing and 

Design that we are experiencing today 

•	 There are gaps and overlaps in standards today that must be bridged and harmonized to bring 

about interoperability and ease of function for efficient data exchange 

55
 

 

 

 

 

 

 

 

 

 

 

 

 

ni.com 1

Industrial Internet of Things: 

The Opportunities and Challenges for Engineers and Scientists 

Shelley Gretlein 

National Instruments 

ni.com 2

The idea of a smarter world where systems with sensors and local processing are connected to share information is taking hold in 

every single industry. These systems will be connected on a global scale with users and each other to help users make more 

informed decisions. Many labels have been given to this overarching idea, but the most ubiquitous is the Internet of Things (IoT). The 

IoT includes everything from smart homes and mobile fitness devices, to the Industrial Internet of Things (IIoT) with smart cities, 

smart factories, and the smart grid. 

The IIoT can be characterized as a vast number of connected industrial systems that are communicating and coordinating their data 

analytics and actions to improve industrial performance and benefit society as a whole. By making machines smarter through local 

processing and communications, the IIoT could solve problems in ways that were previously inconceivable. But, as the saying goes, 

"If it was easy, everyone would be doing it." As innovation grows, so does the complexity, which makes the IIoT a challenge that no 

company can meet on its own. 

This challenge becomes even more daunting and complex when comparing the requirements of the industrial Internet to those of the 

consumer Internet. Both involve connecting devices and systems all across the globe, but the IIoT adds stricter requirements to its 

local networks for latency, determinism, and bandwidth. When dealing with precision machines that can fail if timing is off by a 

millisecond, adhering to strict requirements becomes pivotal to the health and safety of the machine operators, the machines, and the 

business. 

ni.com 3

• As the IIoT comes to fruition, a big change is in store for historical industrial systems, because systems management and 

security will be paramount. As massive networks of systems come online, these systems need to communicate with each other

and with the enterprise, often over vast distances. Both the systems and the communications need to be secure, or millions of

dollars worth of assets are put at risk. One example of the need for security is on the smart grid, which is on the leading edge of the IIoT. As information on the grid becomes more accessible, so does the damage a security breach can inflict. 

• 

In addition to being secure, IIoT systems need to be continually modified and maintained to meet ever-changing functionality

and system-maintenance requirements. As more capabilities are added, new systems have to be tacked on to meet those 

needs. Soon, a tangled web of interconnected components starts to form. The new system must integrate not only with the 

original system but also all of the other systems. Imagine modifying and updating thousands or millions of systems located all

over the world, some in remote locations. 

• 

Developing and deploying the systems that will make up the IIoT represents a massive investment for decades to come. The 

only way to meet the needs of today and tomorrow is not by predicting the future, but by deploying a network of systems flexible enough to evolve and adapt. The way forward involves a platform-based approach; a single flexible hardware architecture 

deployed across many applications removes a substantial amount of hardware complexity and makes each new problem

primarily a software challenge. By investing in a cohesive hardware/software platform, all efforts surrounding security and 

updates can focus on a better solution that's deployable across myriad applications. 

• 

The ongoing design of the IIoT represents a massive business and technology opportunity for all of us. Engineers and scientists 

are already implementing systems on the leading edge of the IIoT, but many things still need to be defined and much work

needs to be done. 

ni.com 5

The Escalating Complexity of Systems 

ni.com 6

Airbus 

reduced development time by 10X 

with NI solutions. 

ni.com 7

National Grid 

gained visibility and access to critical turbine 

performance data for 11GW of wind power 

with NI solutions. 

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ti )

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i i

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I lli

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ni.com 8

Moore’s Law Metcalfe’s Law Battery Life Wireless Sensors 

The Internet of Things 

ni.com 9

SMART 

Factory 

Grid 

Machine 

City 

Car 

SMART 

Phone 

Wearable 

TV 

Appliances 

Home 

Connectivity 

Data Analytics 

INDUSTRIAL 

Internet of Things 

CONSUMER 

Internet of Things 

Based on Moor Insights & Strategy's report "Segmenting the Internet of Things (IoT)" 

ni.com 10

End-To-End Solution Architecture for IoT Decision Mak ng and Control 

Data Aggregat on and Management The Edge 

IT Infrastructure 

(Big Data Analytics, Mining) 

Edge IT 

(Local, Remote, Cloud) Corporate/Federated IT 

Data Acquisit on, Control, 

and Analysis Systems Sensors/Actuators 

Analysis and Visualization Software 

ni.com 11

Big Data Characterized 

Social data sources 

 Social data, behaviors, sentiments 

 Tweets, posts, comments 

Engineering/scientific data sources 

 Physical world: analog phenomenon 

 DAQ, A/D 

Industry/IT sources 

 Enterprise apps: ERM, CRM, HR 

 IT data: events, logs, inventories 

 Process and control 

ni.com 12

Sensors 

i i 

Monitoring Systems 

30,000 sensors 10,000 

machines 2,000+ devices ~60 plant servers 1 Federated M&D center 

Balance of P ant 

Assets 

The Edge 

Turbines (Cri cal 

Example Big Analog DataTM End-to-End Solution 

Fleetwide Online Asset Condition Monitoring 

Systems 

and Data Management 

Access Pon 

Bus ness Network 

IT Infrastructure 

Wireless 

Oi Sensor 

V brat on Sensor 

V brat on Sensor 

Leak Detec on Sensor 

Pressure Sensor 

Temperature Sensor 

nte gent DAQ 

nte gent DAQ 

57
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ni.com 14

Measurements & Petabytes 

Energy Efficiency 

Smart grid, power monitoring 

Environmental Monitoring 

CO2 emission, climate change 

Structural Health Monitoring 

Bridge infrastructure, building monitoring 

Industrial Measurements 

Machine monitoring, hazardous measurements 

ni.com ni.com 15

Acquire Analyze Present 

ni.com 16

Acquire Analyze Present 

ni.com 17

Acquired Data 

• Temp 

• Wind speed 

• Vibration 

Web Service Clients 

• LabVIEW 

• Web UI Builder 

• Other apps

Web Service 

APIs 

Web Service 

APIs A 

rvice Web

NI Technical 

Data Cloud 

ni.com 18

Web Service 

Application 

LabVIEW Web UI Builder 

ni.com 19

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20

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i

i

i 

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Local LabVIEW FPGA Compile 

ni.com 21

Compile Workers 

Compile Farm 

Server 

Development 

Computers 

LabVIEW FPGA Compile Cloud Service (Beta) 

ni.com 23

Acquire Analyze Present 

ni.com 24

End-To-End Solution Architecture for IoT Decision Mak ng and Control 

Data Aggregat on and Management The Edge 

IT Infrastructure 

(Big Data Analytics, Mining) 

Edge IT 

(Local, Remote, Cloud) Corporate/Federated IT 

Data Acquisit on, Control, 

and Analysis Systems Sensors/Actuators 

Analysis and Visualization Software 

59
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Open Cloud Architectures for 

Smart Manufacturing Workshop 

Chris Monchinski 

Co Chair ISA95 

Managing Director ISA S&P Board 

Automated Control Concepts 

www.automated-control.com 

Enabling Integration of 

Manufacturing Operations to 

the Cloud 

Manufacturing 

Use Case 

Integration between Cloud Based Level 4 Systems and Real Time Factory Floor 

Automation made possible with ISA 95 

Cloud-to-On Premise Integration of Manufacturing Enterprise and Real Time Factory 

Floor 

Business 

Challenge 

• Manufacturers are adopting business level systems that are increasingly moving 

toward cloud based architectures (SaaS, software rentals, third party contracts 

and off site systems) 

• Manufacturing systems and IT assets remain fixed assets with real time 

requirements (0 latency) and high availability. 

• Integrating these new, hybrid architectures is increasingly challenging. 

Security, protection of intellectual property, customer data and system 

robustness are all of paramount importance. 

• Evolving Adoption of “Two Tiered” systems requires both cloud based and 

locally hosted solutions increasing integration demands. 

Business Benefit 

of addressing 

challenge; 

estimated 

quantification of 

benefit 

• Reducing the risk and cost of integration between cloud based assets and fixed 

assets will enable rapid adoption of cloud based solutions 

• Reduced asset costs, increased flexibility, increased reliability and robust 

security are all benefits of a well integrated cloud based architecture. 

• Integration when applying standards 

• Prior: projects took 1-2 years & <50% successful 

• After: projects take 2-4 months & >90% successful 

Open Cloud 

Opportunity 

• Standards such as ISA 95 Control to Enterprise Integration standard are a 

facilitator technology that will allow manufacturers to “plug in” to business 

based systems hosted in cloud computing architectures 

• Flexible Integration and collaboration reduces risk and increases speed of 

implementation and adoption rates of these new technologies. 

• ISA 95 Control to Enterprise Integration standard provides models and 

definitions of application boundaries based in function, allowing architects to 

define hybrid systems using cloud and fixed asset systems, as necessary. 

Manufacturing 

Use Case 

Integration between Cloud Based Level 4 Systems and Real Time Factory Floor 

Automation made possible with ISA 95 

Cloud-to-On Premise Integration of Manufacturing Enterprise and Real Time Factory 

Floor 

Technical Issues & 

Initiatives 

• Collaboration with several industry-specific standard groups has facilitated 

adoption of ISA 95 in a wide variety of industries. This needs to continue. 

• National and International Standards groups need to continue to collaborate 

and present a unified voice to the manufacture and software/service vendors. 

• The ability to leverage the standards and models to demonstrate the ability to 

integrate systems and then to turn that collective know-how into toolkits (in 

the form of code, guidance, industry specific technical reports, etc.) will 

greatly reduce the cost and risk of integration and promote best practices. 

• Adoption by vendors of integration standards such as ISA 95 Part 6 and 7 will 

reduce risks associated with interoperability among enterprise service vendors. 

These tools will be “key” to facilitating flexible integration strategies to enable 

manufacturing assets to leverage cloud technology. 

• Promotion and adoption of practices outlined in the ISA 99 / 62443 standard 

will facilitate “integrated” security and best practices for robust 

integration 

Standards Role • The ISA 95 / 62264 Control to Enterprise Integration standard helps system 

architects define logical boundaries between systems, allowing manufacturing 

systems to integrate to cloud based systems, exchanging data reliability and 

securely. 

• B2MML (Business to Manufacturing Markup Language is an open source initiative 

maintained by MESA and is an instantiation of the ISA 95 standard in XML and 

WSDL. 

• Facilitate Best Practices and increase manufacturing “Nimbleness” 

Cloud Benefits 

• Success with Cloud Technologies in Manufacturing 

o Adoption of Cloud Technologies 

 Enterprise Software 

 Sales Force Automation 

 Customer Relationship Management 

o Benefits 

 Reduced Cost of Ownership 

 Pay for the services you use 

 Scalability 

• SaaS, PaaS, IaaS Implementations 

o Logistics 

 Collaboration between suppliers and distributors 

o Sales support functions 

 Company “know-how” and collaboration with customers 

o Product development management 

 Rapid Implementation 

Gap in Integration 

Operations Management Production 

Management 

transactions 

p g 

Production Management 

Real-Time 

Control & Events Continuous Batch Logic 

Sensors, Actuators & Logical Devices 

Business Planning & Supply Chain 

Mgmt. Logistics HR 

ERP Product Life Cycle CRM

60

Challenge in Manufacturing 

• Manufacturing Operations 

o Systems comprised of “fixed” resources 

 Equipment, Materials, People, Energy 

o Need for near Real-Time response 

o Need for High Reliability 

o Protecting Intellectual Property 

o Security Concerns 

o Reduce Integration Costs 

o Increase Integration Flexibility 
 

 

Challenge in Manufacturing Benefits to Enabling Integration 

• Evolving Adoption of “Two Tiered” Systems 

o Use SaaS, PaaS or IaaS for Outsourced ERP, 

Logistics 

o Keep Critical Assets and Infrastructure In-house 

o Allows Customization for Each Location 

• Integration Risks 

o Require High Levels of Integration 

o But Must Be Flexible, Reliable 

o Security 

• Standards Applied to Integration 

o Reduce Risk 

o Prior 

 projects took 1-2 years 

 < 50% successful 

o After 

 projects take 2-4 months 

 >90% successful 

o Increase Adoption of Cloud Technology 

Integration – Current Practice 

• Message based protocols have become the standard 

model for cloud based enterprise integration 

• Enterprise Service Buses (ESB) have become the 

standard model for exchanging integration messages 

• XML has become the standard model for data 

representation within messages 

• SOAP and REST have become the standard interfaces to 

ESBs 

• Web services have become the standard for SOAP 

implementations 

9 

Enterprise 

Service Bus 

SOAP XML Application 

A 

SOAP XML Application 

C 

XML Application 

B REST 

XML Application 

D 

Web 

Service 

Message 

Standards at Each Step 

• National/International, de facto, industry 

standards 

• ISA 95, B2MML, SOAP, ISA 99, WS_* 

10 

ISA 95.06, ISA 99, 

ESB, RSS, FTP, Named Pipes, 

Message Queue System, ... ISA 95.05, 

(IEC 62264-5), 

B2MML, 

OAGIS, ... 

ISA 95.02, B2MML, 

MIMOSA, OAGIS, 

OMAC, ... 

Ethernet, 

TCP/IP, HTTP, ... 

802.xx, ... 

ISA 95.07 SOAP, REST, ... 

Integration with Standards 

A Step by Step Approach 

Convert Local 

format to 

Global format 

Convert Local 

names to 

Global names 

Send 

information to 

exchange 

service 

Exchange 

services 

Collect Local 

information 

Convert Global 

format to Local 

format 

Convert Global 

names to 

Local names 

Receive 

information 

from exchange 

service 

Save & 

Process Local 

information 

Local 

Information 

Local 

Information 

2 

3 

4 

1 

5 6 

7 

8 

9 

ISA 95 Part 2,4,5 

Specifications 

ISA 94 Part 2,4,5 

Specifications 

ISA 95 Part 6 

Specification 

ISA 95 Part 6 

Specification 

ISA 95 Part 7 

Specification 

ISA 95 Part 7 

Specification 

Advantages of the ISA 95 Standard 

• Consistent Terminology 

o Foundation for supplier and end user 

communications 

• Consistent Information Models 

o Model Recognizing Separate, Distinct Processes 

in Business and Manufacturing 

o Foundation for consistency between suppliers 

• Consistent Operations Models 

o Foundation for clarifying product functionality –

“how” information is to be used 

61

• Technology Independent 
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ISA 95 Scope 

• Enterprise to Control Systems Integration 

o	 A Multi-Part Standard 

o	 Define a model of the enterprise, including manufacturing

control functions and business functions, and its information 

exchange. "Enterprise to control system integration” 

• Includes batch, continuous and discrete 

• The interface between: 

ISA95 Levels
 

Level 4 

Business Planning 

& Logistics Plant Production Scheduling, 

Operational Management, etc. 

Level 3 

Manufacturing 

4 - Establishing the basic plant schedule -

production, material use, delivery, and 

shipping. Determining inventory levels. 

Time Frame 

Months, weeks, days, shifts 

3 - Work flow / recipe control, stepping the 

process through states to produce the desired 

end products. Maintaining records and 

Time

Operations Management optimizing the production process. 

Time Frame Dispatching Production, Detailed Production o Business planning & logistics (“level 4”) 

o	 Manufacturing operations & control (“level 3”) 

• B2MML (Business to Manufacturing Markup Language) 

Scheduling, Reliability Assurance, ... 

Shifts, hours, minutes, seconds 

Level 2 o Defines an implementation of the ISA models in an XML format 2 - Monitoring, supervisory control and

automated control of the production process 

Sensing the production process, manipulating 

the production process 

o	 Defines a standard language for representing exchanged information Batch Continuous Discrete Level 1 Control Control Control 1 -

Level 0 0 - The actual production process 

Where the Standards Fit 

ISA95 ISA95 

Parts 1, 2 ENTERPRISE

The ISA95 Standard 

• Part 1: Models and Terminology 

• Part 2: Data Structures and Attributes 

• Part 3: Activity Models of Manufacturing

Operations Management 

• Part 4: Object Models and Attributes of 

Manufacturing Operations

Management 

• Part 5: Business to Manufacturing

Transactions 

• Part 6: Messaging Service Model 

• Part 7: Alias Service Model 

ISA106

ISA88 

AREA

CONTINUOUS
 

PRODUCTION
 

UNIT
 

SITE 

AREA 

BATCH
 

PROCESS
 

CELL
 

Parts 3, 4 

ISA95 

Parts 5,6,7 

AREA

DISCRETE
 

PRODUCTION
 

LINE
 

ISA 95 Initiatives 

• Better Collaboration Between Standards 

o Avoiding Standards “Soup” 

o Guidance for the Market 

o International Standards Harmonization 

• Adoption Across Industry Types 

o Implementation Guidance for Discrete, 

Batch, and Continuous Industries 

• Collaboration of Vendors 

o Bridging the gap between Automation and 

IT service vendors 

ISA 95 Initiatives 

• Better Tools and Toolkits 

o Automate Integration 

o Reduction in Code Maintenance 

o Reduction in Time to Deployment 

o Capture Best Practices Practices 

o Working Reference Models ence Models 

• Adoption 

o Engaging with 

o ESB Vendors 

o Implementing ISA 95 

• Security 

o Leveraging ISA 99 / 62443 Guidance Best Practices 

o Adopting Security “integrated” into the solution 
)

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IPC 

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SS 

S 

(Premise) 

Central 

Mgmt. 

A tuators 

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IoT Smart Manufacturing Areas of Interest 

Enterprise Service Bus 

Manufacturing ‘Real-Time’ Service Bus DB Services 

Devices (1..n) 

DB Services 

L3 Apps 

L3 Adapters 

L4 Apps 

Gateway L4 Adapters

Gateway 

Device: a node, an embedded system, a smart sensor device 

Service 

Oriented 

Architecture 

Firewall 

Gateway 

1 ISA 84 L1 Apps

0 

2 

3 

4 

ISA 95 

Cloud 

Services 

Cloud 

Services 

Edge Workload Dedicated Consolidation Platforms Platforms 

Gateway 

Platforms 

L1, L2 Apps L2 Apps L2 Apps

Cloud 

Services 

ISA 95 

ISA 99 

ISA 88 

#1 Simplify Bus Communications from 

Device to Cloud 

#2 Enable new E2E Integrated Hardware 

Root of Trust Security Models 

#3 Convergence of OT/IT Manufacturing 

Architectures 

#4 Enable Software Defined and Scalable 

Analytics at the Edge and Cloud 

E2E IoT Security is a Pre-Cursor and Basic Capability that Drives all other Success! 

4-30-2015 Intel Corporation 

IoT Smart Manufacturing Positons Summary 

Smart Manufacturing 

Architectures, 

Implementations and the 

Internet of Things 

Kirk Smith 

Solutions Architect 

Internet of Things Group 

Industrial and Energy Solutions Division 

Intel Corporation 

Use Case Challenge Benefit Opportunity Issues Standards 

Simplify Bus 

Communications 

Device access, 

state visibility 

State 

awareness of 

embedded 

industrial 

devices. 

Define open data 

access models for 

embedded devices 

Ease\cost of 

accessing Proprietary 

networks. 

Protocol abstraction or 

translation for IoT use 

cases. 

E2E Security Models HRT linkage High protection 

level for critical 

infrastructure 

Lowers barriers for 

enabling industrial 

use cases 

Expertise, legacy 

components, 

engineering expense 

Connect one-way to 

hardware roots of trust 

at both ends of the wire. 

Convergence of OT/IT 

Manufacturing 

Architectures 

Network 

fragmentation; 

Manageability at 

scale; Access to RT 

data. 

Simplicity, 

scalability 

Lower maintenance 

and integration 

costs 

Long timelines likely 

for system and 

network migration 

Simplify network 

traversal across MSB and 

ESB network 

architectures. Improve 

co-existence of Near RT 

and RT network 

processing 

Enable Software 

Defined Scalable 

Analytics 

Access at the 

edge; skilled 

resource pool 

Higher re-use 

of assets; more 

scalable 

manageability; 

Drive secure 

virtualization 

deeper into 

embedded domains 

Remote connectivity, 

data normalization, 

model, 

interoperability, 

maintenance models 

Improve interoperability 

and scalable access to 

analytics at the edge and 

cloud for E2E systems. 

4-30-2015 Intel Corporation 3 

#1 Simplify Bus Communications E2E #2 Integrated Hardware Root of Trust Security 

FACTORY FLOOR 

re 

i ensors 

I

ems 

ems 

Consolidation 

ca a erver 

Datacenter 

era

HRM 

CM 

DM 

Of Apps 

c

a

ta

ay

Customers 

Suppliers 

Partners 

C ients 

Hist RDBMS HDFS 

e 

DDS 

a ne 

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Sensors

i 

rive Control 

ndustria ERP 

CRM 

Corp. Office/HQ

E rpris Dat 

R mot ERP, CRM, HRM...) ME 

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Mach 

Visio 

nsors 

screet 

Control 

Temperatur

Position Sensors 

HMI 

Syste 

Consolid 

Motor 

PLC 

Systems 

Consolidation 

Operator er

Control 

(Pr e m ise )

Actuato Actuators

Valves 

PLC

IPC

ms 

dation 

LOCAL CO N T 

R O 

Sc daa Serve 

RDat OaO Aggreg ation

S PC/SVC 

Se 

D 

Driv 

IoT 

Gateway	 

Core 

Atom 

Galileo 

Core i5 

Legacy IA 

Core i7 Xeon 

Quark 

Open Middleware 

Sensor Dev ce Too Equ pment 

The Silicon Advantage 1. Secure: 

•	 Intel Hardware Root-of-Trust + 

Middleware + Intel Security + Wind 

River Bundled Solutions 

2.	 Connected: An Open Middleware 

Component Model Supports 

• Device to Cloud Integration 

•	 Middleware to ESB Adaptation 

Integration 

• High QoS Options 

• Migration Path 

3. Managed: 

•	 Intel Security, Wind River, MW 

Solution Integration 

Abstract complexity of 

heterogeneous devices with: 

Manufacturing Service Bus 

High Bandwidth 

Real-time 

Standards-based 

Secure and Trusted Data: 

Unified Security architecture 

“Plug and Play” 

Add devices and connect E2E 

Easily Collect/Transfer Data 

4-30-2015 Intel Corporation 5 4-30-2015 4-30-2015 Intel Corporation 6 

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#3 OT/IT Convergence Trends #4 Scalable Software Defined Analytics

One configurable QoS defines the service bus communication 

technology across the factory and supply chain with overall lower TCO. 

‘Near Real-Time’ 

‘Real Time’ 

Service Bus 

Work oad Consol da on Pla o ms 

Edge Pla o ms 

Embedded 

Virtualizatio n 

DB Services 

Devices (1..n) 

L3 

Apps

L3 QoS 

L4 Apps

L4 QoS 

Gateway 

Device: a node, an embedded system, a smart sensor device 

Service 

Oriented 

Architecture 

0 

1 

2 

3 

4 

ISA 95 

Cloud 

Services 

Dedicated 

Pla o ms 

Operating

System 

Connect, Collect, Analyze, 

Transform 

L2 Apps L2 Apps L2 Apps 

L1 Apps 

Cloud 

Services 

L3 Topic 1 

L3 Topic 4 

L3 Topic 2 

L3 Topic 5 

L3 Topic 3 

Data-Centric 

L4 Topic 1 

L4 Topic 4 

L4 Topic 2 

L4 Topic 5 

L4 Topic 3 

ESB ? Increase Access to 

Highly Actionable Data 

A Single View of the Truth: 

Right Information at Right Time to Right 

Person = Better Decisions! 

Dynamic Real-Time 

Optimization Supply Chain Frequencies approaching 

Factory Frequencies 

Cost Reductions Increased production performance, 

aligned operational / business goals 

Lower maintenance, workforce 

management 

Increased Access to Real-Time Data Translates to $$$ 

4-30-2015 4-30-2015 Intel Corporation 7 4-30-2015 Intel Corporation 

Reference and Related Collateral: 

Intel IoT Insights Day: 

http://newsroom.intel.com/docs/DOC-6097 

4-30-2015 Intel Corporation 9 10 

Legal Disclaimer 

Copyright ©2015. 

Intel and the Intel logo are trademarks of Inte Corporation in the U.S. and/or other countries. 

*Other names and brands may be claimed as the property of others. 

Intel Corporation 

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