The Role of Standards in Product Lifecycle 

Management Support 

Eswaran Subrahmanian 

Sudarsan Rachuri 

Abdelaziz Bouras 

Steven J. Fenves 

Sebti Foufou 

Ram D. Sriram

NISTIR 7289
NISTIR 7289

The Role of Standards in Product Lifecycle 

Management Support 

Eswaran Subrahmanian 

Sudarsan Rachuri 

Abdelaziz Bouras 

Steven J. Fenves 

Sebti Foufou 

Ram D. Sriram 

January 2006

 U.S. DEPARTMENT OF COMMERCE 

 Carlos M. Gutierrez, Secretary 

 TECHNOLOGY ADMINISTRATION 

 Michelle O'Neill, Acting Under Secretary of Commerce for Technology 

 NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY

 William Jeffrey, Director 
 

The Role of Standards in Product Lifecycle Management Support 

Eswaran Subrahmanian1, Sudarsan Rachuri2, Abdelaziz Bouras3, Steven J. Fenves4, 

Sebti Foufou5

, Ram D. Sriram6

Manufacturing Systems Integration Division, 

National Institute of Standards and Technology 

Gaithersburg, MD 20899-8263 

 

Abstract 

A major challenge of any product engineering project is to support the creation, 

exchange, management and archival of information about product, process, people and 

services across the networked and extended enterprise covering the entire product 

lifecycle spectrum. An information support system for Product Lifecycle Management 

(PLM) requires a move from product data exchange to product information and 

knowledge exchange across different disciplines and domains. PLM support systems will 

need to have both syntactic and semantic interoperability of computer systems and people 

through well defined standards. 

We begin this paper with a model of communication between two agents and then extend 

this model to describe the information flows in PLM so as to serve as the basis for 

understanding the role of standards for PLM support systems. Support of PLM requires a 

set of complementary and interoperable standards that cover the various aspects of PLM. 

We identify an initial typology of standards relevant to PLM support. The typology 

primarily addresses the hierarchy of existing and evolving standards and their usage. 

The typology identifies a suite of complementary standards supporting the exchange of 

product, process, operations and supply chain information. 

Given the nature of the task of developing and deploying a set of standards for PLM 

support systems, we argue that open standards with wide participation are the key to 

their realization. 

 

Keywords: Product Lifecycle Management, product realization, PLM systems, interoperability, data 

exchange, standards, open standards

 

1 Eswaran Subrahmanian is a Research Professor at Carnegie Mellon University, Pittsburgh. He is currently a guest 

researcher at MSID, NIST, Gaithersburg, MD 20899, Email: sub@cs.cmu.edu. 2

 Sudarsan Rachuri is with George Washington University, DC. He is currently a guest researcher at MSID, NIST, 

Gaithersburg, MD 20899, Email: sudarsan@gwu.edu. 3 Abdelaziz Bouras is with Lumiere University, Lyon. He is currently a guest researcher at MSID, NIST, 

Gaithersburg, MD 20899, Email: abdelaziz.bouras@univ-lyon2.fr. 4

 Steven J. Fenves is Emeritus University Professor at Carnegie Mellon University, Pittsburgh. He is currently a guest 

researcher at MSID, NIST, Gaithersburg, MD 20899, Email: sfenves@cme.nist.gov. 5

 Sebti Foufou is with LE2i Laboratory, University of Burgundy, B.P. 47870, Dijon France. He is currently a guest 

researcher at MSID, NIST, Gaithersburg, MD 20899, Email: sfoufou@u-bourgogne.fr. 6

 Ram Sriram is leading the Design and Process Group at NIST, Email: sriram@cme.nist.gov. 

1
1 Introduction 

Product lifecycle management (PLM) as a management paradigm is a strategic approach 

to creating and managing a company's product-related intellectual capital, from the 

product’s initial conception to the product’s retirement. As an information technology 

(IT) undertaking, PLM support entails modeling, capturing, exchanging and using 

information in all PLM decision-making processes. 

PLM has come to signify what some call the 21st century paradigm for product 

development. The management of a product from inception to disposal is the strategic 

initiative that defines 21st century product development. This concept is gaining 

acceptance primarily because of the emergence of the networked firm and the networked 

economy, in contrast to the market- or hierarchy-based organizations that used a 

transactions-cost model as the cornerstone for the choice of organizational structure [1]. 

PLM entails the management of product design, manufacturing and service knowledge 

that goes beyond the interaction of suppliers with the system integrator. PLM reaches into 

the sales, customer service and product disposal activities that participate in the larger 

network. Without a comprehensive information base capable of providing the 

information required by the different stakeholders in the product’s entire lifecycle, overall 

efficiencies that can in principle be achieved in the network cannot be realized. 

The concept of the lifecycle of a product is illustrated through the metaphor of epicycles 

in Figure 1. The nodes on the periphery stand for the major stages in the product’s 

lifecycle: conceptualization; organization of resources; design; analysis, simulation and 

verification; manufacturing and distribution; in-use performance and customer feedback; 

and eventually disposal. The wide clockwise links on the periphery stand for the 

“normal” information flows from stage to stage, while the links on the inside stand for the 

feedback information that creates the various epicycles or sub-loops of reappraisal, 

redesign and product improvement or evolution. The feedback loops shown in the figure 

are only suggestive to convey the idea of interdependence among the stages and are not 

comprehensive. 

2
z

z

z

z z

z

z

z

 DESIGN ORGANIZATION: 

 PEOPLE

 INFORMATION

 INFRASTRUCTURE

KNOWLEDGE 

 

CONCEPTUAL DESIGN: 

PRODUCT

PROCESS 

DESIGN EVALUATION: 

 ANALYSIS 

 SIMULATION 

 PERFORMANCE EVALUATION 

 QUALITY EVALUATION 

IDEATION:

MARKET RESEARCH 

USER FEEDBACK 

INNOVATION 

CONCEPTUALIZATION 

MANUFACTURING: 

PLANNING

SUPPLY CHAIN 

CREATION

DISTRIBUTION

PRODUCT USE: 

WARRANTY EXPERIENCE 

MAINTENANCE RECORD 

DETAILED DESIGN: 

PRODUCT

PROCESS 

DISPOSAL: 

RECOVERY 

RECYCLING

Figure 1: Epicycles in product lifecycle development7. 

Some of the feedback loops are unavoidable consequences of product complexity, the 

bounded rationality of the participants, and the rapid changes in technology. How well 

these feedback loops function is critical to the learning process associated with the 

management of information on a product’s lifecycle. Breakdowns in information transfer 

causing additional feedback loops may affect both the efficiency of the operation and the 

quality of the product. The conceptualization of product development presented in Figure 

1 provides credence to the analogy of today’s product lifecycle management systems to a 

control system [3]. This is especially true when the above product development lifecycle 

is seen from the point of view of the globalized market, characterized by changing 

customer preferences and by product variety, manifesting themselves in versions and 

series of the same product. The environment in which the product is designed and 

produced is constantly changing, requiring timely identification and communication of 

failures, anomalies, changes in technology and other important influences. For such an 

adaptable organization to function, an information infrastructure that supports welldefined information exchange processes among the participants is critical. 

 A study of knowledge and information management in a large distributed R&D 

organization has shown that local and global knowledge in such organizations is seldom 

integrated [4]. The recognition of the need for integrated information systems has 

resulted in proposals for maturity models for interoperability to asses and evaluate an 

organization’s ability to provide an interoperable environment [5], [6]. 

 

7

 This figure is adapted from [2]. 

3
The report is organized as follows. In Section 2 we present models of communication and 

of PLM support. We extend this model to the PLM context and describe the current state 

of support for PLM and the needs for information exchange for supporting PLM. In 

Section 3, we present a typology of standards. The typology primarily addresses the 

hierarchy of the standards and is divided into three levels. In Section 4, we present the 

coverage of current standards and their convergence. In Section 5, we present the 

challenges in developing information standards for PLM support. Finally, we present our 

conclusions in Section 6. 

2 Models of Communication and PLM Support 

To understand the role of standards for PLM support systems, we first postulate a model 

of information exchange between two agents (human or computer). We will use this 

model to make the case that supporting PLM is akin to supporting a composition of 

information exchanges across time, space and multiple disciplines. 

2.1 A model of communication between agents 

Communication between two agents requires exchanges that convey the content of the 

information through a language. A model of communication proposed by Flower et al. 

accommodates the semantics of the exchange [7]. In this model, the exchange between 

receiver and sender is dependent on the understanding of the mental model of the receiver 

by the sender, who has to transform his/her mental model to that of the receiver. Both 

mental models are contextualized by awareness, familiarity and other personal 

experiences. The objective of the sender is to ensure that she/he communicate to the 

mental model of the receiver. When the mental models of the receiver and the sender are 

matched, what is communicated takes on a standardized form of exchange. This form of 

standardized exchange behavior within a specified set of conventions is called a protocol. 

The language of a protocol has a form (syntax), function (scope) and the ability to convey 

as unambiguously as possible an interpretation (semantics) when transferred from one 

participant to the other. 

We term the ability of a language to convey a precise semantics the expressiveness of 

that language, more specifically the processible expressiveness as used by Webster to 

mean the computability of the language [8]. Expressiveness of a language is not related 

to the level of abstraction/detail it uses in describing the domain of interest. 

Highly expressive languages are best suited for use within a well demarcated domain. 

Mathematics has served this purpose in many disciplines. Mathematics is a means of 

expressing the physical world with a certain amount of precision and parsimony [9]. 

While mathematics as a meta-language has transcended disciplines, mathematical forms 

used and interpreted in a domain adhere to the disciplinary vocabulary integral to the 

linguistic world of discourse (also known as common ground or domain of discourse) of 

the domain. 

4
Similarly, the visual language of geometry has allowed for the exchange of information 

from designer to fabricator. Visual language has its own protocols, vocabulary and 

mental models and has changed from the traditional drawing on paper to the use of 

computer-based drawing/drafting [10]. In software, the Unified Modeling Language 

(UML) [11] resulted from a consolidation of languages dealing with efforts to manage 

software development [12]. Each language has symbols, rules, conventions and a 

vocabulary that attempt to ensure effective exchange. 

Figure 2 illustrates the exchange of the content in a given domain of discourse between 

the producer and consumer of information and highlights the role of their mental models. 

The figure incorporates the Flower et al. model along with the choice of languages with a 

given processible expressiveness to represent content in a domain of discourse. 

Domain of discourse

Formal

Informal

Language Processible 

expressiveness

Content Represented by

Programming

Information modeling

Visual modeling

Logic based

Query

Natural language

Representational and 

inferential needs

Language types

Producer Specific Consumer

content

Mental

model

Mental

model

Language and expressivity

Domain of discourse

Formal

Informal

Language Processible 

expressiveness

Content Represented by

Programming

Information modeling

Visual modeling

Logic based

Query

Natural language

Representational and 

inferential needs

Language types

Producer Specific Consumer

content

Mental

model

Mental

model

Language and expressivity

Figure 2: Language, Processible Expressiveness and Content 

Exchanges between two agents result in the creation and use of a common linguistic 

world with multiple symbolic languages that serve as a means for efficient exchange of 

content [13; 14]. When the linguistic worlds are not the same, the possibilities of 

misinterpretation and consequently the actions implied by the language (behavior) are 

mismatched. 

In describing the role of protocols in computing, Galloway takes the approach that it is a 

language with a set of conventions that governs the set of possible interpretations 

(behaviors) within a heterogeneous environment. In this sense a language of exchange is 

a technique for achieving voluntary regulation within an environment with many 

5
contingencies [15]. Given the nature of communication in a networked world, protocols 

(specialized and standardized languages) are means for distributed management that 

allow for control to exist within a heterogeneous environment [15]. 

The design of a protocol in the context of information exchange is dictated by: 

1. Content: the information to be communicated. Content includes the model of 

information in the domain and the instances in the domain and explicates the 

relationship between the message and the behavior it intends to elicit from the 

recipient. For example, an ontology of a domain uses a meta-model to create the 

domain specific linguistic world of discourse, leading to the ability to describe the 

information exchanged in a discourse. 

2. Processible Expressiveness: the degree to which a language mechanism supports 

machine understanding or semantic interpretation. Natural language has very low 

expressiveness; by contrast, first order logic and other higher order logic represent 

high levels of expressiveness. 

3. Language: the symbols, conventions and rules for encoding content with known 

expressiveness. 

Expressiveness is closely connected to the scope of the content that can be expressed and 

to the precision associated with that content. The debate on expressiveness8

 as measured 

by the level of conformance to first order logic is illustrative in the development of 

semantic-web-based languages such as Web Ontology language (OWL) [17] and 

Resource Description Framework (RDF) [18]. A good example is the standard for 

dimensioning and tolerancing for manufacturing [19; 20], which uses English, 

mathematics and geometry to explain and codify the standard. The standard represents 

the language of a theory of dimensioning, which serves as the shared mental model in the 

interpretation of the standard [21]. 

We emphasize that there may not be a single representation that can capture all the 

structure and conceptual abstractions of the content in question. Often, compromises need 

to be made in the expressiveness and the level of formalism when deciding on the 

languages to be used in information exchange and on their standards. 

The language chosen or designed for the task is not static and may evolve with 

technology. For example, in geometry the move from traditional drawing to CAD 

evolved in terms of the languages and mental models required in the use and exchange 

process [10]. HyperText Markup Language (HTML) has evolved from its early days, and 

so on. All these languages evolve to incorporate new knowledge and needs as these are 

identified and codified. Given the social nature of knowledge generation and protocol 

creation, as Galloway writes, “By design, protocols such as the internet protocols 

(product information exchange languages) 9 cannot be centralized” [15]. Here the need 

 

8

 The idea of expressiveness has been debated in the knowledge representation community under the two 

terms of “representational adequacy” and “inferential adequacy.” [16]. 9

 Italicized text added. 

6
for agreement across a large number of users is required. We will address the issue of 

how protocols (standards) are created in a later section. 

2.2 Context of PLM support: A complex information management and exchange 

system 

PLM support is a multi-dimensional information exchange undertaking, requiring that a 

variety of contents be exchanged within and across a number of disciplines and functions 

over time and space. To apply the model presented in the last section to the world of 

PLM support, it is necessary to address exchanges among multiple stakeholders who live 

in multiple non-overlapping and overlapping linguistic worlds. 

The intersection of the multiple linguistic worlds of the stakeholders participating in the 

lifecycle of a product creates a new product-centric linguistic world in turn. This new 

linguistic world creates maps among the disciplinary linguistic worlds. This productcentric linguistic world evolves along with the product and the process development. In 

the traditional serialized model of mass production engineering this was not the case. It 

was assumed that the interfaces between the different phases of product development 

were relatively static; that there was no continual improvement in the content of the 

linguistic worlds for exchange, and that the evolution of linguistic structures between 

interfaces was designed in the hierarchical control-based structuring of the organization 

[22]. 

The advent of concurrent engineering brought about the recognition of the importance of 

dynamic information exchange across functional roles so as to ensure the continuing 

validity of the shared linguistic worlds the participants use in their exchanges [23]. This 

dynamic exchange points to the need for: (a) the systematic characterization of the 

different linguistic worlds that participate in the exchanges that take place throughout the 

product lifecycle process; and (b) the ability to create and use context-specific linguistic 

worlds to support the collective task of product lifecycle management across 

organizational boundaries, functions and disciplines. The need for codifying these 

linguistic worlds across the lifecycle has become critical due to two factors at work: (a) 

globalization has spread the need for mass customization of products and services to 

different markets; and (b) global environmental concerns have led to the heightened 

consideration of the servicing and disposal of products as integral parts of the product 

development lifecycle. 

The implication of the above is that the content description in specific information 

exchange contexts requires the customization of languages of different expressiveness to 

make explicit the scope of the exchanges. It is clear that supporting PLM is not a well 

defined task as all of the information needed will not be known a priori. The needs will 

evolve and get incorporated into the system based on the usefulness of the information 

for specific tasks. For example, the representation of the geometry of products has 

evolved from simple drawings to analytical geometry and to more computable 

representations such as boundary representation (B-rep), solid modeling and features. 

7
Here the languages evolved to achieve expressiveness for the description for particular 

aspects of the product development process. In the context of supporting PLM, it is 

inevitable that new languages for different purposes will arise, requiring different levels 

of expressiveness for particular contexts and driven by technological needs and 

possibilities. 

Designers Manufacturers Suppliers Marketing/

Sales Engineers Operations/Maintenance Recyclers

Form 

information

Functional 

Information

Change 

Mgt

Processes

Behavior

Standards: STEP Standards : Incomplete

Function

Requirements

Constraints/

Relationships

Standards : Evolving

Lifecycle 

information

2D/3D

models

Surface 

Model

Features

Material

Tests

Maintenance

Recycle

Topology Disposal

Formal

Informal

Language Processible 

Expressiveness

Content Represented by

Programming

Information Modeling

Visual Modeling

Logic Based

Query

Natural Language

Representational and 

inferential needs

Language types

Domain of Discourse Language and expressivity

Designers Manufacturers Suppliers Marketing/

Sales Engineers Operations/Maintenance Recyclers

Form 

information

Functional 

Information

Change 

Mgt

Processes

Behavior

Standards: STEP Standards : Incomplete

Function

Requirements

Constraints/

Relationships

Standards : Evolving

Lifecycle 

information

2D/3D

models

Surface 

Model

Features

Material

Tests

Maintenance

Recycle

Topology Disposal

Formal

Informal

Language Processible 

Expressiveness

Content Represented by

Programming

Information Modeling

Visual Modeling

Logic Based

Query

Natural Language

Representational and 

inferential needs

Language types

Domain of Discourse Language and expressivity

Figure 3: Communication and information exchange for the PLM 

Figure 3 illustrates how the content of product information is used by various 

stakeholders in a product’s lifecycle. The information content is increasing in two 

dimensions: (a) in complexity because it is being authored and acted on by an increasing 

number of stakeholders; and (b) in scope from form to function and eventually covering 

all aspects of the product during its lifecycle. The increased scope and complexity of the 

content will require languages at various levels of processible expressiveness. We 

emphasize the point that there is no single representation that can capture all the 

8
structural and conceptual abstractions of the content in question for all venues of 

information exchange. 

Support for our model can be seen in the work on developing virtual product models, as 

well as in the development of specific standards in design and manufacture of products. 

As an example, the MOKA (Methodology and tools Oriented to Knowledge-based 

engineering Applications) Project [24], addressing virtual product information, explicitly 

identifies the need to choose languages with the expressiveness required for a specific 

content. The MOKA project itself uses UML as the base language but adds other 

features to create MOKA Modelling Language (MML) [24] to suit the level of 

expressiveness needed in engineering design. 

 

The model of communication for PLM presented here will be used for defining a 

typology of standards that form the basis for effective information exchange and 

interoperability of various systems within PLM. In the next section we describe the 

current state of support for PLM. 

2.3 State of the art of PLM support 

The IT industry that supplies PLM support systems is currently vertically integrated. 

Vertically integrated support systems do not provide for opportunity of full diffusion of 

new innovations across the entire community of users. A study of PLM support provided 

by a representative set of major software vendors shows that the availability of support 

tools is partial and incomplete [25]. The study covers several areas of PLM. Some 

vendors cover several areas, while there are areas that are poorly covered or not covered 

at all by any vendor. Relying on a single vendor to cover all areas of PLM support would 

not provide the kind of innovation needed by PLM customers. The study reveals that 

there is a lack of interoperability across tools and that there are barriers to entry for 

software developers that could provide a plug and play approach to PLM support. 

Currently only a few IT companies with vertically integrated tool sets are able to provide 

facilities that are even partially integrated. 

In an extended enterprise context, PLM support needs to connect the product design and 

analysis processes to the supply chain processes, including: product data management 

(PDM), component supplier management (CSM), enterprise resource planning (ERP), 

manufacturing execution systems (MES), customer relationship management (CRM), 

supply and planning management (SPM), and others that will undoubtedly follow. Most 

of the activities of the systems linked to the supply chain processes are centered on bill of 

material (BOM) management after release through obsolescence, and several stages of a 

BOM may exist: as-planned, as-ordered, as-built, as-shipped, as-maintained, to cite a 

few. Maintaining the accuracy of these stages requires extensive transaction processing 

for recording substitutions, changes, and the like. The benefits of PLM will be realized 

only when these disparate systems are horizontally integrated. Furthermore, as of today, 

there is no commonly agreed-upon linkage between the spatially oriented product 

representations used in design and the BOM based representations used in downstream 

processes. 

9
3 Towards a typology of PLM support standards 

As stated before, PLM support requires a move from product data exchange to product 

information exchange, across different disciplines and domains. 

Several typologies of standards relevant to PLM support have been proposed: 

(1) according to the stages of the product lifecycle the standards address: (a) product 

development standards; (b) product production standards; (c) product use 

standards; and (d) product identification standards linked to product lifecycle 

traceability [26]. 

(2) according to the scope of the standards: (a) PLM commercial best practices and 

specifications; (b) standards related to specific applications; (c) standardized data 

models to represent product data; and (d) domain standards [27]. 

(3) according to the origin of the standards: (a) open standards; (b) industry 

standards; and (c) de facto standards, that are widely accepted and used and 

results generally from widespread consensus [28]. 

(4) according to the development process of the standards: (a) de facto standards; (b) 

regulatory standards created by regulatory agencies to ensure uniformity in 

processes that are not driven by market forces; and (c) consensus standards, 

developed or used by voluntary consensus standard development organizations 

(SDO) [29] . 

(5) according to the intent of the standards: (a) measure or metric standards; (b) 

process-oriented or prescriptive standards, which provide tests in a consistent and 

repeatable way; (c) performance-based standards, where process is not specified 

but the ultimate performance is; and (d) interoperability standards, where 

sometimes process and performance are not explicitly defined, but a fixed format 

is always specified [29]. 

Using the model of communication presented in Section 2.1 and extended to PLM 

support in Section 2.2, we present a hierarchical typology of standards. The typology 

primarily reflects the content to be communicated and implies the appropriate 

expressiveness and language choices for each type. Within each type, individual 

standards may be classified as to origin, intent, development process and, to some extent, 

scope by the typologies listed above. The typology is based on the one initially presented 

in [30]. For illustration, we give some examples of standards in each type. 

Type Zero: Standards for implementation languages 

These standardized languages include programming, scripting, assembly level and other 

computable languages used to implement the Type One, Type Two, and Type Three 

10
standards presented below. Examples include, Basic, FORTRAN, C, C++, Java, C#, 

Prolog, Perl, Tcl/Tk, OpenGL. 

Type One: Information modeling standards 

Semantically rich modeling language standards, based on different forms of logic, 

include the Knowledge Interchange Format (KIF), OWL and RDF that support reasoning 

over the information representing a content domain [17; 18; 31]. OWL includes the 

RDF/XML interchange syntax and has three sub-languages of different expressiveness 

and complexity (OWL Lite, OWL DL, OWL Full). All of these efforts are directed 

towards building formal ontologies that are expected to aid semantic interoperability. 

EXPRESS [32] and UML (Unified Modeling Language) are two examples of information 

modeling languages. EXPRESS is used in the STEP-based systems [33], while UML is 

based on the object-oriented methodology [12]. UML is primarily intended for 

specifying, visualizing, constructing, and documenting components of software systems 

as well as for business modeling and other non-software systems. The expressive power 

of EXPRESS is comparable to the combination of UML and the Object Constraint 

Language (OCL), a formal language used to describe expressions in UML models [34]. 

XML Schema is becoming popular for expressing the structure and typing constraints for 

data embedded in XML documents. XML Schema offers a higher level of expressiveness 

than the earlier DTD (Document Type Definition) descriptions. 

A NIST focus area is the standardization of the representation of manufacturing 

processes, called the Process Specification Language (PSL) [35]. PSL uses first order 

logic and Ontology Web Language (OWL)-like representations [17]. 

Type Two: Content standards - domains of discourse 

Content standards pertain to information models specifically defined for particular 

domains using a generic information modeling language (Type One) or an extended one 

(for example, UML with its extension, SysML). The Systems Engineering Modeling 

Language (SysML) is directed towards the specific domain of systems engineering. 

SysML is derived from the basic UML to cover the requirements, structure, behavior, 

parametrics, and the relation of structure to behavior (allocation) [36]. Content standards 

might use general Type Zero languages for implementation. 

Content standards subdivide into several categories based on the specialization of the 

content addressed. The principal categories are briefly described below. 

Product information modeling and exchange standards. Standards such as ISO 

10303, informally known as the STandard for Exchange of Product model data (STEP) 

deal with product structure and geometry and part-related information [37]. STEP uses 

the EXPRESS information modeling language to define a generic product model. In the 

modular approach of STEP, information models form modules and integrated resources 

11
(IRs), from which specific content standards (application protocols or APs) are 

developed (for example, AP 214 [38]). These specific content standards can use specific 

catalogs. As another example, UML and its extension, SysML, can be used to define 

specific system (say, control system) standards. This hierarchy is illustrated in the 

following figure (The arrows represent “uses”). 

EXPRESS 

Modules and IRs 

Application 

protocol (AP) 

Catalog/repository 

UML 

SysML 

Control system design tool 

standard Automotive design tool 

standard

Figure 4: Examples of Content Standards 

STEP AP239, called PLCS (Product Lifecycle Support), is dedicated to product support 

and is based on an extension to the STEP PDM Schema capability [39]. PLCS provides 

mechanisms to maintain the information needed to support complex assets (such as ships, 

aircraft or engines). PLCS builds upon the functionality defined by other standards 

relevant to product support (these include AECMA S1000D, AECMA 2000M, United 

States Military Specification 1388, United Kingdom Defense Standard 00-60). 

Information exchange standards. XML-based protocols are being developed to 

exchange content among various stakeholders. Examples of information exchange 

standards are the electronic data interchange (EDI) [40] and the simple object access 

protocol (SOAP) [41] standards. Among the specialized versions of these exchange 

standards are: (a) STEPml [42], a library of XML specifications based on the content 

models from the STEP standard; (b) the Product Data Markup Language (PDML) [43] 

being developed as part of the Product Data Interoperability (PDI) project [44]; (c) PLM 

XML [45], a set of XML schemas serving as a transport protocol; and (d) BPML 

(Business Process Modeling Language) [46], a meta-language for the modeling of 

business processes. 

Product visualization standards. The U3D graphics standard is a simple format for 

interactive viewing and sharing of 3D data [28]. X3D is an XML-enabled 3D standard to 

enable real-time communication of 3D data [47]. JT is a CAD neutral data format for 

product visualization, collaboration and data sharing [48]. JT Open is a library of Java 

classes supporting the client/server and Internet programming models. JT2Go is a JT 

12
format viewer. OpenGL (Open Graphics Library) is a low-level graphics library for 3D 

data visualization [49]. OpenML (Open Media Library) is a programming environment 

that supports the creation and playback of digital, audio, video and graphics [50]. 

E-business and value chain support standards. Many extensions to XML have been 

osettaNet is an example of standardizing eBusiness interfaces to align processes 

nother interesting initiative for supply chains is the SCOR reference model, which 

ecurity standards. The earlier types of standards focus on what is to be represented, 

ype 3: Architectural frameworks standards 

o achieve interoperability between the standards within the PLM context, it is 

developed to describe the business activities associated with all phases of satisfying 

customer demand, such as electronic business XML (ebXML) [51] to replace traditional 

EDI standards and commerce XML (cXML) [52]. Related extensions include the 

Chemical markup language (CML) [53] and the Materials Markup Language (MatML) 

[54]. 

R

between supply chain partners [42]. The IPC-2570 standard series is a complementary 

effort to foster application integration through encoding scheme that enables a total 

product definition to be described at a level appropriate to facilitate supply chain 

interactions [55]. 

A

defines standard metrics to measure process performance and management practices [56]. 

A new model called VCOR aims at providing a unified and universal approach to 

organizational analysis and help in consolidating enterprise processes [57]. VCOR is 

intended to be a de facto standard Value Chain Operational Reference Model [58]. 

S

how it is to be represented and how it is to be exchanged. What is missing is how much 

of the information needs to be exchanged and with whom. This is important from the 

point of view of information overload, intellectual property rights, and security. DRM 

(Digital Rights Management) refers to technologies that have been specifically developed 

for managing digital rights. As an example, XrML (eXtensible rights Markup Language) 

provides a universal method for specifying rights and issuing conditions associated with 

the use and protection of content [59]. Various organizations such as the NIST 

Information Technology Laboratory and the World Intellectual Property Organization 

(WIPO) are establishing international standards in this area [60]. 

T

T

imperative that the different types of standards described in this section be reconciled and 

made convergent. In integrating these types of standards, it is necessary to take into 

consideration the architectural frameworks for creating integrated support systems. A 

number of integration framework standards have been proposed, such as the Zachman 

Framework [61], the Department of Defense Architecture Framework (DoDAF) [62] and 

the Federal Enterprise Architecture Framework (FEAF) [63]. These frameworks do not 

yet provide the full spectrum of viewpoints needed to address the overall interoperability 

concerns. Another interesting framework is the ISO RM-ODP Reference Model for Open 

Distributed Processing [64]. This model has been used as a framework for CORBA-based 

13
distributed applications management, and defines five architectural viewpoints that 

address a wide range of interoperability concerns from policies and procedures to 

engineering solutions: the enterprise, information, computational, engineering and 

technology viewpoints. 

 

4 Convergence of PLM support standards 

he current state of the underlying linguistic structures populating PLM support is 

he importance of interoperability across the phases and functions in PLM among the 

oday’s standards, particularly in the area of CAD, have produced direct improvement in 

 the context of PLM the need for standards at different levels of expressiveness 

 

T

fragmented and incomplete in coverage. Beyond incompleteness, the incompatible 

linguistic structures have evolved bottom up (based on localized needs and vendorcentric definitions) in developing support for particular aspects of the product lifecycle. 

This has led to the lack of interoperability, an issue that has become the Achilles heel of 

integration for PLM support. 

T

multiplicity of languages dealing with the varied contents comprising the complete 

product description has been recognized by a number of institutions including NIST, the 

US Department of Defense (DOD), the European Ministries of Defense and, more 

recently, by the vendor and end-user communities [65; 66]. While there has been 

articulation of the need, the issue has not been fully addressed due to the divergence of 

interests on how interoperability should be achieved. The challenge is to create standards 

and protocols that allow legacy systems as well future technological innovations to 

interoperate seamlessly. 

T

productivity, especially in the manufacturing arena, by reducing transaction costs and 

even more so by increasing the richness of interactions between supplier and customer 

[67]; [68]; [69]. The real cost of the lack of interoperability is difficult to measure and is 

often buried in day to day operations of individuals needing the information or needing to 

transmit the information. 

In

becomes critical in supporting the processes of information exchange. The achievement 

of the PLM objectives requires near decomposability of systems, as was observed by 

Herbert Simon in his essay, “The Architecture of Complexity” [70]. We claim that the 

complexity of the information exchange issue and the diversity of participants and their 

perspectives make it highly improbable that a single disciplinary perspective can 

accomplish the task of supporting PLM. For these reasons we believe that much of the 

stable part of the information base supporting PLM should be developed within the 

framework of open standards. The recent document called Roadmap for Open ICT 

Ecosystem [71]10, defines open standards as standards that are created by standardssetting organizations including consortia such as the Internet Engineering Task Force 

(IETF), the World Wide Web Consortium (W3C), and the Organization for the 

10 released by the Berkman Center for Internet and Society at the Harvard Law School 

14
Advancement of Structured Information Standards (OASIS) and formal standard 

development organizations (SDOs) such as the American National Standards Institute 

(ANSI) and the International Organization for Standardization (ISO). Krechmer 

provides more detailed definitions of open standards, open source, and open architecture; 

and defines ten rights that will enable open standards [66]. 

The incompatibilities and gaps that exist among current standards can arise at different 

t is clear from Figure 5 that there is no standard that provides full coverage of the PLM 

levels. These can be explained using the typology defined in Section 3. The 

incompatibility may arise at the level of implementation by the choice of Type Zero 

standards. The choice of Type One Standards and the underlying representation 

formalism is another major source of incompatibility. The choice of Type Three 

standards may lead to different architectural frameworks which might introduce more 

incompatibility. The gaps among standards can be understood by differences in the 

domain of discourse and in the scope of standards along the PLM spectrum. 

I

support spectrum. Note also that some standards, for example SysML and PSL, cover 

some aspects of PLM with notable discontinuity in their scope. Product Process Enterprise services

Ideation

Design organization

Conceptual design

Detailed design

Design evaluation

Manufacturing

Supply

chain

Product use

Disposal

SCOR

SysML

PSL

EDI ebXML

PLCS

STEP SysMLPSL

Product Process

Enterprise services

Ideation

Design organization

Conceptual design

Detailed design

Design evaluation

Manufacturing

Supply

chain

Product use

Disposal

SCOR

SysML

PSL

EDI ebXML

PLCS

STEP SysMLPSL

Figure 5: An example of current standards and their coverage 

15
5 Challenges in standards development for PLM 

As the type and scope of the standards needed for PLM support becomes clearer, there is 

increased interest in the models that have emerged in the distributed internet world for 

standards development and software production. Specifically, it is increasingly clear that 

a combination of open source models and TCP/IP-like open standards approaches is 

needed [15; 65]. The Internet Engineering Task Force (IETF) open standards approach 

ensured that the features incorporated were demonstrated to be useful not just for one 

organization but for all who are affected and interested enough to participate in the 

process. Membership in these standards development organizations is voluntary; the 

reputation of the contributor through prior reliable and useful contributions and active 

participation leads to influence and power. Open source models that have evolved with 

the rise of the internet have addressed the large scale distributed design of complex 

products. The primary reason for success of the open source model has been its ability to 

scale that transcends “Brooks’ Law” [72]. According to Brooks’ law, the propensity for 

errors increases geometrically when resources are added linearly. In the case of open 

source, this constraint on the use of resources is resolved through the voluntary nature of 

participation and task selection [65]. Further, the availability of the complete record of 

the decision-making process and of the results of testing and use allows for the designuse-maintenance cycle to be rather quick in turnaround. The major success of open 

source comes from the recognition of the scale and diversity of skills through modular 

design; minimizing costs of bad local decisions; and the ability to mobilize people of 

diverse skills [65]. 

The development of standards for PLM support requires many people with different skills 

and expertise to participate. These people cannot be assembled in one place -- virtual or 

real -- to create a centralized top-down set of standards. Standards are best created in an 

open process and within a voluntary participatory model. Earlier experiences with 

standards development in the distributed, connected world point to open standards and 

open source models as an alternative model of consensus building and production [66]. 

Who should be responsible for creating these communities is an open question. Many 

existing standards have been created by individuals or groups of individuals. Some of 

these efforts also involve regional economic development zones. 

There are enormous benefits due to network effects that can be realized socially by open 

approaches; this will allow university, industry (small, medium, and large), and 

laboratories to draw out of the same well, minimizing incompatibilities and increasing the 

ability to create a plug-and-play system. This approach will foster innovation at the 

modular level without requiring a drastic redesign of the overall system. Repeated drastic 

design changes for both standards and software lead to increased costs in the creation, 

training, maintenance and archiving of the information and knowledge created in the life 

of a product. The open source and open standards models seem to address these issues in 

the best manner given the scale and scope, and provides us with alternative models for 

standards development. 

Maintenance and use require conformance to standards and certification of the same. 

Institutions such as NIST can play a major role in being the honest broker and archivist of 

16
the process of standards creation, maintenance, and evolution. To encourage this process, 

the Manufacturing Interoperability Program of the Manufacturing Engineering 

Laboratory at NIST is working on achieving convergence among standards. Beyond the 

convergence of the types of standards referred to in this paper, standards for other aspects 

such as traceability, validation, verification and other audit and archival functions will 

have to be considered in the support system for PLM [73]. A good example is the Open 

Archival Information System (OAIS) reference model which facilitates a much wider 

understanding of what is required to preserve and access information for the long term 

[74]. 

The current disparate standards with differing assumptions and purposes are not easily 

reconciled; neither can they be resolved by any single entity. The extraction of positive 

network externalities in the networked manufacturing economy can only be achieved by 

the free flow of ideas and the exchange of knowledge in a public or semi-public space to 

create new innovations in the new knowledge economy [75]. To exploit the efforts of a 

large number of researchers, practitioners, users and students to continuously integrate 

their work into the larger vision of full PLM support, there is no choice but to develop a 

pragmatic mechanism for supporting the development of standards in an open 

environment where the participation of all parties concerned will become critical. 

The convergence of standards can only take place in an open environment given the 

complexity of the task ahead. This realization can be seen in the publications of 

information technology vendors such as IBM, end users such as DOD and engineering 

consultants making a case for open standards for the information base required to support 

the underlying IT infrastructure to accommodate legacy and changing technologies [5; 

76; 77]. 

6 Conclusions 

In this paper, we start by describing a model of communication between agents and 

extend the model for PLM support among various stakeholders. This model of 

communication is influenced by: (1) the choice of a particular language with a required 

level of processible expressiveness; (2) the choice of representational formalism and an 

appropriate information modeling language; (3) structuring of the domain knowledge 

using the above choices; and (4) architectural frameworks as a medium of 

communication. Using this model we defined a typology of standards. 

We also provided an overview of the current state of IT standards for PLM support. The 

incompatibility and gaps that exits among standards could be due to various reasons that 

can be explained using the typology defined in Section 3. 

We make a case that the nature of the task needs open standards with wide participation. 

It is always said that markets are the best determinants of standards and that, if history is 

a guide, even market forces lead to co-operation among competitors to work towards 

open standards. Publications in the popular press lead us to believe that IT vendors are 

ready for a move towards open standards. As is evidenced in the evolution of the Internet, 

the development of standards can only flourish through an open but centralized 

17
participatory model of development. A single monolithic/monopolistic structure is not 

adaptable and flexible to address the variety and complexity inherent to this issue. 

Standards cannot be advocated by just a select few in the organization. While advocating 

open standards, Srinivasan claims that the natural tendency of PLM software vendors is 

to make their product the de facto standard, which allows them to control the content and 

the price of their products; and that customers, on the other hand, push for open 

standards, which allow them freedom of choice and flexibility in running their businesses 

[78]. He states that this tension is not likely to disappear any time soon and must be 

treated as a part of the standardization process. How you overcome this tension by 

accommodating the needs for intellectual property rights for sustainable business and the 

needs of end users are questions that are still being answered in the open source 

community. 

7 Disclaimer 

No approval or endorsement of any commercial product by the National Institute of 

Standards and Technology is intended or implied. Certain commercial equipments, 

instruments, or materials are identified in this report to facilitate better understanding. 

Such identification does not imply recommendations or endorsement by the National 

Institute of Standards and Technology, nor does it imply the materials or equipment 

identified are necessarily the best available for the purpose.[65] 

References 

 1. Powell, W. W., Neither market nor hierarchy: network forms of organization. Staw, B. M 

and Cummings, L. L. 295-336, 1990. Greenwich, CT, JAI Press. Research in 

Organizational Behavior. 

 2. Lederberg, J., Introduction: Reflections on Scientific Biography. Lederberg, J. [3], xviixxiv, 1990. Annual Reviews Inc, CA, USA. The excitement and fascination of science: 

Reflections by eminent scientists- Part 1. 

 3. Westerberg, A., Subrahmanian, E., Konda, S. L., and Reich, Y., Designing the Design 

Process. Special Issue of Computers and Chemical Engineering 21, s1-s9, 1997. 

 4. Davis, J., Subrahmanian, E., and Westerberg, A., "The Global and the Local in Knowledge 

Management," Journal of Knowledge Management, Special Issue on Technology, Vol. 9, 

No. 1, 2005, pp. 101-112. 

 5. C4ISR Architecture Working Group, "Levels of Information Systems Interoperability 

(LISI): C4ISR Architecture Working Group Final Report," 1998. 

 6. Ingward, B., Falk, M., Edwin, S., and Erik, M., Project iViP: Integrated Virtual Product 

Creation - Final Report. Frank-Lothar, K, Trac, T, and Irich, A. 2002. Organization 

responsible for production and manufacturing technologies (PFT), Research Centre 

Karlsruhe GmbH. 

 7. Flower, L., Stein, V., Ackerman, J., Kantz, M. J., McCormick, K., and Peck, W. C., 

Reading-to-Write Exploring a Cognitive and Social Process, Oxford University Press, 

1990. 

18
 8. Dallas E.Webster, "Mapping the design information representation terrain," IEEE 

Computer, Vol. 21, No. 12, 1998, pp. 8-23. 

 9. Gregory, B., Inventing Reality: Physics as Language, John Wiley & Sons, New York, 

1988. 

 10. Henderson, K., On Line and on Paper: Visual Representations, Visual Culture, and 

Computer Graphics in Design Engineering, MIT Press, Cambridge, MA, USA, 1998. 

 11. OMG, UML 2.0 Superstructure Specification. http://www.omg.org/cgi-bin/doc?ptc/03-08-

02 , 2003. 

 12. Booch, G., Rumbaugh, J., and Jacobson, I., The United Modeling Language User Guide, 

Addison-Wesley, 1997. 

 13. Clark, H. H., Using Language, Oxford University Press, 1996. 

 14. Minneman, S. L., and Leifer, L., "Group engineering design practice: The social 

construction of a technical reality,"1993. 

 15. Galloway, A. R., Protocol, how control exists after decentralization, The MIT Press, 2001. 

 16. Minsky, M., "Commonsense-based Interfaces," Communication of ACM, Vol. 43, No. 8, 

2000, pp. 67-73. 

 17. Web Ontology Language (OWL). http://www.w3.org/2004/OWL/ , 2005. 

 18. RDF- Resource Description Framework. www.w3.org/RDF/ , 2005. 

 19. ISO 1101:1983, Technical drawings -- Geometrical tolerancing -- Tolerancing of form, 

orientation, location and run-out -- Generalities, definitions, symbols, indications on 

drawings. International Organization for Standardization, Geneva, Switzerland. 

 20. ASME, Dimensioning and Tolerancing Y14.5M, ASME, 1994. 

 21. Srinivasan, V., "A geometrical product specification language based on a classification of 

symmetry groups," Computer-Aided Design, Vol. 31, No. 11, 1999, pp. 659-668. 

 22. Waring, S. P., Taylorism Transformed: Scientific Management Theory Since 1945, 

University of North Carolina Press, 1994. 

 23. Finger, S., Konda, S. L., and Subrahmanian, E., "Concurrent Design Happens at the 

Interfaces," AIEDAM, Vol. 9, 1995, pp. 89-99. 

 24. MOKA, MOKA: A Framework for structuring and representing engineering knowledge. 

http://www.kbe.coventry.ac.uk/moka/miginfo.htm , 1999. 

 25. Burkett, M., Kemmeter, J., and O'Marah, K., "Product Lifecycle Management: What's Real 

Now," AMR Research, September 2002, 2002. 

19
 26. Terzi, S., Elements of Product Lifecycle Management: Definitions, Open Issues and 

Reference Models. 2005. Politecnico di Milano, Italy and Henri Poincarre University of 

Nancy, France. 

 27. Iyer, R. G., and Gulledge, T., "Product Lifecycle Management for the US Army Weapon 

Systems Acquisition," Inderscience Publishers, PLM: Emerging solutions and challenges 

for Global Networked Enterprise, ISBN 0-907776-18-3,2005, pp. 553-564. 

 28. Lubell, J., Peak, S. S., Srinivasan, V., and Waterbury, S. C., "STEP, XML, AND UML: 

Complementary Technologies," Vol. CIE-2004-141, Proceedings of DETC 2004: ASME 

2004 Design Engineering Technical Conferences and Computers and Information in 

Engineering Conference September 28–October 2, 2004, Salt Lake City, Utah USA,2004. 

 29. Allen, R. H. and Sriram, R. D., "The Role of Standards in Innovation," Technological 

Forecasting and Social Change, Vol. 64, 2000, pp. 171-181. 

 30. Gruber, T. R., "A translation approach to portable ontologies," Knowledge Acquisition, 

Vol. 5, No. 2, 1993, pp. 199-220. 

 31. KIF-Knowledge Interchange Format. http://logic.stanford.edu/kif/kif.html , 2005. 

 32. ISO 10303-11: 1994, Industrial automation systems and integration -- Product data 

representation and exchange -- Part 11. Description methods: the EXPRESS language 

reference manual. 

 33. Schenck, D., and Wilson, P. R., Information modeling: the EXPRESS way, Oxford 

University Press, New York, 1994. 

 34. OMG, UML 2.0 OCL Specification. http://www.omg.org/cgi-bin/doc?ptc/03-10-14 , 2004. 

 35. Process Specification language (PSL) . http://www.nist.gov/psl , 2005. 

 36. Bock, C., "Systems Engineering in the Product Lifecycle," International Journal of 

Product Development, Special Issue on Product Lifecycle Management, 2004. 

 37. Kemmerer, S., "STEP: The Grand Experience, (Editor)," NIST Special Publication 939, 

National Institute of Standards and Technology, Gaithersburg, MD 20899, USA, 1999. 

 38. ISO/DIS 10303-214:2000, Product data representation and exchange: Integrated application 

resource: Application protocol: Core data for automotive mechanical design processes. 

International Organization for Standardization (ISO), Geneva, Switzerland. 

 39. The STEP PDM Schema Home Page. http://www.pdm-if.org/pdm_schema/ , 2005. 

 40. UN/EDIFACT: United Nations standards for Electronic Data Interchange for 

Administration, Commerce and Transport. http://www.unece.org/trade/untdid/welcome.htm

, 2005. 

 41. SOAP Specifications. http://www.w3.org/TR/soap/ , 2005. 

 42. STEPml - STEP markup Language. http://www.stepml.org/ , 2005. 

20
 43. Product Data Markup Language (PDML). http://www.PDML.org/pdmlintro.html , 2005. 

 44. Joint Electronic Commerce Program Office (JECPO) re-named as Defense Electronic 

Business Program Office. http://www.acq.osd.mil/scst/index.htm , 2005. 

 45. PLMXML. www.plmxml.org , 2005. 

 46. Business Process Modeling Language (BPML). http://www.service-architecture.com/webservices/articles/business_process_modeling_initiative_bpmi.org.html , 2005. 

 47. Web3D: Open Standards for Real-Time 3D Communication. http://www.web3d.org/ , 

2005. 

 48. Wang, M. Y. and Wang, X., "A level-set based variational method for design and 

optimization of heterogeneous objects," Computer-Aided Design, Vol. 37, No. 3, 2005, pp. 

321-337. 

 49. OpenGL - The Industry Standard for High Performance Graphics. http://www.opengl.org/ , 

2005. 

 50. OpenML - The Standard for Dynamic Media Authoring. http://www.khronos.org/openml/ , 

2005. 

 51. ebXML. http://www.ebxml.org/ , 2005. 

 52. cXML. http://www.cxml.org/ , 2005. 

 53. CML. www.xml-cml.org/ , 2005. 

 54. Materials Markup Language (MatML). www.matml.org , 2005. 

 55. Shop floor communications (PDX): IPC 257x. http://webstds.ipc.org/2571/2571.htm , 

2005. 

 56. SCOR: Supply Chain Operations Reference-model. http://www.supply-chain.org/index.ww

, 2005. 

 57. VCOR: Value-Chain Operations Reference. www.value-chain.org , 2005. 

 58. Roy, U. and Liu, C. R., "Establishment of functional relationships between product 

components in assembly database," Computer-Aided Design, Vol. 20, No. 10, 1988, pp. 

570-580. 

 59. eXtensible rights Markup Language (XrML). www.xrml.org/ , 2005. 

 60. The World Intellectual Property Organization (WIPO) . http://ww.wipo.org/ , 2005. 

 61. Sowa, J. F. and Zachman, J. A., "Extending and Formalizing the Framework for 

Information Systems Architecture," IBM Systems Journal, Vol. 31, No. 3, 1992, pp. 590-

616. 

21
 62. DoD, DoD Architecture Framework Working Group, DoD Architecture Framework 

Version 1.0, Volume I: Definitions and Guidelines. 

http://www.defenselink.mil/nii/doc/DoDAF_v1_Volume_I.pdf , 2004. 

 63. A Practical Guide to Federal Enterprise Architecture. 

http://www.cio.gov/archive/bpeaguide.pdf , 2001. 

 64. DSTC RM-ODP Information Service. 

http://www.dstc.edu.au/Research/Projects/ODP/ref_model.html , 2005. 

 65. Weber, S., The Success of Open Source, Harvard University Press, Cambridge, MA, 2004. 

 66. Krechmer, K., "Open Standards requirements," The International Journal of IT Standards 

and Standardization Research, Vol. 14, No. 1, 2006. 

 67. Robertson, D. and Allen, T. J., "CAD system use and engineering performance," IEEE 

Transactions on Engineering Management, Vol. 40, No. 3, 1993, pp. 274-282. 

 68. Liker, J. K., The Toyota Way: 14 Management Principles from the world's greatest 

manufacturer, Mc Graw Hill, 2004. 

 69. Gregory, T., "Interoperability Cost Analysis of the U.S. Automotive Supply Chain," 

National Institute of Standards and Technology, Department of Commerce, USA, 99-1 

Planning Report, 1999. 

 70. Simon, H. A., "Architecture of complexity," Proceedings of the American Philosophical 

Society, Vol. 106, 1962, pp. 467-482. 

 71. The Berkman Center for Internet and Society at Harvard University, "Roadmap for Open 

ICT Ecosystems," 2005. 

 72. Brooks, F. P., The Mythical Man-Month: Essays on Software Engineering, 20th 

Anniversary Edition, Addison-Wesley Professional, Boston, MA, USA, 2005. 

 73. Denno, P. and Thurman, T., "Requirements on Information Technology for Product 

Lifecycle Management," International Journal of Product Development - Special Issue on 

PLM, Vol. 5, No. 1, 2005. 

 74. CCSDS, "CCSDS 650.0-B-1: Reference Model for an Open Archival Information System 

(OAIS). Blue Book. Issue 1. ISO 14721:2003.," 2005. 

 75. David, P. A. and Foray, D., "Economic Fundamentals of the Knowledge Society,Policy 

Futures In Education," An e-Journal : Special Issue: .Education and the Knowledge 

Economy, Vol. 1, No. 1, 2003. 

 76. Mick, R., Defining and Measuring Interoperability. ARC Insights, Insight 2004-43 , 2004. 

 77. Srinivasan, V., Open Up PLM Systems. Design News , 2004. 

 78. Srinivasan, V., "Open Standards for Product Lifecycle Management," Inderscience 

Publishers, in PLM: Emerging solutions and challenges for Global Networked Enterprise, 

ISBN 0-907776-18-3,2005, pp. 475-484. 

22
23