Series
Toward Realization of Smart Manufacturing Systems

Case: Improvement of the Machining Process Productivity
Based on the Machine Tool Technology

Robot Revolution Initiative
WG for manufacturing business revolution through IoT
The Industrial Machinery Steering Committee

April 2016

Contents
1. What is implementation of smart manufacturing?
2. Improvement of the machining process productivity based on the machine
tool technology
3. Examination method
4. Overview of the target services and the issues(1) Remote maintenance service, predictive maintenance service, andproduction management service(2) Issues faced on the spread of the target services
5. Information modeling associated with remote maintenance service, predictive
maintenance service, and production management service(1) Organization of information modeling for machine tools(2) Organization of information modeling for the target services
6. Draft of the guidelines for the deployment of the target services extracted
from the information model(1) The guidelines/interfaces relating to the definitions of the basic states ofmachine tools and methods for extracting information on the states(2) Basic concept relating to information security measures at connection ofmachine tools with the Internet− Technical background−−

Examples of use cases
Information security management establishment on the factories andmanufacturers(3) Guideline for access control for digital data generated by machine tools
7. Proposal of a smart factory by utilizing the information model relating to thetarget services

1. What is implementation of smart manufacturing?
Currently, new information technologies including IoT, big data, and artificial
intelligence (AI) have brought significant changes in various fields of theeconomic society and a reform called "the 4th industrial revolution" is occurringin the manufacturing industry also.
Until now, in the manufacturing industry, the information and knowledge
intensive reforms have occurred to in the manufacturing process. Above all, inparticular, in a machining process (a process starting from setting work in amachine tool up to the final process in a production line), control systems aredeveloping at high levels by commanding the digital control technology whilepursuing improvement of accuracy and efficiency. Such control systems
generate and process a large volume of data with variety of types including
information on the status of the work, which is the target of machining andinformation relating to the status of the machine tool that performs themachining.
In the context of the 4th industrial revolution, these information items become thesources of new value creation while involving synergistic effects with theinformation generated from other systems beyond the prime objectives, which
are the improvement of accuracy and efficiency of the machining process. That
is why the term indicating a discontinuous change, "revolution", is used. For
instance, from a perspective of management of a supply chain from order
receiving to product shipment, the information presents the machining processprogress status as well as the operating status of the related facility such asmachine tools, leading to the global optimization of the production plan. From aperspective of management of daily operation of a machine tool and so on, theinformation can be used for the identification of the health of machine tools andfor the basis of predicting failure occurrence. Furthermore, a machine tool
manufacturer may be able to accumulate the information about the machine tool
operations in various utilization conditions in a long term, which can be used andanalyzed. As a result, the machine tool manufacturer will be able to use theinformation for design and development of machine tools with higher
performance as well as for refinement of the operational expertise to exert thefunctions to the maximum capability. With use of such operational expertiseeffectively, the manufacturer can develop a service business that supports the
improvement of accuracy and efficiency of the machining process. Eventually, a1smart machining process will be able to create new industries, not to mention theincrease of competitiveness of the existing industry.
In this way, the revolutionary change mentioned today provides opportunities foracquiring new added values not only for manufacturers regarded as users ofindustrial machineries, but also for manufacturers of industrial machineries. In
particular, in the movement called a new industrial revolution, the cases where
information technology is provided through open source are becoming tangible
and utilization of information technology that is developing remarkably isessential for securing competitiveness. However, the obstacle for
implementation of the service that adds high values by utilizing the information
technology cannot be easily overcome. This is because linkage and integration,
which have not been contemplated, but rather have been avoided, arenecessary. Typical obstacles are vague uneasiness towards the unexpectedrisks associated with linkage and integration, with which the operators have noexperience, concerns towards the risks associated with information leakage andsecurity attacks that will inevitably increase as a result of linkage and integration,technical issues (interfaces, protocol, and so on) of the information system forwhich linkage and integration have not been assumed originally.
A promising approach for achieving significant results through the revolutionarychange by overcoming these obstacles is to find specific examples of smart
manufacturing that can create an added value substantially enough to overcome
the difficult obstacles, share the smart manufacturing among the stakeholders,and acquire the methodology for overcoming the obstacles through theimplementation.
Smart manufacturing has the following three features.
Firstly, it has the mechanism that centrally manages and integrates productionengineering data of the machines in the factory, processes the data that is
obtained as a result, and provides the data to upper level systems such as ERP
and MES, on the production management side, as the data useful for
improvements of machining efficiency of the machines, predictive maintenance,and “Kaizen” (on-site improvement activities).
Secondly, it has the mechanism that enables optimization of the entire
production line without human interventions beyond the conventional approachof accumulating partial optimizations performed manually in each process, by2

feeding back to the machines the production engineering data that has been
digitally processed.
Thirdly, it has the mechanism that enables the visualization of the entire
structure of the engineering chain, which is production engineering, and the
supply chain (production control), which is production management,
management in an integrated manner by utilizing AI technologies if necessary,capture the site as the cyber-physical system, and consequently, achieve
improvements that lead to the global optimization.
The linkage and integration, which are the essence of smart manufacturing,
require collaboration among multiple different entities under the commands ofthe conductor that performs the total optimization. On the other hand, a newvalue that is created through collaboration is spread to many stakeholders over awide range, not attributed to specific players only. The important factors forcreating such a structure as this and realizing the win-win relationship are that
implementation of smart manufacturing is presented in the form that can beshared by a wide range of stakeholders, the merits, risks, and risk management
techniques are correctly understood, and wide range of entities can participate.
Above all else, it is important for operators that use smart manufacturing to proveto the customers their abilities to provide the solutions such as the best products
and services and that many stakeholders enjoy the profits.
"Series: Toward Realization of Smart Manufacturing Systems" is the message tothe world from the practitioners at the front line in Japan, who declare as theleaders of the revolution and share and implement such a concept as this.
2. Improvement of the machining process productivity based on the machine
tool technology
As the primary approach to the realization of smart manufacturing, improvementof the machining process productivity is focused on and examined.
In a sense where advancement of the manufacturing industry has been realized
by mechanization in production processes, industry machine manufacturers
made a significant contribution to the evolution of the manufacturing industry. In
the emerging countries that are aiming at adding high values to the
manufacturing industry, movements for adding high values will spread in the
future by installing advanced industry machines as has been done by developed3countries.
Among the production processes, in a machining process in particular, there are
significant differences depending on the operating skill levels of machine tools
and the productivity and added values are influenced greatly by thecomprehensive expertise including setup and maintenance inspection.
Therefore, there is an ample scope for machine tool manufacturers to makecontributions. That is, a new market is available for machine tool manufacturers
as "manufacturing service providers" that provide the effective utilization
expertise of machine tools as well as supplying them.
Accordingly, this document summarizes and presents the use cases towardrealization of smart manufacturing by specifying concrete services that improves
the productivity of a machining process through the capitalization of the latest
technologies such as IoT and AI as the precondition.
3. Examination method
An examination team was organized (see page 46) by the practitioners mainly
including the users and manufacturers of the machine tool. The examination was
carried out in the following procedure as the implementation that conforms to theactual businesses.
[1] Based on the customer needs relating to machining processes, teammembers documented the summary of the specific details of the services
addressed as the implementation of smart manufacturing. After that thetarget service contents were specified by the team.
[2] The service that was specified in [1] was described as the information
model (in this examination, SysML of OMG is used) as a common method
to enable the team members to mutually compare their services
implemented or examined for this implementation.
[3] Through the comparative analysis of the information models based on theexamined service contents provided by the team members, the teammembers extract common items, which construct the basic (general)structure of the service.
[4] The forms of linkage and integration with other systems, which arenecessary for implementation of the service, were verified based on theinformation model that was specified in [3] and the items that are to be4

regulated into rules such as the items to be standardized includinginterfaces, security, and data control entities were specified andsummarized.
4

Overview of the target services and the issues(1) Remote maintenance service, predictive maintenance service, andproduction management service
To improve the productivity of machining processes, it is necessary tominimize the reduction in the operating rate caused by troubles as well as
promote multitasking of machine tools to minimize work transfers and setupchanges (e.g., increase of the number of controlled axes and number ofmachine tools used).
Of these objectives, each machine tool manufacturer has focused on thelatter objective since around 2000 and has been providing services such as
checking and monitoring the operating status from the service base of the
manufacturer by connecting the machine tool to the network.
As the typical services such as predictive maintenance and maintenancethat are provided mainly to large manufacturers, the machine tool used by
the user is connected to the service base of the manufacturer via themobile phone network or the Internet. The manufacturer collects theoperating status of the machine tool at that time and past log information inremote mode. Based on the collected information, the manufacturer repairs
the tool in remote mode or gives advices to the user. In comparison withthe method where the manufacturer visits the site for verification of thecondition from the service base after receiving the information from user,
the cause of the trouble can be identified and measures can be taken more
quickly. In addition, by utilizing various types of data relating to the
behaviors of the machine tools that have been accumulated by the
manufacturer, signs of troubles can be predicted and predictive measures
can be taken. In this way, more refined measures can be taken. As a result,the user can reduce the downtime of the machining process (standalone
machine) and improve the productivity.
In addition, the operating status of machine tools can be stored digitally as
5data, enabling accumulation and analysis and, beyond the scope oftroubleshooting, operating skills can be checked. . Manufacturers can
extend the services to operation support to users, transforming the service
to a high value added machining process.
If the data relating to the operating status of machine tools has beencollected and organized to the degree that enables the checking in remotemode, the data can also be used for production management of the entire
factory, and management and optimization of the supply chains.
The service for the productivity improvement for machining process as
described above is summarized as the predictive
maintenance/maintenance/operation support service in remote mode.
A variety of forms can be assumed for the procedures of the predictive
maintenance service, maintenance service, and operation support service.
For instance, the following methods can be considered for the operating
status monitoring mode: method that acquires various types of sensing
data on the operating status in remote mode at the frequency close to realtime, method that automatically acquires only the signals on theoccurrence of fixed events such as abnormal termination, which require
countermeasures in remote mode, method that automatically acquires, inremote mode, log information of related sensing data together with theevent at its occurrence, and method where the manufacturer searches andacquires the necessary data in remote mode at the occurrence of an event.
The following maintenance methods are assumed: method where the user
performs maintenance of the machine tool at the installed site, method
where the manufacturer directly takes the necessary measure in remotemode via the Internet if the measure is possible within the range of general
operation procedure or parameters, and method where a fix program iscreated in remote mode and the system version is upgraded by sending
the program to solve the trouble at a program level.
In mere combinations of monitoring of operating status and possible
maintenance procedures, a substantial variety of the combinations can beassumed. While the discussions subsuming such a variety of service forms
as these are intended, there is still an issue regarding significant
6differences depending on the service form such as information security
measures. Therefore, for the design of maintenance procedure,
discussions will be carried out based on the principle under which the user
implements maintenance at the site where the machine tool is installed.
Such a method as this is applied according to the maintenance procedurecurrently requested by the user. Since more diverse forms will become
available as the market expands in the future, other forms will not be
eliminated from the examination targets and will be handled as futureissues to be examined.
(2) Issues faced on the spread of the target services
Although each machine tool manufacturer provides a part of the service
that was described in (1), the service is not necessarily widely accepted byusers. This means a loss of useful opportunities not only for the
manufacturers intending to provide the service, but also the users who will
be able to enhance the machining processes by using the new service.
The following main issues are assumed if the service becomeswidespread..
[1] Apprehension towards the risks attributed to network connection
Many users assume serious risks due to the connection of their information
systems such as machine tools that are used by machining processes with
the network that connects internally and externally. Such risks can belong-term suspension of the production lines caused by malicious hackers
or computer virus infection and malfunctions causing fatal accidents. The
data relating to the operating status of machine tools about machining
processes are considered highly confidential as such data directly indicatesthe performance of the machining processes. Possibilities of serious
economic loss caused by information leakage are often apprehended.
Information network technology is the largest technological factor that
leads to the 4th industrial revolution. Thus, proper management of network
connection is necessary considering the aforementioned risks due to the
network connection as the precondition. Due to the lack of theunderstanding of the service structure based on the network connection as7

the precondition and the absence of the sharing of a definite view on therisk management techniques, many users seem to hesitate to utilize theservice that capitalizes IoT. The handling of information security thatremoves the uneasiness of users is necessary.
[2] Difficulty in providing the service through the machines of different
manufacturers
In general, machines of multiple manufacturers are installed in users’
production sites (production lines). To take the full advantages of theservice based on the network connection as the precondition, it is desirable
to be able to collectively check the behaviors of machine tools of various
manufacturers that configure the production line. Even if the maintenanceservice or predictive maintenance service can be provided by eachmanufacturer individually, there is a limit to the effects of optimization of theentire factory if there are significant differences among the service contents
and the measures for risk management as indicated in [1], and as a result,the merits to users become low.
Currently, no linkage structure is available for manufacturers to collectively
implement the service in a unified manner. For the realization of such astructure, it is necessary to define the coordination area among the
manufacturers such as the quality and volume of data, data linkage
frequency, grading, and communication protocol.
[3] Difficulty in service deployment based on the data accumulation andanalysisCurrently, each manufacturer provides their service within the scope
requested by the user for solving troubles such as troubleshooting for astandalone machine tool and so on by intermittently obtaining data relating
to the operating status or log data. As outlined in (1), one of the services
assumed for realization of smart manufacturing systems is the operation
support for further enhancement of machining process of users by studying
more data in more detail regarding the behaviors of the machines that run
at the users’ sites.
To materialize such a service, it is necessary to organize the concept of8

data such as the agreement on the utilization range of the data relating tomachine tools and organization of responsibilities for data accumulationand management to enable the stakeholders to collaborate widely under
the common recognition. However, such details have not been organized.
[4] Uncertainty of service merits in return on investment
It is difficult for the manager (user) to predict the effects that lead to theinvestment judgment such as other actual services enabled by the
introduction of the service and the effects of these enabled services. Thus,
it is necessary to provide the materials as the guidelines for the
management decision-making process and clearly promote the service thatcan be effectively utilized. In addition, through the implementation of smart
manufacturing, creation and proposal of effective services are necessary.
[5] Shortage of engineers for network and security
Up to now, systems such as machine tools and robots have been
integrated by machine tool manufacturers and line builders. In theimplementation of smart manufacturing, system integration including IT
equipment and network is necessary as well. However, the shortage ofengineers for network and security in the machine tool manufacturers
makes it difficult to provide technical advice to enhance the understandingof the service to the users and remove the uneasiness relating to security
at the proposal of a solution. It is necessary to train engineers for networkand security and create a guideline for clearly explaining the service to theusers by describing the form of the system linkage and specifying thesections for which rules are to be established.

The common points on the issues that were described in 4. (2) can besummarized as the absence of the common recognition regarding thebasic characteristics of the service that utilizes network and data and theabsence of rules specific to the service. As the preconditions of actions toverify and solve these issues, a service information model is presented as
described in 5. (1). Based on the information model, verification of the formof linkage and integration with other systems, sections that are to be
standardized such as interfaces, and sections for which rules are to be9

established such as security and data control entities are to be identified
and organized.

5. Information modeling associated with remote maintenance service,
predictive maintenance service, and production management service(1) Organization of information modeling for machine tools
The function for monitoring the states ”Mieruka(visualization)" of themachine tools that form the production line is an valuable factor to apply
remote maintenance and predictive maintenance services. In particular, torealize ”Mieruka" of various machine tools manufactured by different
providers with same manner, it is important to clarify their hardware
configurations and internal statuses and to be prepare for information
models for designing and implementing the information system of
productive activities. Machine tools that configure the current productionlines vary in the structures and dynamic behaviors according to themachining spindles and number of pivots of the machining table,
installation location, and the drive mode of each axis. These differences
make it difficult to define a common model that indicates all the functions.
Even if a common model for the current machine tools is defined andmachine tools are designed and manufactured based on the model, itmeans that a model is determined for machine tools corresponding to the
future manufacturing of all the products, impairing the development ofmachine tools.
However, for the users of a production line with multiple machine tools,"Mieruka" of the entire production line at the uniform level is also importantin terms of production management. Therefore, we attempt to createmodels that enable the recognition of the hardware configurations andmachine operating status of the target machine tools at a uniform level. In
this project, models were created in terms of the block definition diagram(static structure) and the state machine diagram (dynamic structure) of an
NC cutting machine based on the information collected from machine tool
manufacturers.

10[Block definition diagram of an NC cutting machine]
Hardware configurations of NC cutting machines vary depending on the
degree of operation freedom of the machining equipment and the numberof tool units. The basic configuration comprises the "CNC unit (referred toas "NC" in the diagram) that controls the machining equipment, the “PLCunit” (referred to as “PLC” in the diagram) that controls the sensors and theauxiliary tool units, the "industrial PC (referred to as "IPC" in the diagram)"that functions as the user interface and the network interface with the officefloor, and the "machining unit" (referred to as “Motor” and “Cutting tool unit”
in the diagram). The block definition diagram in Figure 5.1 shows therelationship among these components.
When sensor information within the NC cutting machine is distributed to theInternet (EtherNet), the information is transmitted to the Internet by using
the industrial PC that functions as the gateway of the information and thebus-connected PLC unit as the source of the information. The otherdevices of the production line that are connected to the field network(FA-Net) are controlled via the PLC unit only. Regarding the common
issues such as the securement of operation safety of the production line,
the model help to examine the problem such as how the information
system that distributes information to the Internet and the control systemthat controls the production line can co-exist without any problem. Suchmodeling also clarifies the control information at operation of each machine
tool that forms the production line, design information, the sections that
handle sensor information, and the connection relationship/access range.
This is effective for identification of failure factors at the occurrence ofmachine failures, impact relationship with other machines, and designing of
the information system that handles the relationship between various typesof information and the interfaces.

11Machine tool block definition
diagram: NC Cutting machine: Sensor: Auxiliary
tool unit: Motor: Cutting tool unit

Figure 5.1 Block definition diagram of an NC cutting machine[State machine diagram at normal operation of an NC cutting machine]
By using the block definition diagram of an NC cutting machine showing in
Figure 5.1, the relationship among the internal units of the NC cutting
machine, various functions, and information that is handled can be
described. However, since the information generation at NC cutting
machine operation and the flow are not described, the information is not
sufficient for developing an information system for "Mieruka" of the statusesof NC cutting machines. Therefore, we modeled an inside state transition ofan NC cutting machine at normal operation as the state machine diagram.
For the state machine diagram at NC cutting machine operation also, thedetails vary depending on the functions of each machine and configurationof internal units in the same way as the block definition diagram that is
described above. As a result of the information collected from the
manufacturers, the common state machine diagram can be presented asshown in Figure 5.2.
The status transition indicated here refers to the flow of operation and thetiming of status transition when an NC cutting machine is operated in a
12

factory.
An NC cutting machine often has multiple machining preparation states forprevention of accidents during machining operation, requested accuracy of
products (machining targets), and preparation of peripheral devices andauxiliary devices of the working machines. To realize "Mieruka" ofproduction at the factory configured by multiple machine tools, production
line, and production cell, design and installation of an information system atthe level that commands the entire operation are necessary. Modeling ofcommon sections as this are effective for its realization. If detailed models(individual models) corresponding to individual machine tools can beprovided by the manufacturers, an information system capable of "Mieruka"
of various levels can be easily designed and installed by combining
common model and individual models. By presenting the operation of eachworking machine as a common model, an important guiding principle canbe made available for standardization of manufacturer’s specific ID thatindicates warning information and failure information.
Machine tool statustransition

Power supply
ON

Initial state(excitation OFF
state)

Machining
completed
Unrecoverable

Power supply
OFF

Setup

Machining preparation
state(Excitation ON, manual
operation ON mode)

Machining
preparation error

Machining
completedErroroccurred
Machining operation
state (Automatic
operating state)

Error state

Figure 5.2 State machine diagram at NC cutting machine operation13

(2) Organization of information modeling for the target services[1] Modeling maintenance service
Important points for realization of high-efficiency production activities byenhancing the existing production technology by introducing IoT formachine tools are minimization of down time due to various failures in theexisting production line and elimination of waste such as occurrence of
manufacturing defects. Efficiency improvement and enhancement ofmaintenance work of machine tools that comprise the production line are
one of the important techniques for the elimination of waste.
Currently, in many factories, maintenance work of production lines iscarried out in various methods. However, most of the "Kaizen" ofmaintenance work are individually handled based on the tacit knowledge ofthe operators (production engineers of the factory and site administrators).
"Kaizen" of production activities through individual handling based on thetacit knowledge as the core will soon reach the limit due to the bottleneck
attributed to human resources. It is difficult to utilize advanced systems andtechnologies such as machine tools equipped with IoT technologies,
various information system, and AI technologies.
For the maintenance work in the current production sites to overcome such
limit and continue to evolve by introducing IoT and AI, the conditions that
require human intervention for various maintenance work must be changed.
Initially, it is important to clarify a current maintenance work by modeling.
Therefore, modeling of maintenance work at the current production sites
was attempted by collecting information from machine tool manufacturers
and users of production lines.
Figure 5.3 shows the block definition diagram relating to maintenance work.
This model shows that there are delay of dissemination, underdevelopmentof the technologies, and ambiguous relationship between maintenancework and workers (persons in charge in users and manufacturers) inremote/preventative maintenance.

14

Maintenance activities

Routineinspection

Maintenanceactivities

Predictive
maintenance

Daily inspection
Predictive
items
maintenance basedon the sensor data

Regularinspection

Regularinspection
items

Predictive
maintenancebased on thequality data of the
products

Maintenancebased on theutilization volume

Handling
unexpected
event

Remotemaintenance

Alert

Maintenancebased on theutilization volume

MinorfailureSerious
failurePerson incharge ofmaintenance

Person incharge of user

Worker

Maintenancestaff

Person incharge ofmanufacturer

Telephoneservice

MaintenanceworkerFigure 5.3 Block definition diagram of maintenance work at current factories

Maintenance priority items in the current production line vary depending on
the product and production system. For instance, in case of single breed
mass production/small lot production of many products in 24-hour systemsuch as factories in the automobile industry, it is most important for
maintenance work to realize of the zero downtime maintenance. On thecontrary, in the make-to-order mode that is applied in production lines ofinfrastructure facilities as units that form a large power generation system,
maintenance work is performed to prevent a failure of machine tools or
product failure during the production period. Most of the factories in large
companies have the sections that can implement most maintenance andrepair without the need for the support of each manufacturer regardless ofthe particular machine as long as the machine tool forms the production
line. On the other hand, small to medium companies cannot afford to havesuch sections.

15

In creating the information model, we believe that it is necessary to classify
into two viewpoints, "viewpoint on the presence/absence of the section ofmaintenance work" and "viewpoint of the production system (massproduction, small lot production of many products, and make-to-orderproduction)". In addition, we need to create individual models and analyze
the requirements while noting the clear indication of the contents ofmaintenance work and functions that require human interventions.

[2] Modeling remote maintenance and predictive maintenance services
While referencing the information models that indicate the current
maintenance work as described above in [1], we attempt to model both
remote and predictive maintenance systems that are currently realized byrelated companies.
[Remote maintenance system]
Currently, Internet connection via cabled or wireless LAN is seldom
introduced in factories due to the reason of inadequate information security
measures. Therefore, for most of the machine tools that support remote
maintenance, the maintenance service is implemented by using the public
line network through the mobile phone network dedicated to data
communication. Figure 5.4 shows the typical block definition diagram of theremote maintenance system that is currently implemented by machine tool
manufacturers.
Since there are problems in terms of the capacity restriction andcommunication cost of communication lines under the current remote
maintenance service, data monitoring in real time through constantconnection is difficult. Therefore, information on the operation time in themachining process by machine tools and information obtained from internalsensors are stored in the storage unit that is installed inside of the machine
tools such as hard disks and the data is regularly uploaded to the databasethat is managed by the manufacturer. Normally, when an alarm is issued
due to the occurrence of a fault, relating information such as the alarm typeis automatically transmitted to the manufacturer and the manufacturer
16performs the initial analysis of the faulty section corresponding to the alarmby using the data such as the operation history that is uploaded regularly.
In this case, the data such as operation history that has been accumulated
in the server regularly is often used only for the initial analysis of the faulty
section at the occurrence of an alarm. This is because information such asmachine tool operation history is the production engineering expertise itself
for users as mentioned in 4.(2). This hinders the deployment of services ofmachine tool manufacturers, where "a large volume of data is collectedfrom various users, and is analyzed and high-value added remote services
are developed by using the analysis results". However, in fact, theoperation data that is accumulated handles the movements of machine
tools only as has been clarified by this modeling and it is impossible torestore the entire machining process by the data only. Even if the dataacquired for remote maintenance is leaked, the risk for the leakage tocause the flow-out of the production technology of the user is low.
The modeling of the system is effective for clarifying the sections wherefaults are likely to occur by a new service as remote maintenance. It is also
effective for assessing the risks by the introduction of a new technology.
Therefore, in popularization of IoT equipment and improvement of theInternet environment within factories in the future, the model of remote
maintenance system can be useful to realize a service expansion withadequate security measures by updating it with the change of theconfiguration.

17

Remotemaintenance

Remote maintenancesystemMachine tool

Mobile phone line

Safe data
communicationby leased line

Machiningequipment

Saving operation
history

Remote operation
terminal(manufacturer)

Storage

Database(manufacturer)

Remote accessafter the agreementwith the user

Regularuploading of alert
information

Mobile communication
unit

Operation history
data

Figure 5.4 Block definition diagram of the remote maintenance system

18

[Predictive maintenance system]
Predictive maintenance can be said that it is conservation activities toachieve efficient operation of the production line by predicting failures ofthe machine tools configured the production line by using various
information of their inside or outside sensors. Under the present condition,
the technology for measuring the correlation between the sensor dataassociated with such predictive maintenance and defects is being
developed and the predictive maintenance service for machine tools is
restricted to the limited function units only. In this section, modeling was
implemented as the block definition diagram of the system configuration(Figure 5.5) relating to the predictive maintenance system that is currently
tackled by each manufacturer by assuming multiple machine tools basedon the results of interviews.
Figure 5.5 shows the configuration of the predictive maintenance system inthe production line configured by multiple machine tools. This model isbased on the factory where conditions surrounding the production line canbe measured by external environment sensors and so on. Regarding
predictive maintenance, more accurate signs can be detected by using thedata on the environment where machine tools are used, as well as sensors
of stand-alone machine tools. For foretaste detection, machine tool
installation locations and data that indicates shapes and materials of
metals may be useful and the data accumulated relating to production lines
including such data can be used as the user-specific production technology
or expertise. Therefore, when compared with remote maintenance, asystem must be configured considering the risks of information security. In
the model that is shown in this document, the use of the database of the
production site and the cloud system is assumed. Classification andranking of the types of the information to be uploaded to the cloud system
is found to be effective in information security risk assessment.
For the predictive maintenance system also, the service provider and theuser can have common recognition more easily through the priordeliberations on the risks and the countermeasures for the service that is tobe created in the future by modeling the entire factory including theexternal systems,

19

Predictive
maintenancePredictive
maintenance system

Cloud system

Base

Database

Operation
data

Environment
data

Production
line

Operation
data

TransportmachineMachine tool

Assessment/prediction
systemEnvironment
data

Environment
sensorCamera Barometer

Hygrometer

Thermometer

MachiningdeviceFigure 5.5 Block definition diagram of a predictive maintenance system20

6. Draft of the guidelines for the deployment of the target services extracted
from the information model(1) The guidelines/interfaces relating to the definitions of the basic states ofmachine tools and methods for extracting information on the states
The machine tool information model has been discussed in Section 5. (1)[1]. The state machine diagram of Figure 5.2 presents the sufficient state
definitions for comprehensively checking the operation status of the
production line or the entire factory for the user that operates the
production line, detecting any defects of the production line, andimplementing maintenance activities. As the basic states of machine tools,
the following four states can be defined.
[1] Initial state
The machine tool is set to this state immediately after the power is turnedon and before the machine is stopped safely after termination of machining.
Since termination of the power supply due to an error or some other defectmay cause some fault in the machine tool, the machine tool must be
returned to this state for normal termination of the power supply.
[2] Machining preparation state
The machine tool is set to the machining preparation state to shift to themachining operation state and this state can be subdivided to multiple
states such as the warmup state at machine tool replacement for
maintaining machining precision and preparation state for automated setup.
The machine is to return to this state at the returning to the normal statefrom the error state that is set due to the alarm that is occurred during themachining operation. When the machine cannot be returned to the normal
state (machining enabled state) from this state, the machine is to be
stopped as an unrecoverable error and is to be set to the mode that
requires maintenance.

21[3] Machining operation state
In this state, the machine is processing a work after normal completion of
setup and the machine is set to this state from the machining preparation
state. When an alarm is occurred during machine tool operation, themachine is set to an error state.
[4] Error state
The machine is set to this state from the machine operation state when awarning or fault alarm is occurred during machine operation. To return themachine to the power supply disconnected state or machining state, themachine must be set to the machining preparation state.
Since these basic states of machine tools are defined for improving theefficiency of production management through "Mieruka" of the operatingstate of the entire factory or the production line, the states need to be
notified to the information system that performs production management
via the internal IPC. Currently the information acquisition specifications in
the NC and PLC that form a machine tool vary according to the
manufacturer. Therefore, to acquire the information on the state of amachine tool, IPC acquires the state of the machine in the production line
through the interface (API: Application Programing Interface) according to
the manufacturer of the NC and PLC and the external information system
acquires the information of the state of each machine through IPC. Since a
specific interface is defined for each machine tool manufacturer and the
production line control system must be constructed according to theinterface, it may be necessary to reinstall the production line control system
whenever the production facility is updated.
To realize a "smart factory" for the total optimization of the supply chainsand engineering chains, and construction of an efficient platform andimprovements of production efficiencies of various machine tools, thenecessary information should be able to be acquired by applying the open
platform technology as much as possible to reduce the adjustment costs
associated with differences among the manufacturers.
Based on such a concept as this, standardization is planned for the22

following two interfaces for the acquisition of machine tool states and otherinformation.

[Interface among NC, PLC, and IPC]
In the conventional method, API specific to the manufacturer is used for
acquiring information from NC and PLC that control the jigs of machine
tools and peripheral auxiliary tool units. This causes an extra development
load to the manufacturer of the machine tools and consequently, lessconvenient for the users of machine tools. Therefore, an open standard
specification is applied in principle for acquisition of the information thatsatisfy the configuration that is expressed in the shared model. Specifically,an interface that complies with the MT-Connect Standard, which is
becoming a de facto standard or the Dejure Standard such as ORiN is
recommended.

[Interface between IPC and an external information system]
The target of control for machine tool users is the production line, notindividual machine tools. The approach for improving the production
efficiency by monitoring the operating state of the production line from theoffice or an external base is developing. Therefore, the interface for linking
the information system that completely grasps the state of the production
line including the behaviors of individual machine tools with the external
information system that performs production control is important. Currently,
installation of API specific to each manufacturer is necessary, requiring
major reconstruction whenever the facility is updated. To avoid such a load,
the use of the common interface including the linkage function section with
MES and ERP is recommended. For the common interface, middlewarethat complies with the international standard such as ISO20242 can beassumed as the future global open strategy.

(2) Basic concept relating to information security measures at connection ofmachine tools with the Internet
23-Technical background
For a long time, manufacturers have assumed that devices in the factory
are to be connected to a closed-area network that does not involve in any
way with external networks such as the Internet. Consequently, manyfactory devices available today became significantly “insecure” whencompared to the devices used in the other field, and many security
vulnerabilities of PLC and other factory devices are reported publicly.
Further worse, today’s closed-area network is not really “closed” inpractice; there is so many possible intrusion paths available for security
attackers, and is becoming a major risks to the real systems. Many real
successful invasions are reported, such as destruction of factoryequipment and loss of control/explosion in factories. Under thesecircumstances, there seems to be great difficulty of applying the concepts
on IoT and big-data application via Internet to the current factory-area
network.
In the area of control systems (such as critical infrastructure systems),
separation between the control system network and information system
network/external Internet using multi-level firewall configurations has
already been exercised (Figure 6.1). In these configurations, the machinesconnected to (or “bridges between”) two or more network is the critical pointof the network security. We cannot avoid such machines to exist, since
information distribution is necessary among the different layers in suchconfigurations. In addition, from the view point of security,commonly-used USB storage media used for the distribution of informationsuch as design data from the information network to the control network,
can also be regarded as "devices that are connected to two or more
networks" in a broad sense. When a malware (computer virus) infects a
device connecting two or more networks, it can infect into the control
network and the many insecure devices in the control network (including
PCs without proper security updates applied) fall into a serious condition(Figure 6.2).

24

Small control system(mainly control of a production line in a factory)

Large control system(mainly process control of power, gas, and chemical)
Internet
OA terminal

Factory management(production control)

Production line
control/monitoring
control

OfficeInformation
systemInformation network

Controlsystem(DCS)

Log server

Monitoring
control
serverInformation control network
MonitorMaintenanceroom/
servercomputer(engineering
workstation)
room
Control network

Controller/PLC
Site
Sensoractuator,
etc.

Field network

Figure 6.1 Example of conceptual configuraiton of the control system including
factories(Source: page 15, "Security risk of control systems as a serious management
issue", by Information-tecnology Promotion Agency Japan; translated byauthors)

Internet

OA terminal

Information
systemInfectedthroughstandard mail,etc.

Controlsystem(DCS)

OfficeInformation network

Log server

Information control network

Transmit via USB
memory at thesame time as
settings, etc.

Monitoring
control
server

Maintenanceserver(engineering
workstation)

Monitorroom/
computerroom

Control network
Attack the system
inside FW
Controller/PLC

Site

Sensoractuator,
etc.

Field network

Figure 6.2 Example of the route of malware infection bypassing the firewall(Source: the same as Figure 6.1, with alternation by authors)

25

On the other hand, many manufacturers are providing an optional
communication module that connects a machine in the factory to the
manufacturers’ network directly, through an externally provided network
services (such as 3G/4G mobile phone networks) (Figure 6.3). The
possible reasons for using such a “bypassing” feature are twofold: forsmall-scale users it is not always realistic to prepare a network
environment specifically to applications for the 4th industrial revolution; forlarger entities, it is not practical to reconfigure the already-existingclosed-area control network to allow external communications for remote
maintenance purpose. Such connection becomes more and more practicalunder the current trend of low-cost wireless communication environment.
From the viewpoint of the network security, only if such external connectionis the only connection to the machine (and when the manufacturer isabsolutely trusted), it is a practical solution. However, if a local-area IP
network is existing, or it is to be installed in the near future, the solution isquite unacceptable, because all of such devices will become "the machine
connected to two or more networks" as described above (Figure 6.4),
causing a vulnerable situation. In particular, the presence of multiple
external connections under differently administrations is a serious situation
for network management and operation. If devices inevitably need toaccommodate both the in-house and external connections, suchconnections must be completely controlled by the firewall managed by thefactory and an unnecessary increase of the number of connection points
must be strictly avoided.

Manufacturer X

Manufacturer Y

Mobile phone
network, etc.

MachineA

MachineB

MachineC

Figure 6.3 Direct connection via the mobile phone network, etc.

26

Virus Infection
on service side Manufacturer X

Manufacturer Y

Mobile phone
network, etc.
Virustransmission,
serving as
multi-network
deviceMachineA

MachineB

FirewallIn-house LAN
Available virus
infection route
bypassing the FW

Direct attack from external
network is prevented by thefactory-managed firewall

MachineC

Internet

Control
device, etc.

Figure 6.4: Risk of possible virus intrusion caused by the dual connection of themobile phone network and in-house LAN

Considering the perspective and the current situation indicated above, forthe time being, we propose that the security model for the remote
maintenance services for industrial machineries shall be examined as two
separate use cases: whether in-factory inter-device communication isrequired or not.
As the first case, if in-house inter-device communication is not required, we
can consider the use of the direct logical connection of machines to the
network on the manufacturer side by using dedicated connection such as amobile phone network. In this case, such machines should be considered
as belonging to the manufacturer’s network in terms of the information
security, regardless of the actual ownership and the installation location.
We show the two example configurations of the use case, "standalone
device connection case," and "simple connection configuration case using
VPN.”
In contrast, if inter-device communication within in-house LAN is required,
we propose that we should focus and invest to the design and constructionof the properly managed, externally connected in-house network, including
the development of required technologies. We summarizes this use caseas an "in-house LAN case" and examines some specific requirements forsecurity measures.

27

In any case, security protection of devices is considered strictly essential
today, even in the closed and stand-alone environments. The security
measures independent of the connection figuration will be summarized
separately as the information management system.
-

Examples of use cases[Standalone device connection case]This use case involves direct connection of in-factory devices to the
manufacturer’s network using external network services (such as 3G/4G
mobile phone network). The case assumes that 1) there is no in-house
information exchange with other systems through LAN, USB storage
device etc., and 2) security violation risks from the manufacturer’s side canbe ignored (the factory side decides to trust the security management of
the manufacturer). In this case, the machine connected to the
manufacturer system must be considered as belonging to the
manufacturer’s network. Factory-side users should verify the following
points as security assessment.

[1] The machine that is connected to the manufacturer’s system must not be
connected to the in-house LAN in principle (Figure 6.4).
[2] When any data is exchanged between the machine and the factory-side
computer system using a USB storage etc., such a carrier device must be
considered as one outside of the factory environment. For example,
virus checking should be performed each time it is used.
In addition, it is important to verify that the connection network(communication network service) satisfies the following criteria.
(a) The connection network must be isolated from the Internet.
(b) The manufacturer-side systems that accommodate the connection
network must either disconnected from the Internet, or have its security
strictly managed and protected as if it were the critical factory-side
infrastructure.
(c) If either the connection network or the manufacturer-side network
accommodates multiple devices, direct communication between
28

devices should be isolated; at least, devices from different factories ordifferent sections/lines must not be able to communicate to each other.
(d) The devices from different factories must be network-separated on the
logical link layer (Layer 2) or below. If necessary, a virtual network(VLAN) must be used.
(e) The communication network should provide protection against
tampering/eavesdropping of the traffic. If such function is not provided
as a network service, alternatively, the device manufacturer must
implement the encryption and mutual authentication between the device
and system, using the widely accepted standard technologies.
The use of the “public network” services without the dedicatedcommunication control/separation functionality is not recommended within
this use case. If such connection is to be used, we recommend to
consider the network connection as the public Internet, and to takeadequate security measures as provided in the “simple connection use
case using VPN” below.

[Simple connection case using VPN]
If in-house LAN is to be used as a communication channel to the
manufacturer’s network, but the full-brown control system network (asshown in Figure 6.1) has not been deployed, we may consider some
simplified configuration. This use case requires slightly more management
cost compared to the previous use case, and it still does not support
inter-device linkage within the factory well. However, it can be considered,
for today’s small-scale deployments, as an intermediate, transitional step tothe future full-scale controlled environment supporting full use cases.

29

MachineA

MachineB

MachineC

VPN device

VPN device

Securecommunication
moduleIn-house LAN

Network with device
separation control

FirewallManufacturer X

Manufacturer Y

VPN device

VPN device

Internet

Figure 6.5 Communication control by combination of VPN and communication
control switch

In detail, this case uses the virtual private network (VPN) functionality torealize the functionality of the dedicated network on the Internet (Figure6.5). In terms of security, it does not rely on the security of the in-housenetwork compared to the Internet, still it provides virtually the same level of
security to individual devices, compared to the previous “dedicated network”
case. However, since the VPN device is itself a high-risk device due to its
vulnerability caused from complex functionality, cautions are necessary.
To mitigate this risk, we propose to introduce additional security control to
the network level in this use case.
In detail, this use case requires the same cautions and provisions as the“standalone device connection case” above. In addition to that, thefollowing settings are deployed on VPN devices and network equipment.

(a) In VPN devices on both ends, the whole traffic from the internal side istransferred to the virtual network and not to the in-house LAN.
(Cautions are required when generic-purpose VPN devices are used,because the VPN client devices usually forward general traffic to thein-house LAN by default). All incoming traffic from in-house LAN are
discarded (except the traffic for the VPN communication itself).
(b) Strict management is required for mutual authentication andencryptions of VPN devices.
(c) The manufacturer (possibly with other third-parties), should provide
30

up-to-date management on the vulnerabilities of VPN devices andothers.
(d) Network switches should be configured so that only the communication
between each VPN device and the external firewall is permitted. Directcommunication between devices is discarded by default (Figure 6.6).
(e) Firewall is configure to allow the outbound communication from thein-house LAN to the Internet only, and incoming communication fromthe Internet is discarded (technically, except the responses to theoutgoing communication) (Figure 6.6). This means that VPN
connection is to be established from the factory side. If possible,
configurations will only allow individual communications from thein-house VPN devices to the manufacturer’s counterpart.

MachineA

MachineB

MachineC

VPN device

VPN device

Securecommunication
moduleIn-house LAN

Network withfunction control

Fire Wall

Internet

Figure 6.6 Setting of enabling/disabling communication by a communication
control switch and so on

The switches that perform such control is available from many vendors,
primarily designed for separation of customers in the shared network suchas in a residential complex. Many wireless LAN devices are also equippedwith such a separation function in the infrastructure mode.
Actual deployment of this case can have some variations; one base case is
to use separate VPN device (machine A in the diagram). VPN facility canalso be integrated with the equipment as a part of the communication
module of the equipment (machine B). Furthermore, full VPN facility can be
replaced by some simple, secure, dedicated communication protocol(machine C).
Management of the VPN devices in this use case is better served by the31manufacture’s side for two reasons; it should be configured tightly related
to the manufacture’s counterpart; and also it is infeasible to perform
management operations (b) and (c) described above by the client side.
Such maintenance operations may be included to the (possibly paid)
maintenance service provided by the manufacturer. On the opposite, themanagement of in-house LAN and the firewall should be performed on theclient side, as a measure for the self-management of the factory security.

[In-house LAN connection method]
If a full-scale inter-device communication within the factory is required, it isnecessary to manage both external and internal communication at the local
network level. Without that, we cannot restrict the external security borderof the in-factory network to the single point of management.
Consequently, the network configuration becomes similar to those shownin Figure 6.1, and the all external communications pass through thefactory’s single external connection point.
One of the most major risks for such configuration is that the infection of
every single device within the LAN affects broadly many other (possibly
vulnerable) devices within the same LAN. Leakage of internal information
abusing the permitted route of communication for external services is alsoa major risk. To mitigate or reduce such risks, it is desirable to control as
detailed as possible the permission of both external communications toservices and internal communication between devices. At the same time,
if complicated network operation such as VLAN is employed, it will impose
both high costs and high risks of operation errors even if professional
engineers are involved. To solve such problems, the following measures
should be examined. Unfortunately, some of measures suggested herecannot be implemented easily today, due to the high cost of implementationand management. We propose to develop such technologies/productssoon to reduce the operation cost and make it realistic.

(a) To prevent device spoofing, describe and manage all connections of the
in-house devices to the network at the physical level or logical level, e.g.
which device is connected to which connection port and which IP
32

address is used for communication. It can be achieved, for example,
by the use of individual encryption keys or the use of WPA2-Enterprisein the wireless LAN. For wired LAN, the use of fixed IP addresses
along with the ARP and IP filter setting in physical port level on switches
can be used (Layer 2 configuration). Alternative method is to separate
each wired devices to the individual logical network by using the L3
switch or VLAN (Layer 3 configuration).
(b) Manage and control the all mutual communication among the in-house
devices and communication between local devices and the Internet.
Such control should be employed by the communication type andprotocol level. Assuming the provisions described in (a), it can berealized by using packet filtering on the switch in the Layer 2
configuration and by setting IP filter of the L3 switch or the router in theLayer 3 configuration.
(c) Above managements should put into the central control at the factory or
manufacturing line level. Information Management Chief of thefactory/line should be able to comprehensively check the configuration
status of all the devices.
(d) Operational management must be provided to monitor the state of theunpermitted communication in (b) and decide whether to update therules or to isolate the malfunctioning devices.
(e) For any externally outgoing traffics, take appropriate traffic-securing
measures such as encryption for protection from eavesdropping andinterferences. The technologies used for such securing should be thegeneral-purpose ones that has been widely used and verified for thecommunication via the Internet. As the examples, authentication using
the TLS server certificate and client certificate or establishment of VPN
communication such as L2TP can be considered. Whenever possible,
it is desirable to have an end-to-end encryption between the devices
and the external servers. However, if the communication have to be
relayed by some internal management systems, end-to-end encryption
must be applied to the communication between the device and the relay
system and the relay system and the external system, respectively. If
encryption is not applied in the terminal devices side, take enoughmeasures (such as (a) and (b)) so that the communication is notaffected in the IP network before encryption is applied.
33

As a partial measure compared to the full-featured method above, having aseparate local network for each device manufacturer may mitigate somerisks influenced by the mixture of different security management by someextent. However, as long as logical network is shared at least partially, or
as long as having a device that connects two or more logical networks, weconsider that the above-mentioned measures will be required in the near
future.
-Information security management establishment on the factories andmanufacturers
In the above use cases, fundamental requirements for the information
security management of these systems are similar to that of theclosed-network control systems (for instance, IEC 62443-2-1 CSMS for
IACS). Additionally, these systems need more strict management for therisks of vulnerabilities and intrusion incidents, as existence of allowed
external communications raises the risks of the security intrusion andinformation leakage.
Depending of the system designs described earlier in this section, theentity that should primarily manage the information security of thesesystems will vary. The basic principle is that the entity who holds actual
control of the information flow should take the primary role on theinformation security management. In the first “direct connection use case,”
the manufacturers (service providers) must take the primary role, since
only the manufacturers’ system engages the primarily control of thedevices communications. In this case, the terminal device on the
manufacturers’ side that is connected to the factory-side machine shouldbe thought as “a part of factory networks that have been extended to the
distant manufacturer’s facility", and the manufacturer’s side network should
be conceptually considered as the network of a virtual factory with multiple
independent lines (corresponding to multiple customers). Existing
guidelines for the control systems should be applied, after appropriately
modified based on this virtual aspect of view. Of course, the fundamental
diversity between the actual owner of the machines and the manager of theinformation systems should be carefully understood, and both customers
34and manufacturers must have tight communications with each otherregarding security policies, risks and countermeasures. The second“simple connection use cases using VPN” can also be considered in thesame manner, at least in this moment.
Oppositely, in the “In-house network use case,” the factory side shouldtake the primary role of control, and the information flow from factorymachines to the manufacturer’s network shall be considered as data
provision to the external entity with a different security management
policies. These external communications should be put under strict andcareful management.
In any cases, users and manufacturers should have adequate sharing of
information on the contents of communications and its security risks. To
enable the factory-side managers to employ reliable management on theirinformation property, it is desirable for the manufacturers to provide thefollowing information to the factory-side in a systematically organized ways.

 Detailed information of communication required for each device tooperate as an information device:
Such information includes the following: communication destinations andtraffic volume to occur under normal operation, and those relating to alertsthat occur at error/abnormal states; the communication destinations andits volumes required to perform software updates, and so on. Without
those information, local communication control policy will become either
unnecessarily tolerant or inappropriately tightened, causing either failed
detection of malware behavior or interference of alert transmissions.
 Guaranteed/agreed provision period for the maintenance of third-party
software platform (operating systems etc.) used in the devices, procedure
for applying security updates, and manufacturers’ provision period for
security vulnerabilities handling of their products:
In these days, almost all OS and software cannot be used securely
without proper maintenance updates. Accurate information on the
period of software maintenance provisions, along with the cost requiredon such provisions, must be shared between customers and providers, toprevent old devices without being maintained from being used continually
without proper maintenance. In other words, “when the old devices
35become unuseful” should be mutually understood and agreed.

(3) Guideline for access control for digital data generated by machine tools
The information security measures described in (2) are those for preventing
unexpected situations for the parties concerned. The guideline of access
control for digital data described in (3) is the summary of "(should be)
expected state" for the parties concerned.
For instance, machine tool users can easily assume that information
relating to machine tools is supplied to the service provider to some extent.
However, it is rare that common understanding regarding the use of digital
data and management state (e.g., “which digital data is used in what way
under whose management" and "how related digital data is processed after
the immediate objective has been accomplished”) are established by theuser and the service provider. Focusing on such an aspect of digital data
management as the background for users, particularly machine tool users
become cautious about sharing of digital data under the environment
connected to the Internet, the guideline summarizes a means to thedevelopment of common understanding by the parties concerned.
In this case, even if the contents are restricted to the service such as
maintenance management assumed in this implementation, the contents
vary according to the original idea of the provider so that a caution isnecessary in terms its strong nature as the competitive area. Since themanner of using digital data also varies depending on the service contents,
it is necessary to allow such diverse ways and foster innovation inorganizing the commonly understood items relating to access control for
digital data.
Based on such problems involved, the actual concepts are summarized asfollows.
[1] Principle(a) Parties concerned must have the clear common recognition on thedigital data handled in terms of following aspects.
 Range of the digital data that is handled36 Purpose of using the digital data that is handled Collection, storage, processing, and disposal methods of the digital
data that is handled Range of the persons who can collect, store, process, anddisposed of the digital data that is handled Range of the persons who can access the digital data that ishandled(b) The digital data that is handled must be collected within the necessary
and adequate range for the use purpose.
(c) For the new knowledge obtained as a result of processing the digital
data that is handled, the guideline must be clarified in advance among
the parties concerned, under the principle that such knowledge isattributed to the person engaged in the processing.
[2] General summary of the remote maintenance and predictive maintenanceservices
For the contents described in the principle of [1], it is desirable to maintaincertain rules among the parties concerned through a contract and so on
within the necessary range according to the individual services.
Ultimately, various handlings must be permitted based on the agreement
among the parties concerned. However, when the main service is based on
the use of the open network such as the Internet as the precondition, therange of the parties concerned becomes wide in both the service providers
and the service receivers, and consequently, related parties may not beable to be specified in advance. Therefore, regarding the typical service
type, topical concepts are summarized and the result is utilized for thesmooth agreement for individual services.
[Handling of digital data relating to the remote maintenance service]
As shown in the block definition diagram for maintenance work in Figure
5.3, remote maintenance is one of the measures taken for unexpected
events. In the main service of the current remote maintenance is
identification of the cause of the fault and maintenance parts to be replacedby referencing the histories at the occurrence of a fault in the machine tool.
The handling of digital data can be summarized as follows based on the37block definition diagram of the remote maintenance system that is shown in
Figure 5.4.
 Range of digital data:• Operation information of the machine tool for a certain period up to
the occurrence of a fault (Information of sensors installed in themachine tool and alarm information, excluding the manufacturing
program and information on work regarding the product••manufacturing by the user)
Operation history of the worker (operations of power
supply/operation switches, operations of auxiliary tool units, etc.)
Past maintenance record for a certain period of time Use purpose of the digital data:
To resolve the fault of the machine tool, recover the machine tool toenable normal operation, and identify the relationship between the fault
and maintenance parts
 Collection, storing, processing, and disposal methods of the digital
data:
Operation information of machine tools and operation history ofworkers are collected from the sensors installed in the machine and arestored in the machine tool or the server maintained by the
manufacturer based on the remote maintenance contract, which isconcluded between the user and manufacturer. In principle, pastmaintenance record refer to the records of the maintenance work
performed by the manufacturer and when the user implements
maintenance work individually, the record is collected and stored in theserver maintained by the manufacturer based on the remote
maintenance contract.
The digital data described above is processed only by the computerwith adequate security measures and is disposed when the fault is
resolved, the relationship between the cause of the fault and theoperation history is clarified, or based on the remote maintenancecontract.

38 Range of the persons who can collect, store, process, and disposed ofthe digital data:
Digital data can be handled only by the production manager in the userside, person in charge of maintenance and person responsible in the
manufacturer side, and persons designated in the remote maintenancecontract.
 Range of the persons who can access the data:
In principle, access to digital data is restricted to only those who cancollect, store, process, and disposed of the data.
[Handling of digital data relating to the predictive maintenance service]
As shown in the block definition diagram of maintenance work in Figure 5.3,
the predictive maintenance service is to inspect data at a certain cycle inthe same way as regular inspection and daily inspection and notify thesections to be repaired in advance. Currently, the service used for
detection of the foretaste of the fault in the part that causes the stopping(alarm stop) of the production line for a long period of time. Access controlof the data that is handled can be summarized as follows.

 Range of the digital data:• Maintenance and replacement records of the parts that cause
alarms• Operation information (insulation resistance, spot welding pressure,
chip wearing degree, voltage and current of arc welding, etc.)• A reasoning model for the termination of alarms (a model thatcauses alarm stop) Purpose of using the digital data:
Detection of abnormality prior to the alarm stop of machine tool Collection, saving, processing, and disposal methods of the data:
During the operation of a machine tool, operation information iscollected from the sensor that is installed in the machine and is stored
in the server maintained by the user or manufacturer. Past
39

maintenance records (e.g., part replacement records) are collectedfrom maintenance records of the user based on the predictive
maintenance contract and is stored in the same server as for theoperation information. A reasoning model is generated and managed
by the manufacturer that provides the predictive maintenance, and isstored in the server that performs detection tasks. Digital data aretransmitted to the server that performs detection tasks, processed, anddisposed of.
 Range of the persons who can collect, store, process, and disposed ofthe digital data:
Digital data can be handled only by the production manager in the userside, person in charge of maintenance and person responsible in the
manufacturer side, and persons designated in the predictive
maintenance contract.
 Range of the persons who can access the data:
In principle, access to digital data is restricted to only those who cancollect, store, process, and disposed of the data.
The handling of digital data of the predictive maintenance service has beensummarized. However, the current predictive maintenance service has notreached the level of detecting all the foretastes of machine tool defects andvarious technical developments are required in this field. In particular, thetechnology relating to the models of reasoning the sings that lead to alarmstop and the technology for processing data are the basis of the predictive
maintenance service and are currently in the process of development.
Therefore, to promote the research and development of such technology,
consideration should be given to permission of access of the digital data to
third parties that exchanged the confidential contract.

40

7. Proposal of a smart factory by utilizing the information model relating to thetarget services
The information model organized in 5. comprehensively represents the
behaviors of machine tools and describes their various statuses. Accordingly,
this model can also be utilized for production management of the entire factoryor management of our supply chains as discussed in 4. (1). Recently,
remarkable progress of AI technologies represents an opportunity to establish auseful environment for factories to collect and organize machine tool generated
digital data in a state that allows great cost savings with significant gains inefficiently.
The keys for implementing mass customization targeted by a smart factory are
the cycle for controlling the system and complete optimization. Important to noteis that smart customization refers to the strategy of manufacturing customized
products at the similar cost and price as those of mass-produced products.
Production data is manageable by personal judgment if data is processed daily.
However, creating optimum production instructions is a challenge to be done bypersonal judgment for data processed by the hour or by the minute. Flexible
approaches are important for situations involving a level of difficulty causing ashort-term suspension of machine operation which cannot be handled byinflexible production instructions. Various software tools are necessary tosupport performing complete control analysis, and measures in real time byconnecting facilities of production sites, machine tools, and states of various
processes. Despite this need for such software tools, connecting extremely
diverse hardware and software cannot be done easily. Therefore, constructing afactory to develop this connection mechanism is a great challenge for thecustomer.
The manufacturing industry has strength in its “Kaizen”, meaning the ability to
improve on-site improvement capability, and maintenance and reinforcement
measures are important elements of this strength. Conventional improvements
by manufacturers result in favor partial optimization. “Kaizen” is implemented forhuman-oriented activities so that the range is often within the visual reach orarms’ reach so that such activities are effective for the problems in a narrow
range such as those between facilities, between a facility and a worker, betweena facility and a part, and between parts. However, such an approach cannot
41

achieve the entire optimization even if partial optimizations are gathered. The
following points are to be examined in order to realize a smart factory while
ensuring the strength of the domestic manufacturers.
(1) Cyber-physical on-site improvement activity (Cyber-physical “Kaizen”)
This refers to an improvement for a work area at a distance even if it is in
the same factory, remote improvement that enables improvements in an
overseas factory, and production innovation for improvement.
By visualizing a range that is actually invisible by utilizing the IoT
information collection capability, create a virtual environment and constructa cyber-physical improvement site that runs PDCA cycles with predictive
techniques, and an improvement site of quick PDCA cycles.

(2) Providing an emergent infrastructure that takes advantage of the strengthof the manufacturing industry
From the cyber-physical “Kaizen”, emerge services and methodology for a
new manufacturing concept.
In Japan, there are software vendors and integrators relating to machine
tools production facilities, peripheral devices, MES, and SCADA. An
infrastructure that can integrate the expertise of software vendors andintegrators with those in the manufacturing industry exists here.
What is important here is to construct a cyber-physical factory that allows
the flow of feeding back the improvement results on the productionengineering side to the production management side. At utilization in
production management and analysis by AI technologies, it is notnecessarily reasonable to use the entire data generated in real time fromthe machine tool as it is. Although the trend of technological progress that
determines the speed of information processing and communication is tobe taken into consideration, at least, based on the trend of technologicalprogress that is assumed for the time being as the precondition, themechanism for using generated information effectively by selecting suchinformation is the reasonable method. This enables improvements of theprocess design as well as the manufacturing planning.
42On one hand, the engineering chain (production engineering)determines
specifications of advanced real time control derived from the machine tools,
FA, and robots for the realization of high quality and efficiency. On the other
hand, the supply chain (production management) determines how many
products are to be produced by when and where. Regarding a linking
between two chains at the information level, it is significant to arrange
specific linkage measures as the interfaces (information contents,
granularity, frequency, method, communication protocol, etc.), with theemphasis on the differences of quality and volume of the information
required for each chain to enhance the functions by fully utilizing the resultof the new technology such as IoT.
The structure of a conceptual smart factory is presented by utilizing theinformation model that is summarized in 5. The skeletal frame of theinterface draft is also presented. The primary proposal of the interfaces will
be announced in this year.
 Data (A) in the machine tool that is represented by NC of the diagram
below are utilized in both the production management and productionengineering areas and specifically, a wide range of services can beprovided by the following data flow. The conventional service such as
operation condition visualization is directly integrated into the
production management data from each machine tool (B). In the
proposed smart factory, the production engineering data is integrated,
processed, and then provided to the production management side.
 Various types of data that indicate the operating state in (A) extracted
in the various units (i.e., second, minute, hour, and day), are integrated
and stored as production engineering data (C). The data are used topromote more detailed site visualization of operating states and on -site
improvement activities (i.e., “Kaizen”).
 Various types of data that indicate the operating states in (A) in the timeunits of the μs and ms levels are integrated and stored as productionengineering data at the production site and are used for improvementof machining conditions.
 Production engineering data (C) are primarily processed (systemconstruction options such as remote mode and cloud are available) by
the intelligent judgment module (D) installed in a machine production
43

site, are fed back to (A), and are used by the service such asmachining efficiency improvements.
 The intelligent judgment module (D) promotes improvements on the
production engineering side. By sending the information from (D) to the
production management side (B), a cyber-physical factory with an
improvement scenario of total optimization can be constructed.

(Production management)(Production engineering)
(D)

ERP
MES

Information processing(Including intelligent
judgment)

SCADA

Machining efficiency
improvement

(B)

HMI

Predictive
maintenance

Production
management
data[Conventional technique]
In the conventional service,a part of the information thatindicates the operating stateis directly integrated into the
production management
data from the machine tool.

Productionengineering data

NC

Machine tool
Machine tool

PLC

(C)

SensorMachine tool
(production system)(A)

Figure 7.1 Smart factory conceptual diagram

To fully utilize the strength of the production engineering in the
manufacturing industry, it is important to provide the interfaces to be
standardized for distribution of data by modeling the data flow based on the
improvement cycle in each service as described above.

[Skeletal frame of interfaces]
In the examination of this system, standardization of interfaces is importantdue to the involvement of a variety of components of (A) such as CNC andsensors, and of a variety of their manufacturers.
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At this point, examples of the necessary data types that are critical to theinterfaces are listed. In addition, further examination regarding thestandardization of meaning of these specific data types is necessary.
■ Interfaces among (A), (C), and (D)• Machine tool state signals (initial, machining preparation, machining,alarm, communication disconnection, and so on)• Machine tool machining state (machining program, machining mode,
•
•
•
•
•

start of machining, and stop)
Machine tool motion state (position, speed, acceleration, and so on)
Spindle/feed motor state of machine tool (position, speed, acceleration,
torque, temperature, etc.)
Machine tool alarm state (alarm type and related information)
Machine tool mechanical state (operation management and volume ofstates required for predictive maintenance)
Information from sensors■ Interfaces between (D) and (B)• Operating status of machining cell (initial, machining preparation,
machining, alarm, communication disconnection, etc.)• Machine operation state of machining cell (machining part type,
machining quantity, machining time, stop period, etc.)• Machine power consumption of machining cell
• Machine alarm state of machining cell and its assumed cause• Machine warning state of machining cell and predictive maintenancetarget parts•

Information relating to the quality of machining cell parts (accuracy,
surface quality, etc.)

45

(Attachment)
Members of the committee(Chairman)(Vice-Chair)Waseda University, Professor
Akiyoshi Kabe
National Institute of Advanced Industrial Science andTechnology
Information Technology Research Institute,
Cyber Physical System Research Group
Group Leader[Syllabary order]
Okuma Co.

JTEKT Corp.

DMG Mori Co.,Ltd.

Hitachi, Ltd.

FANUC Co.

Hiroshi Oiwa

Member of the Board Executive Director
Technology Division
General Manager
Atsushi Ieki
Member of the Board
Executive Vice-President
Masakazu Isaka
Senior Fellow
Shirou Nakano
Senior Executive Officer
Manufacturing and Development Head Office in charge ofElectrical circuit/ control
Makoto Fujishima
MONOZUKURI Strategy Division
Production Engineering Promotion Department
Chief Engineer
Akio Hamaoka
Member of the Board Executive Vice President
Research & Development Administration Division
General Manager
Shunsuke Matsubara

Fujitsu, Ltd.

Industry Business Development Unit
Principal Consultant
Hiroyuki Kumagai
Mitsubishi Electric Co. Factory Automation Systems Group
Industrial Automation Machinery Division
Senior Chief Engineer
Koji Yasui
Yamazaki Mazak Co.Managing Officer Production Headquarters
Yasuhiko Ohno
Administration Headquarters BEST Promotion Department
Corporate Officer General Manager Isamu Inazuru

46National Institute of Advanced Industrial Science and Technology
Robot Innovation Research Center
Robot Software Research Laboratory
Research Laboratory Leader
Isao Hara(WG1 Chief examiner)
Hitachi, Ltd.
Power and Infrastructure Systems GroupPower & Infrastructure Systems Strategic Planning
Division
Business Development & External Relations Department
Department Manager
Kiyoshi Mizukami

47