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Reliability, Maintainability, and Safety 42.4 Challenges, Trends, and Open Issues 745

extrapolation, prognostics can be used to evaluate the

time when the drift will exceed a threshold and to pro-

pose a time before next potential failure. In this way,

proactive maintenance can optimize maintenance ac-

tions and planning in order to minimize production

downtime.

Proactive maintenance allows a maintenance ac-

tion improvement (mean availability), to follow the

degradation tendency (quality of service), to avoid the

occurrence of dangerous situations (safety), and ﬁnally

to support the operator with knowledge oriented to the

degradation cause and effect (maintainability).

e-Maintenance is an organizational point of view

of maintenance. The concept of e-Maintenance comes

from remote maintenance capabilities coupled with

information and communication capabilities. Remote

maintenance was ﬁrst a concept of remote data acquisi-

tion orconsultation. Data are accessible during a limited

time. In order to realize e-Maintenance objectives data

storage must be organized to allow ﬂexible access to

historical data.

In order to improve remote maintenance, a new con-

cept of e-Maintenance emerged at the end of the 1990s.

The e-Maintenance concept integrates cooperation, col-

laboration, and knowledge-sharing capabilities in order

to evolve the existing maintenance processes and to try

to tend towards new enterprise concepts: extended en-

terprise, supply-chain management, lean maintenance,

distributed support and expert centers, etc. Based on

web technologies, the e-Maintenance concept is nowa-

days available and industrial e-Maintenance software

platforms exist. e-Maintenance platforms (sometimes

termed asset management systems) manage the whole

of the maintenance processes throughout the system

lifecycle from engineering, maintenance, logistic, expe-

rience feedback,maintenance knowledge capitalization,

optimization, etc. to reengineering and revamping.

e-Maintenance is not based on software functions but

on maintenance services that are well-deﬁned, self-

contained, and do not depend on the context or state of

other services. So, with the advent of service-oriented

architectures (SOA) and enterprise service-bus tech-

nologies [42.45], e-Maintenance platforms are easy

to evolve and can provide interoperability, ﬂexibility,

adaptability, and agility. e-Maintenance platforms are

akindofhub for maintenance services based on exist-

ing, new, and future applications.

42.3.4 Industrial Applications

Industrial software platforms have been developed dur-

ing the 1990s in order to provide the proof of concept

of this RMS modeling framework before marketing off-

the-shelf products. The ﬁrst applications have appeared

since 2000 in various sectors such as power energy, steel

factory, petrochemicalprocess, navy logisticsand main-

tenance support, nuclear fuel manufacturing and waste

treatment, etc.

A common objective of these multisector applica-

tions is to reduce operation costs by increasing the

availability, maintainability, and reliability of plants and

systems, and to facilitate their compliance with regu-

lation laws. Another common objective is to elicit and

save the implicit knowledge acquired by skilled oper-

ators as well as by skilled engineers when performing

their tasks.Others objectives are speciﬁc to anindustrial

sector; forexample, understanding complex phenomena

to anticipate maintenance operations is critical to opti-

mize the impact of shutdown and startup operations in

process plants [42.46].

Return on investment is estimated to be at most

1year from these industrial experiments, and leads to

a distributed service-oriented e-Maintenance infrastruc-

ture to warrantee by contract a level of availability in

plant operation (Fig.42.8).

42.4 Challenges, Trends, and Open Issues

All aspects of dependability such as reliability, main-

tainability, and safety should be viewed in a broader

context depending on both management and technical

processes within the enterprise system to ensure the

necessary resilience to intrinsic and extrinsic complex

phenomena occurring when systems are operating in

changing environments. For example, MTBF is a mea-

sure of the random nature of an event and does not

predict when something will fail but only predicts the

probability that a system will fail within a certain time

boundary. Contrary to conventional wisdom, accidents

often result from interactions between perfectly func-

tioning components, i.e., before a system has reached

its expected life as predicted by RMS analysis.

Such considerations underscore that other advanced

concepts are beyond traditional RMS analyses and the

individual mind-set of each engineering discipline to

cope with emergent behavior as one of the results of

complexity. In other words, dependability assumes that

cause–effect relationships can be ordered in known and

Part E 42.4

746 Part E Automation Management

knowable ways, while resilience [42.47] should con-

ﬁne the contextual emergence of complex relationships

within the system and between the system and its envi-

ronment in unordered ways [42.48].

An initial challenge is to understand that the con-

cept of system as the unique result of normal emergence

within a collaborative systems engineering process

leads to an ad hoc solution based on heuristics and nor-

mative process-driven guidelines [42.49].

A second challenge relies on weak emergence

[42.50] to perceive, model, and check added behaviors

due to the interactions between the component sys-

tems. This should be led by extensive model-driven

requirements analysis adding more details than current

practices and complementary experiments such as mul-

tiagent simulation to track self-organizing patterns in

order to improve component systems’ adaptability.

A third open challenge deals with the quality of

the engineering process to determine whether a system

can survive a strongly emergent event, as well as the

adaptability of the whole enterprise to come into play in

facing an inevitable systemic instability.

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spectives: Mind, Causation and World,Vol.11

(Blackwell, Oxford 1997)

Part E 42

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749

Product Lifecy

43. Product Lifecycle Management

and Embedded Information Devices

Dimitris Kiritsis

The closed-loop product lifecycle management

(PLM) system focuses on tracking and managing

the information of the whole product lifecycle,

with possible feedback of information to prod-

uct lifecycle phases. It provides opportunities

to reduce the inefﬁciency of lifecycle operations

and gain competitiveness. Thanks to the ad-

vent of hardware and software related to product

identiﬁcation technologies, e.g., radiofrequency

identiﬁcation (RFID) technology, recently closed-

loop PLM has been highlighted as a tool of

companies to enhance the performance of their

business models. However, implementing the

PLM system requires a high level of coordination

and integration. In this chapter we present the

background methodologies and techniques and

the main components for closed-loop PLM and

how they are related to each other. We start with

the concept of closed-loop PLM and a system ar-

chitecture in Sect. 43.1.InSect.43.2 we describe

the necessary components for closed-loop PLM

and how to integrate and coordinate them with

respect to business models, hardware, and soft-

ware. In Sect. 43.3 we propose a development

guide based on experiences gathered from proto-

type applications developed to date. In Sect. 43.4

we introduce a real case example that imple-

ments a closed-loop PLM solution focusing on

43.1 The Concept of Closed-Loop PLM ............ 749

43.2 The Components

of a Closed-Loop PLM System................. 751

43.2.1 Product Embedded Information

Device (PEID)................................ 751

43.2.2 Middleware ................................. 753

43.2.3 Decision Support System (DSS)........ 753

43.2.4 Product Knowledge

and Management System (PDKM) ... 754

43.3 A Development Guide

for Your Closed-Loop PLM Solution ......... 755

43.3.1 Modeling .................................... 755

43.3.2 Selection of PEID System................ 756

43.3.3 Data and Data Flow Deﬁnition ....... 758

43.3.4 PDKM, DSS and Middleware ........... 759

43.4 Closed-Loop PLM Application ................. 761

43.4.1 ELV Information

andPEIDTechnology..................... 762

43.4.2 Decision Flow .............................. 762

43.5 Emerging Trends and Open Challenges ... 763

References .................................................. 764

end-of-life (EOL)ofvehicles(ELV). Finally,

Sect. 43.5 discusses some challenging issues

and emerging trends in the implementation

of closed-loop PLM.

43.1 The Concept of Closed-Loop PLM

Product lifecycle management (PLM) is a new strategic

approach to manage product-related information efﬁ-

ciently over the whole product lifecycle. Conceived as

an extension to product data management (PDM), its

vision is to provide more product-related information

to the extended enterprise over the whole product life-

cycle. Its concept appeared in the late 1990s, moving

beyond the engineering aspects of a product and pro-

viding a shared platform for creation, organization, and

dissemination of product-related knowledge across the

extended enterprise [43.1]. PLM facilitates the inno-

vation of enterprise operations by integrating people,

processes, business systems, and information through-

out product lifecycle and across extended enterprise. It

Part E 43

750 Part E Automation Management

aims to derivethe advantagesof horizontallyconnecting

functional silos in organizations, enhancing informa-

tion sharing, efﬁcient change management, use of past

knowledge, and so on [43.2]. To meet this end, a PLM

system should be able to monitorthe progress of a prod-

uct at any stage in its lifecycle, to analyze issues that

might arise at any product lifecycle phase, to make

suitable decisions to address problems, and to exe-

cute and enforce these decisions. In spite of its vision,

PLM as deﬁned above has not received much atten-

tion so far from industry because there are no efﬁcient

tools to gather product data over the entire product

lifecycle. However, recent applications of product iden-

tiﬁcation technologies in various PLM aspects [43.3–9]

demonstrate that a sound technological framework is

now available for PLM to implement its vision. Prod-

uct identiﬁcation technologies enable products to have

embedded information devices (e.g., RFID tags and on-

board computers), which makes it possible to gather

the whole lifecycle data of products at any time and

at any place. A new generation of PLM systems based

on product identiﬁcation technologies will make the

whole product lifecycle totally visible and will allow

all actors involved in the product lifecycle to access,

manage, and control product-related information, espe-

cially information after product delivery to customers

and up to its ﬁnal destiny, without temporal or spatial

constraints. During the whole product lifecycle, we can

now have visibility of not only forward but also back-

ward information ﬂow; for example, beginning of life

(BOL) information related to product design and pro-

duction can be used to streamline operations of middle

of life (MOL)and endof life(EOL). Furthermore,MOL

and EOL information can also go back to designers

and production engineers for the improvement of BOL

decisions. This indicates that information ﬂow is hor-

izontally closed over the whole product lifecycle. In

addition, based on data gathered by product embedded

information devices (PEID), we can analyze product-

related information and take some decisions on the

behavior of products, which will affect data gathering

again [43.10]. This means that information ﬂow is also

vertically closed. We call this concept and relevant sys-

tems the closed-loop PLM. The concept of closed-loop

PLM can be deﬁned as follows: a strategic business ap-

proachfor the effective management of product lifecycle

activities by using product data/information/knowledge

which can compensate PLM to realize product lifecy-

cle optimization dynamically in closed loops with the

support of PEIDs and product data and knowledge

management (PDKM) system.

The objective of closed-loop PLM is to optimize

the performance of product lifecycle operations over

the whole product lifecycle, based on seamless prod-

uct information ﬂow through a local wireless network

of PEIDs and associated devices and through remote

Internet connection [43.11] to knowledge repositories

in PDKM. In addition to PEIDs, sensors can be built

in products and linked to PEIDs for gathering status

data [43.12]. During product lifecycle, each lifecycle

actor can have access to PEIDs locally with PEID

controllers (e.g., RFID readers) or to a remote PLM sys-

tem for getting necessary information. Furthermore, in

closed-loop PLM, decision support systems (DSS)inte-

grated to PDKM systems may provide lifecycle actors

with suitable advice or decision support at any time.

In the closed-loop PLM, all business activities per-

formed along the product lifecycle must be coordinated

and efﬁciently managed. Although there are a lot of in-

formation ﬂows and interorganizational workﬂows, the

business operations in closed-loop PLM are based on

the interactions among three organizations: the PLM

agent, PLM system,andproduct. The PLM agent can

gather product lifecycle information quickly from each

product with a mobile device such as a personal digital

assistant (PDA) or a ﬁxed reader with built-in antenna.

He sends information gathered at each site (e.g., retail

sites, distribution sites, and disposal plants) to a PLM

system, as illustrated in Fig.43.1.

A PLM system provides lifecycle information or

knowledge generated by PLM agents through product

lifecycle activities realized through the three main prod-

uct lifecycle phases: BOL, MOL,andEOL.

BOL is the phase where the product concept is

generated and subsequently physically realized. In the

closed-loop PLM, designers and production engineers

will receive feedback about detailed product informa-

tion from distributors, maintenance/service engineers,

customers or remanufacturers on product status, prod-

uct usage, product service, conditions of retirement, and

disposal of their products. The feedback information is

extremely valuable for product design and production

because designers and production engineers are able

to exploit expertise and knowhow of other actors in

the product lifecycle. Hence, closed-loop PLM can im-

prove the quality of product design and the efﬁciency of

production.

MOL is the phase where products are distributed,

used, maintained, and serviced by customers or engi-

neers. In the closed-loop PLM,aPEID can log the

product history related to distributing routes, usage

conditions, failure, maintenance or service events, and

Part E 43.1

Product Lifecycle Management and Embedded Information Devices 43.2 The Components of a Closed-Loop PLM System 751

Necessary functions

• Data processing

• Memory

• Power unit

• Communication unit

• Sensor reading unit

• Sensor

Combinations of the following

• Sensor

• RFID tag

• Onboard computer

• Etc.

PEID controller

• PDA

• Fixed reader with built-in antenna

• Etc.

PDKM

(product data and

knowledge management)

PLM experts

PEID

(Product embedded information device)

Product

PLM agent

PLM system

Data & info.

Data & info. request

Fig. 43.1 Basic framework for PEID applications in PLM

so on. This information is later gathered into a PLM

system for analysis and sharing. Thus, during MOL,

an up-to-date report about the status of products and

real-time assistance can be obtained from this system

through the Internet or wireless mobile technology.

Based on these feedbacks, predictive maintenance can

be done by maintenance engineers [43.13]. Further-

more, optimizing logistics operations for maintenance

and service can be facilitated.

EOL is the phase where EOL products are col-

lected, disassembled, refurbished, recycled, reassem-

bled, reused or disposed. It can be said that EOL

starts from the time when the product no longer sat-

isﬁes an initial purchaser [43.14]. In the closed-loop

PLM, the use of PEIDs can greatly increase the ef-

fectiveness of EOL management; for example, material

recycling can be signiﬁcantly improved because re-

cyclers and reusers can obtain accurate information

about valuable parts and materials arriving via EOL

routes: what materials they contain, who manufactured

them, and other knowledge that facilitates material

reuse [43.15].

43.2 The Components of a Closed-Loop PLM System

The components of a closed-loop PLM system and their

relations are presented in the ﬁve layers of the system

architecture schema shown in Fig.43.2 [43.16].

These layers are mainly classiﬁed into business pro-

cess, software, and hardware. PEID is an important

hardware component for facilitating the closed-loop

PLM concept. Furthermore, software related to ap-

plications and middleware layers, and their interfaces

play important roles in closed-loop PLM. Following

are some more details about the components of whole

closed-loop PLM system: PEID, middleware, DSS,and

PDKM.

43.2.1 Product Embedded Information

Device (PEID)

PEID stands for product embedded information device.

It is deﬁned as a device embedded in (or attached to)

a product, which contains information about the prod-

uct [e.g., product identity (ID), and which is able to

Part E 43.2

752 Part E Automation Management

Tractor Locomotive

Milling

machine

PEID

management

Semantic

enrichment

Dispatching Notifications Read/write

RFID

Embedded

systems

Decision

making

Knowledge

management

Analytics

Design for X

Adaptive

production

Preventive

maintenance

Tracking &

tracing

Effective

recycling

Business

process

Applications

Middleware

PEID

Products

Fig. 43.2 Overall system architecture for closed-loop PLM

provide the information whenever requested by external

systems during the product lifecycle. There are vari-

ous kinds of information devices built in products to

gather and manage product information, for example,

various types of RFID tags and onboard computers.

A PEID has a unique ID and provides data gathering,

processing, and data-storage functions. Power manage-

ment of a PEID is important to allow it to provide

its functionality along the product lifecycle. Particular

Long-range communication

Internet/GSM/GPRS/

mobile phone

Short-range communication Radio wave

Product identification EPC

Data storing Memory

Data processing/diagnosis Processor & firmware

Data gathering Sensor reading unit

Power management Power unit

PEID

Passive

RFID

Active

RFID

Onboard

com.

Fig. 43.3 PEID functions and types (EPC – electronic product code, GSM – global system for mobile communications,

GPRS – general packet radio service)

attention is obviously paid to the data gathering func-

tion. Over the last decade, a lot of sensor technologies

have beendeveloped togather environmental status data

of products related to mechanical, thermal, electrical,

magnetic, radiant, and chemical data [43.12,17]. These

sensor technologies can be incorporated into the PEID

to gather the history of product status with the data

gathering function. Eventually, these functions enable

a PEID to gather data from several sensors, to retain or

Part E 43.2

Product Lifecycle Management and Embedded Information Devices 43.2 The Components of a Closed-Loop PLM System 753

PDKM (product data and knowledge management)/other applications

ISC (intersystem communication)

RHL (request handling layer)

Core PEID access container

DHL (device handling layer)

Content

Passive