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CE Challenges – Work to Do

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CE has been used for more than two decades now. Despite many successes and advantages, there are still many challenges to be addressed. These challenges are both technical and organisational. In the paper we will address the current challenges of CE. Many challenges are related to the exchange of data and knowledge and to the systems that make data and knowledge exchange possible. Although much progress has been made in enabling extensive data and knowledge exchange and use, much remains to be wished. For example, there are still barriers to data exchange. Technically, these barriers may consist of different formats, differences in infrastructures and systems, and different semantics. There are also organisational and political barriers. For example, investment in information system may heavily impact upstream suppliers, while revenues of better information exchange may predominantly be gained by downstream actors. Without sharing costs and revenues, chain-wide information exchange will not be easily realised. Another barrier is the possible lack of willingness to share information, because of potential misuse of knowledge and loss of power. The paper is organised as follows. First we will describe the current manifestation of CE as described in a recent book. Second, we will list current trends in CE. Third, we will present some Critical Success Factors (CSFs) that are considered relevant for implementing and adapting CE practices. Last, we indicate some research and practical questions to be addressed, especially for areas that have a high potential and actual impact.
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CE Challenges – Work to Do
Josip Stjepandić a , Wim Verhagen b and Nel Wognum1
a
PROSTEP AG, Germany
b
Technical University of Delft, Faculty of Aerospace Engineering, Air Transport &
Operations.
Abstract. CE has been used for more than two decades now. Despite many
successes and advantages, there are still many challenges to be addressed. These
challenges are both technical and organisational. In the paper we will address the
current challenges of CE. Many challenges are related to the exchange of data and
knowledge and to the systems that make data and knowledge exchange possible.
Although much progress has been made in enabling extensive data and knowledge
exchange and use, much remains to be wished. For example, there are still barriers
to data exchange. Technically, these barriers may consist of different formats,
differences in infrastructures and systems, and different semantics. There are also
organisational and political barriers. For example, investment in information
system may heavily impact upstream suppliers, while revenues of better
information exchange may predominantly be gained by downstream actors.
Without sharing costs and revenues, chain-wide information exchange will not be
easily realised. Another barrier is the possible lack of willingness to share
information, because of potential misuse of knowledge and loss of power. The
paper is organised as follows. First we will describe the current manifestation of
CE as described in a recent book. Second, we will list current trends in CE. Third,
we will present some Critical Success Factors (CSFs) that are considered relevant
for implementing and adapting CE practices. Last, we indicate some research and
practical questions to be addressed, especially for areas that have a high potential
and actual impact.
Keywords. Cross-disciplinary, cross-functional, cross-boundary collaboration,
information and knowledge exchange.
1. Introduction
CE has been known for more than three decades now. It is a encompassing concept,
emphasizing collaboration between relevant stakeholders throughout any innovation
process, whether product, process or organization innovation. The aim of CE is to
reduce time-to-market, improve quality and reduce costs by an ever more efficient
product creation process. CE is justified by higher competitiveness. Already from the
inception of an idea for an innovation, the whole process of development, production or
implementation, usage, service and maintenance, and finally disposal or recycling
should be highly transparent. People from various lifecycle stages, different companies,
and also from other stakeholders like government, financial institutes, knowledge
institutes, and possibly others need to be involved [1]. CE requires people from
different functions, disciplines, and cultures to collaborate deeply in an inherently
uncertain process for a dedicated period of time. They need to communicate
continuously and exchange huge amounts of data.
1 Corresponding author, E-Mail: wognumnel@gmail.com
Transdisciplinary Lifecycle Analysis of Systems
R. Curran et al. (Eds.)
© 2015 The authors and IOS Press.
This article is published online with Open Access by IOS Press and distributed under the terms
of the Creative Commons Attribution Non-Commercial License.
doi:10.3233/978-1-61499-544-9-627
627
Although CE in principle is not difficult to understand, it is tremendously difficult
to implement and use. An investment for the implementation of CE is hard to justify
with exact calculation. There are many barriers to reach an optimal CE situation. First
of all there are the technical barriers. Despite the fact that many systems have been
developed that allow the exchange of data within and across organizational borders,
there is still much that needs to be aimed for [2].
Second, there are economic barriers. Many different information systems are in use
by powerful parties in collaboration. For SMEs in a supply chain or network it is often
not possible to buy new systems for collaboration with strong parties like OEMs. They
may adapt their existing systems or take the additional burden for exchanging data. In a
supply chain, a supply chain-wide information system has many advantages, especially
when they are web-based. It may be able to connect to different proprietary systems
and offer a communication platform for supply chain actors as well as additional
processing power. However, the need for such a system may be larger in one stage of
the supply chain, while benefits may be larger in another stage. The willingness to
invest in a supply chain-wide information system may thus not be equally divided [3].
When investments and benefits are not well balanced in a supply chain, adoption and
implementation of a supply chain-wide information system may not be possible.
Moreover, the processes in individual companies may not yet be ready to be
harmonized [4] thus leaving many gaps in the information flow.
Third, there are the cultural and power barriers. The willingness to collaborate
may be limited, in particular when involved parties have different positions and goals
e.g., in a joint venture. The free exchange of knowledge is not without danger.
Companies may be afraid of loosing their competitive position and power [5], while
people may be afraid of loosing their expert position when they share their knowledge.
We have also to keep in mind that a collaboration lasts for limited time.
In section 3 we will address current trends in CE as have been identified in a recent
publication [6] following a description of the current manifestation of CE in section 2.
In section 4, Critical Success Factors (CSFs) are listed that are deemed relevant in a CE
context. The last part of the paper will address research and practical question that still
exist. We will limit the discussion to areas that have a high potential and actual impact.
2. Current manifestation of CE
Concurrent Engineering (CE) as a concept is still very much alive, although the term as
such is not often heard anymore. As was the case with CE already from the beginning,
also now the emphasis is on collaboration between multiple disciplines, functions and,
most of the cases, companies, which may be separated in large time and space. Current
CE is about (open) innovation of products, processes, and organisations (see also [1]).
From the early inception of ideas the whole trajectory of product development,
production, service, and even destruction or assett recovery has to be understood and
taken into account. The customers of (intermediate) products and services and
consumers also play a large role in the processes. In Figure 1, the essence of current CE
is depicted.
In Figure 1, CE is depicted as an encompassing innovation system aimed at
generating either a totally new product or service or at changing existing ones, where
the changes may be large or small. The CE process influences the production system,
which may already exist or needs to be created, possibly including a totally new
J. Stjepandi´c et al. / CE Challenges – Work to Do628
organisation. The production system is an essential part of the design that is the output
of various stages of the innovation process. For example, in the case of adaptation to
existing products the changes that are needed in the production system need to be taken
into account. In the case of a new product or service the way in which the new
company or even a whole supply chain needs to be structured is also part of the total
design and also gradually evolves with during the design process. It is important that
relevant important parties are involved in this process. Collaboration between all
different parties and actors needs to be arranged and governed well with specific
arrangements and possibly also contracts.
Figure 1. The system of CE
As can be inferred from Figure 1, the exchange of information and knowledge
plays a crucial role in the whole process from inception of an idea to actual production
and use. Information and knowledge can be exchanged by means of documents and
drawings and by intensive discussions in design meetings. Face-to-face meetings occur
especially in the earlier stages of design with also much paper documents exchanged.
Time and money can, however, be saved with information systems, that exist in many
different forms and formats and for different stages of the development process.
The development process can, in general, be divided into the following steps, in
line with the systems engineering V model [7,8,9]:
1. Concept generation and requirements analysis
2. System specification (incorporating conceptual, preliminary and detailed
design)
3. Implementation
4. Integration and testing
5. Verification & validation
Numerous disciplines and associated types of information systems and applications
target individual or multiple stages of the development process. Because product
development has become an increasingly global activity, involving many different
organizations, complexity and dynamics have dramatically grown [10]. This situation
poses significant challenges on interoperability of methods, tools as well as on
organizations and users. Below, some trends are discussed that aim to deal with the
growing complexity and dynamics.
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3. Reducing complexity and dynamics
Globalization as well as increasing complexity are drivers of increasing integration of
method and tools. Integration and interoperability are assumed to speed up
development and lower costs, yet developing and implementing interoperable,
integrated solutions can be assumed as a driver of complexity as well. To simplify
these aspects, existing standards may be employed to reduce complexity and improve
interoperability [11].
Besides standardization, there is a trend towards loosely coupled models in
federated environments. On a local level, users can specify their domain models
without worrying about integration aspects. On a global level, the federated framework
takes care of model integration and interoperability. Furthermore, globalization
requires a high level of time synchronization of distributed teams [12].
Another major strategic shift is servitization of manufacturing industries, i.e., the
innovation of organization’s capabilities and processes to shift from selling products to
selling integrated products and services that deliver added value [13].
With increasing complexity and integration, the size and complexity of the
stakeholder environment are also expanding. First of all, this sitution has implications
for short-term dynamics in stakeholder environment composition, which emerges
typically as a network-centric structure with various level of interdependence based on
operational needs [14]. The realization of complex systems usually requires the
temporary collaboration of a multitude of stakeholders from different domains, such as
hardware, software and services [15]. Besides the customer/user and the system
integrator, there are stakeholder groups for the system components, life cycle services
and system environment, each with their own objectives and context. During the
various stages of the design process, these stakeholders will generate dynamic and
sometimes conflicting sets of requirements. Involving all stakeholders continually in
the process may very well drive up overall design time. To counter this, techniques
may be employed such as agile design and development, where fast prototyping, test-
driven, model-driven and behavior-driven development methodologies allow focusing
on specific business cases [16].
The stakeholder environment is also subject to long-term dynamics. In this light,
the previously mentioned trend towards servitization will impact stakeholder
composition. A trend towards the provision of product-service packaging and the
proliferation of service businesses introduces both tangible and intangible elements into
system design. It requires the utility of hierarchical system models as a way of flexibly
combining such elements by focusing on requisite functionality [17]. In the digital
context, organizations are increasingly focusing on value creation outside their
boundaries, because value is created through interplay of customers, competitors,
collaborators and the wider community. In terms of product lifecycle management, this
trend gives after-sales importance equal to other phases of the product lifecycle,
including added value generated from Big Data and Internet of Things [18, 19].
The aforementioned trends towards integration and interoperability have an impact
on the exchange of knowledge and information. By using technology means sharing
has become easier than ever. However, sharing is not yet good enough, because the
amount of data being created, stored and used every day is growing exponentially.
Moreover, the way in which the knowledge is used in the design process is changing
continuously. Some of the driving factors of sharing are listed below [20]:
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1. The rise of the wikis. A wiki is a database of interactive web pages that allows
members of a user group to collectively edit the same material from any computer
with an Internet connection. Wikis provide a flexible and self-organizing platform
that is especially useful from the point of view of early design, when the
information and knowledge is unstructured, and from the point of view of
collaborative design, where all communication is persistently recorded and loosely
organized through user-defined tags. With such capabilities wikis aims to fill gaps
left through large software systems in almost each enterprise [21].
2. Bio-inspired knowledge for design. Bio-inspired designs can be classified under
the heading ‘conceptual’, when the result of the inspiration is an artifact, or
‘computational’, when the result is a process. Both areas face the challenge of
identification of relevant biological phenomena, the abstraction of concepts to a
level that can be understood by engineers without a background in biology,
enabling non-obvious applications of the phenomena, and avoiding
misinterpretations of the underlying biological phenomena [22,23]. Such
approaches are already widely known and applied like bionics and evolutionary
computation. They may become even more important for the product design
process, but are not dominant yet.
3. Ontologies and semantic interoperability. Ontologies are required for both
encoding design knowledge and for facilitating semantic interoperability.
Development of engineering ontologies on a large scale can evolve in a similar
manner to the compilation of the Oxford Dictionary. Researchers (across the
globe) could undertake ontology development in selected areas and then contribute
to a global repository [24]. This would require the establishment of appropriate
standards for encoding ontologies. Here occurs another collision of the reuse of
knowledge and intellectual property protection, which is still to be resolved.
4. Natural user interfaces. Reality-based systems facilitate intuitive human–
computer interaction with little user training or instruction. This is evident in the
recent upsurge in touch-based personal computing devices like smartphones and
tablet computers, and in gesture-based controls in gaming. The portable and
ubiquitous nature of tablet computers make them ideal for collaborative design
processes like the recording and progressive documentation of design discussions.
It is thus likely that NUIs may prove an important factor towards mass
collaboration and the democratizing of the design process. Utilization of a user-
friendly common client architecture based on backend services helps reduce
training and support effort, in particular in case of a change. Definition of different
roles in a sole architecture will foster agility.
Another issue with respect to knowledge and information concerns human
involvement. Humans need to be ‘in the loop’, especially in the earlier phases of design.
Deterministic thinking is not suitable anymore for complex problems, as has been
emphasize by Moser [25]. Emergent behavior cannot be explained sufficiently, because
interaction between components and their behaviors is not well understood. As
highlighted before, socio-technical modelling approaches are necessary to model and
evaluate this emergent behavior. A significant positive influence on product innovation
results is exerted by external resources such as consultants, commercial labs or private
R&D institutions. Different amounts of input information provided by
customers/clients/end-users have high impact on innovation results [26].
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A final trend in research and practice related to information and knowledge in CE
concerns intellectual property (IP) and its protection. Increasing cooperation between
stakeholders necessitates intellectual property protection and enterprise rights
management. As virtual product design increases (see previous section), the risks and
consequences associated with intellectual property theft rise dramatically. Methods for
patent infringement tracking as well as for IP protection in information and data flow
must be developed to a further extent [5].
Complexity and dynamics, however, also impact upon the adoption and
implementation of CE in practice, in particular because the many different solutions
and trends require organizations to adapt their strategies, technology, and way of
working. The fact that CE processes are also performed in collaboration between
different departments within companies and between different companies complicates
this continuous adaptation [27].
Adoption, implementation and continuous adaptation of CE has many pittfalls.
Knowledge of these pittfalls is necessary for reducing failures and achieve success.
Below, we list some Critical Success Factors (CSFs) that are considered relevant for
implementing and adapting CE practices.
4. Critical Success factors for implementing CE
The implementation of CE in organizations is in essence not much different from the
implementation of complex information systems or the adoption of different work
practices. Much has been published already on complex change processes within and
across organizations, including the many barriers, like in [27]. Many pitfalls exist.
Ignoring them may dramatically impact complex change processes like CE
implementation. In the literature Critical Success Factors (CSFs) can be found that
need to be taken into account in such processes.
In a recent publication critical success factors for the implementation of supply
chain-wide information systems have been discussed [28]. A chain-wide information
system, as is necessary in CE, requires the alignment of existing information systems
and work practices, as well as collaboration between people with their different culture
and power. As such, we can learn from the area of information system implementation
to start defining CSFs for implementing CE in its current manifestation: complex
innovation of products, processes and organizations, requiring the adoption and use of
information systems within and across organizations.
Starting point of the research, as published in [29], was the extensive literature on
the implementation of ERP systems. CSFs from this literature were used as a starting
point for identifying CSFs in the context of implemention of information systems in
supply chains. A list of 21 articles on supply chain information systems was analazed.
In total 13 CSFs have been formulated. CSFs are, however, not stand-alone issues, but
interact with each other. To model this interaction the encompassing MIT90s
framework of Scott Morton [30] was used. In Table 1, the CSFs are listed according to
this framework. CSFs are generic in the sense that more detailed guidelines and actions
are needed to be able to apply and use the CSFs. Besides actions, responsibilities need
to be clear in any change project. This aspect is often neglected. Project experience
helps in understanding the depth of CSFs and applying them in specific situations.
In a CE context the CSFs listed in table 1 are relevant. The sociotechnical nature of
CE becomes apparent in the list of CSFs. In particular in the multi-company
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environment of CE, translating and applying the CSFs is not without many challenges.
Let’s take the second CSF as an example. In adopting web-based technology that
enable companies to exchange information, decision are needed on investments, costs,
and revenues. Investments may be high in one part of the supply chain or network,
including the risks, while revenues might be high in other parts of the supply chain or
network. In addition, maintenance costs might also not be equally divided over the
parties involved. Sharing costs, benefits, and risks is necessary to increase success of
an information system that is to be used by more than one party.
Table 1. Critical Success Factors for Implementing Supply Chain Information Systems.
Scott Morton element
Critical Success Factor
Project Strategy
Align vision and build p
lans
Share costs, benefits, and risks
Management processes
Manage project
Monitor and evaluate performance
Communicate effectively
People
Manage relationships
Take top
-management responsibility
Manage change and deliver training
Compose project team
Information system(s)
Assess legacy IT systems
Select standards, vendor, and software package
Manage data exchanged
The list of CSFs is just a starting point. They can be used as a basis for additional
research in the context of CE. They need to be refined and specified for use in different
CE contexts.
5. Challenges for research and practice
Current trends in economy and society can and likely will exert a sizeable influence on
CE. These trends are mostly either accompanied by or related to information and
communication technology (ICT). To keep pace, CE must be well synchronized with
the development of ICT. Below, some recent developments in ICT are briefly
discussed which are expected to influence future CE solutions.
x Mass collaboration: Mass collaboration involves large numbers of people
working independently on a single project, often modular in nature, using
social software and computer-supported collaboration tools. This idea has
been implemented as crowdsourcing, which typically involves an online
system of accounts for coordinating buyers and sellers of labor.
Mass collaboration is based on the realization that customers are regarded as
an important information source for product innovation. As an effective way
to aggregate a crowd’s wisdom for product design and development,
crowdsourcing shows huge potential for creativity and has been regarded as
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one important approach to acquire innovative concepts [31]. However, it is
still a challenge to make use of crowdsourcing in product design: how can the
large number of crowdsourcing concepts be reviewed efficiently? Challenges
exist in approaches and methods to improve the efficiency of result evaluation
and to assist designers in identifying promising design candidates for further
design, analysis and evaluation. The workload to review crowdsourcing
responses manually is very heavy. Moreover, the reliability of evaluation
results heavily relies on designers’ personal knowledge and experience.
Concept screening methods are needed to assist designers in identifying useful
responses from crowdsourcing results.
x Cyber Physical Systems (CPS): A Cyber Physical System (CPS) integrates
computational and physical processes. CPS comprises embedded computing
devices and networks that monitor and control physical processes, with
feedback loops when physical processes affect computations and vice versa.
Interaction with the physical environment will provide added value with new
capabilities and characteristics to systems, while inclusion of physical
processes not only increases the complexity of the system but also increases
the uncertainties in the behavior of the system [32]. Holistic decentrality is the
main challenge for cyber-physical production systems (CPPS) in which
organization, services, objects and software are organized in a fully
decentralized way. The industry requires such systems for the production of
highly customized products in small quantities with high resource productivity
and corresponding speed.
The top level of interoperability is considered with the systems of systems in
which multiple CPS can combine their autonomous singular capabilities with
their own intelligence. Thus, they can evolve entirely new capabilities and
develop new services. This level of interoperability remains a vision for
facilitating decentralized, autonomous systems development and design with
the capability for self-configuration and plug-and-produce.
x Big Data: The amount of data around us is growing exponentially. ‘Big Data
applications promise to provide better insights into various business processes
or everyday life in a novel way, by analyzing large data sets and discovering
relationships across structured and unstructured datasets. Big Data is a
booming topic in the scientific community as well as in the enterprise world
[33]. Many of the Big Data challenges are generated by future applications
with which users and machines will need to collaborate in intelligent ways.
Within the context of CE, a huge challenge concerns the issue of Knowledge
Discovery in Databases (KDD), a nontrivial process of identifying valid, novel,
potentially useful, and ultimately understandable patterns in data [34,35].
Intelligent utilization of existing data (e.g., digital manufacturing) provides a
new support function for modern product creation processes. Based on
planning data, compiled during preceding product emergence processes,
products can be evaluated more easily, which leads to a faster and easier
attainment of planning and design levels. The feasibility to segment product
data in valid subject-specific groups and to map adequate product-specific
assembly operations will remain a subject of research.
Big Data will likely bring disruptive changes to organizations and vendors. As
a cautionary note, the analysis of Big Data, if improperly used, may pose
J. Stjepandi´c et al. / CE Challenges – Work to Do634
significant issues specifically in the following areas: data access and policies,
industry structure, and techniques. Because large amounts of unstructured data
may require different storage and access mechanisms combined with more
sensitive data assembled together, Big Data will be more attractive to potential
attackers. Application of Big Data requires the issuing of specific rules and
regulations as well as the associated control mechanisms to become useful and
fruitful.
6. Summary
In this paper, concurrent engineering has been depicted as an encompassing concept
that matches current approaches to current forms of innovation in which many different
actors from different stages of a product lifecycle and different context are involved.
Many different technologies have been developed to support collaboration and
information and knowledge exchange in an innovation process. Many systems and
system ideas have been listed to show the different approaches and their relevance for
particular stages in a development process. However, many challenges still exist and
many new technologies are underway. We have indicated the most important
challenges and technologies that are underway to solve some or most of the challenges.
Nevertheless, CE is also a process involving many people who need to be open to
collaboration. Organisational arrangements need to support and enable such
collaboration. These arrangements and their challenges need further exploration.
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J. Stjepandi´c et al. / CE Challenges – Work to Do636
... To accomplish TE, some researchers advocate knowledge sharing across boundaries (e.g. Stjepandić et al., 2015) by applying di®erent tools to represent the knowledge to be shared (e.g. Borsato and Peruzzini, 2015). ...
... Although concurrent development has been on the academic agenda for more than three decades (Wognum and Trienekens, 2015), practitioners still struggle to implement and use these principles (Stjepandić et al., 2015). As TE involves di®erent professional disciplines (Wognum and Trienekens, 2015;Wognum et al., 2016), practitioners operate within various working practices (Bucciarelli, 2002;Stjepandić et al., 2015), meaning that knowledge is embodied and embedded in practice (Carlile, 2002) and continuously modi¯ed (Zouari et al., 2015;Mathiasen and Koch, 2015). ...
... Although concurrent development has been on the academic agenda for more than three decades (Wognum and Trienekens, 2015), practitioners still struggle to implement and use these principles (Stjepandić et al., 2015). As TE involves di®erent professional disciplines (Wognum and Trienekens, 2015;Wognum et al., 2016), practitioners operate within various working practices (Bucciarelli, 2002;Stjepandić et al., 2015), meaning that knowledge is embodied and embedded in practice (Carlile, 2002) and continuously modi¯ed (Zouari et al., 2015;Mathiasen and Koch, 2015). This contextual knowledge implies that the use of a \knowledge transfer best-practice" approach is inappropriate. ...
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