Concurrent Engineering in the 21st Century

Concurrent engineering (CE) has been a major theme in the 80s and 90s of the previous century in research and practice. Its main aim is to reduce time-to-market, improve quality and reduce costs by taking into account downstream requirements and constraints already in the design phase. While starting with a design-manufacturing alignment, gradually the CE way of thinking has been ex-tended to incorporate more lifecycle functions together with a stronger focus on and involvement of both customers and suppliers. Application of CE in practice has led to remarkable cost savings, time reduction and quality improvement. However, many failures have been reported too. Often, the complex system of CE has not been sufficiently well understood, in particular because the system that is needed to market, produce, sell, and maintain the new product, the so-called production system, has not been considered sufficiently. The particular properties of the production system that is needed to really make the new product a success need to be understood well, because they heavily influence the CE process. In this chapter a history of CE is sketched as well as its major achievements and challenges. The essentials of the system of CE are described together with the system that is designed by it: the production system. The production system, as defined in this chapter, is an encompassing system, because it also comprises functions like marketing, sales, production, and maintenance. The interaction between the two systems needs to be taken into account in all CE processes in any application domain. The chapter ends with examples of the food application area. The variety of the system of CE, in terms of different innovation efforts, is illustrated. Some important properties of the result of a CE process, a food production system, are discussed, in particular a food supply chain and its coordination for quality.

By framing complex engineering as sociotechnical systems, the concurrent engineering (CE) community can gain new insights, practices, and tools to cope with program difficulties. Todays distributed product development teams need to manage both human (organization) and technical (product and process) elements of their work. These sociotechnical elements combine in a real-world engineering program as an integrated architecture with dynamic interactions. Based on traditional representation and analysis of engineering activity, the prediction of performance can become challenging. Practices for engineering planning and ongoing management often rest upon deeply held beliefs of stability, detailed decomposability, and feasible control of related products, processes, and organization. However, while these assumptions drove collocated manufacturing during the industrial revolution, today’s engineering programs—and how the CE community considers them—have evolved. This chapter provides historical context on the evolution of systems thinking as applied to engineering and project management. Concepts are summarized as forces which reinforce and those which restrain the treatment of engineering programs as sociotechnical systems. Complexities of real world engineering programs can be considered in order to anticipate emergent outcomes driven by dynamic interaction of technical and social characteristics. This perspective is leading to a new generation of methods and practices for high performance engineering programs.

The chapter focuses on the underlying concepts of concurrent engineering technology from the point of view of concurrent process expression and its actualization. It lays out the evolution of computing platforms and networking complexity that constitute the foundation of every distributed information system required for concurrent engineering. Network integration is the working foundation for computer-based approaches to concurrent engineering. Therefore, an architecture of a concurrent engineering system is presented from the point of view of evolving methodologies of remote method invocation. Within the architecture the integration of concurrent distributed processes, humans, tools and methods to form a transdisciplinary concurrent engineering environment for the development of products is presented in the context of cooperating processes and their actualization. To work effectively in large, distributed environments, concurrent engineering teams need a service-oriented programming methodology along with a common design process, domain-independent representations of designs, and general criteria for decision making. Evolving domain-specific languages (DSLs) and service-oriented platforms reflect the complexity of computing problems we are facing in transdisciplinary concurrent engineering processes. An architecture of a service-oriented computing environment (SORCER) is described with a service-oriented programing and a coherent operating system for transdisciplinary large-scale computing.

Requirements engineering (RE) is the key to success or failure of every product, service or system development project, understanding the development results as the implementation of the specific set of requirements. A good requirements definition is thus the prerequisite for high-quality solutions and reduces the cost of change, both of prototypes and production tools, and ultimately the warranty costs. However, RE for system development is more and more challenged by two interrelated trends: the increasing complexity of systems and the responsibility of the provider for the whole system life cycle. Thus, from a systems engineering point of view, RE has to define requirements for a rising amount of tangible and intangible components from a growing number of different stakeholders. Additionally, RE has to take into account requirements from every stage of the system life cycle and feed the results back to the development process. Many organizations are still missing effective practices and a documented RE process to tackle the upcoming challenges in systems engineering. This chapter aims at giving an overview on the RE context and challenges for systems engineering and subsequently describes the state-of-the-art for structuring and processing requirements. Furthermore, two case studies illustrate the current situation and methods for resolution in industry and show how the identified challenges can be met by IT support. Finally, future trends and needs for RE research and its further integration with concurrent engineering and life cycle management approaches are outlined.

To face an increasingly competitive environment within a globalization context, and to focus on core high-added value business activities, enterprises have to establish partnerships with other companies specialized in complementary domains. Such an approach, primarily based on optimization of the value chain, is called virtualization of the Enterprise. Enterprises relying on virtualization, sub-contracting and outsourcing have to coordinate activities of all the partners, to integrate the results of their activities, to manage federated information coming from the different implied information systems and to re-package them as a product for the clients. The adopted organization, which is considering as well as the internal and external resources, is called “Extended Enterprise”. Nevertheless, in such complex emerging networked organizations, it is more and more challenging to be able to interchange, to share and to manage internal and external resources such as digital information, digital services and computer-enacted processes. In addition, digital artifacts produced by enterprise activities are more and more heterogeneous and complex. After characterizing expected interoperability for collaborative platform systems and highlighting interoperability issues and brakes not yet addressed, this chapter describes an innovative approach to build interoperability based on a Federated Framework of legacy eBusiness standards of a given ecosystem. It implies facing important issues related to semantic preservation along the lifecycle of the artifacts and infrastructures required to define and exploit an application. We present two use case studies that apply interoperability strategies.

Collaborative Engineering is the practical application of collaboration sciences to the engineering domain. Its aim is to enable engineers and engineering companies to work more effectively with all stakeholders in achieving rational agreements and performing collaborative actions across various cultural, disciplinary, geographic and temporal boundaries. It has been widely applied to product design, manufacturing, construction, enterprise-level collaboration and supply chain management. The present chapter clarifies the main concepts around Collaborative Engineering, as well as the various forms of collaborative ventures, such as virtual enterprises. It underlies the crucial impact of Collaborative Engineering in the context of global distributed engineering. The most applied forms of technology for collaboration are presented, such as Computer Supported Collaborative Design (CSCD) and web-based design, which are mature fields of study in constant improvement, as collaborative tools and cloud-based systems become more pervasive. The application of Collaborative Engineering in the context of product lifecycle is also discussed, and different needs for collaboration are evidenced along successive steppingstones of product development. Two case studies are provided to illustrate successful application of the concepts hereby provided.

Following the introduction of systems thinking concepts in Chap. 3, we demonstrate here the treatment of complex engineering projects as sociotechnical systems in practical engineering practice. This approach, called Project Design, enables concurrent engineering (CE) teams to foresee the influence of project architecture, behaviors, dependencies, and complexity on emergent performance, thereby reducing the occurrence of unpleasant surprises. We have seen in multiple industrial cases this method as a source of new thinking and practices relevant to CE, with supporting tools and processes. Past assumptions about standard work practices may be tested, including such factors as degree of concurrency, phasing, roles, technology decomposition, system interfaces, and risk and its reduction. If embedded behaviors, in interplay with the total project architecture, lead to surprising negative or positive performance, the design of the engineering project as a sociotechnical system begins with un-learning, then awareness, and then learning of the project approaches more likely to produce positive results. The design of concurrency is specific to the nature of the social and technical elements of the system and its architecture.

Unlike the first cars, which essentially have been mechanical systems, nowadays cars have become very complex mechatronic systems that integrate sub-systems created in a synergy between people from different domains such as mechanical engineering, software engineering and electric and electronics (E/E). This fact has increased product complexity in the last decades and therefore the product development complexity. Complexity is multidimensional and consists of product, process, organizational, market as well as use complexity. A methodology for mastering complexity is Systems Engineering, which actually means applying systems thinking to tackle the challenges of creating complex products. The focus of this chapter is providing a deep understanding of systems engineering (SE) as well as a rough recommendation for companies that might be interested in implementing SE. Thus concepts for implementation are proposed. As an entry point, the context of product creation is presented with the challenges that are linked to. The need of appropriate methods is emphasized and the application of SE is motivated. In order to present SE as it is applied in the practice, SE processes are described in detail and the artifacts of the different steps are highlighted. For performing the processes described, SE tools and methods are presented. The important role that the company organization and the project management both play for SE projects as well as SE success factors are highlighted. Additionally, a proposal for an introduction process for SE is elaborated. A selection of functional features that can provide a cutting-edge advantage when practicing SE are presented and discussed. Two case studies are illustrated in order to provide real applications of SE and therefore an additional orientation for SE implementation. The relation between SE and Concurrent Engineering is addressed and some future challenges of SE are identified.

The handling of knowledge represents the key to competitiveness, with company-specific product and process knowledge marking a unique position with respect to competition. Knowledge-based engineering (KBE) is a comprehensive application of artificial intelligence in engineering. It facilitates new product development by automating repetitive design tasks through acquisition, capture, transform, retention, share, and (re-)use of product and process knowledge. The idea behind KBE is to store engineering knowledge once by suitable, user friendly means and use it whenever necessary in a formal, well documented, repeatable and traceable process. It works like design automation. This chapter begins with the definition of knowledge in an engineering context and subsequently addresses the state-of-the-art in KBE research. Three particular areas of research are discussed in detail: knowledge structuring, maintainability of knowledge and KBE applications, and the technological progress and weaknesses of commercial KBE applications like KBE templates. From case study examples, various recent developments in KBE research, development and industrial exploitation are highlighted. By the resulting sequence optimization of the design process a significant time saving can be achieved. However, there are still notable drawbacks such as the complexity of KBE implementation and the adaptability of developed applications that need to be researched and solved. A view on KBE systems within the Concurrent Engineering context is synthesized, leading to the identification of future directions for research.

When products are developed in 3D using engineering applications, the data is initially stored in the native format of the used CAD software. If this 3D CAD data is to be shared with people who do not have this software or to be consolidated with visualization data from other sources, neutral 3D formats are needed. For visualization of product data in the engineering field—regardless of native CAD formats—a plethora of 3D formats are available. Among these are disclosed or standardized formats like PDF from Adobe, JT and also X3D, Collada and STEP. The choice of a format has many implications, including the options available for using the data and the resulting follow-up costs. For this reason product lifecycle visualization is a rising discipline for product lifecycle management. This chapter provides an overview of the industrial challenge, technical background and standardization, typical applications, and evaluation and testing in the field of engineering visualization with neutral 3D formats. The chapter is completed by assessment approach for 3D formats and examples from the industrial practice in various fields.

One of the most time-consuming aspects of creating 3D virtual models is the generation of geometric models of objects, in particular if the virtual model is derived (digitized) from a physical version of the object. A variety of commercially available technologies can be used to digitize objects at the molecular scale but also multi-storey buildings or even planets and stars. The process of 3D digitizing basically consists of a sensing phase followed by a rebuild phase. The sensing phase collects or captures raw data and generates initial geometry data, usually as a 2D boundary object, or a 3D point cloud. Sensing technologies are based on tracking, imaging, and range finding or their combination. The rebuild phase is internal processing of data into conventional 3D CAD and animation geometry data, such as NURBS and polygon sets. Finally, in most cases, the digitized objects must be refined by using the CAD software to gain CAD models of optimal quality which are needed in the downstream processes. Leading CAD software packages include special modules for such tasks. Many commercial vendors offer sensors, software and/or complete integrated systems. Reverse engineering focuses not only on the reconstruction of the shape and fit, but also on the reconstruction of physical properties of materials and manufacturing processes. Reverse engineering methods are applied in many different areas, ranging from mechanical engineering, architecture, cultural heritage preservation, terrain capture, astronomy, entertainment industry to medicine and dentistry.

Product development in the mobility industry is characterized by extreme time-to-market, high product complexity, cost pressure and many geographically dispersed stakeholders. Thus, efficient control mechanisms are necessary to manage a seemingly unmanageable project successfully and to achieve a strong finish. Digital mock-up (DMU) serves, as a central validation instrument in such a complex scenario, not only to visualize spatially the current status of the virtual product but also to evaluate the project’s progress. In conjunction with a high-variant product structure, as it is the case in modern vehicles, the use of DMU makes the check of the spatial consistency of the overall product possible, taking over what today’s CAD and PDM systems alone are not capable of. Taking the function of the product into account, the result is the so-called functional DMU (FDMU) which aims at facilitating the direct experience of functions on the virtual model in the overall context of the product. While DMU offers a visual straightforward human interface for control, DMU creation, calculation and processes can be automated well, so that the spatial test (collision check, assembly check) can be performed for all conceivable product variants in batch during the night). Nevertheless, human intervention is still required for the solution of design conflicts. Although all current problems are not yet solved in the context of DMU, leading PLM vendors do offer powerful tools to support the DMU process. Due to its central role in the development process DMU is subject of intensive research and development for speeding up the process and to increase accuracy.

The paradigm of modularity has emerged as a relevant way to meet customer requirements with a wide range of variety and customisation of products, from unique to standard ones. The modularity area is becoming increasingly multidisciplinary, which implies holistic and articulated concurrent engineering approaches. Modularity can intersect technical aspects with the business aspects. The use of modular technology has wide-reaching implications for any design and development company that undertake to use this paradigm. This chapter provides a framework for understanding the modularity in the context of concurrent engineering. It involves design for modularity as well as management of modularity. Theoretical and practical development of consistent modular methods, their implementation technologies and tools for mass customization and product configuration are examined. Some of the possible implications of these developments are presented from concurrent engineering point of view. The current trend is drawn toward usage and integration of different technologies such as advanced CAD systems, product configurators, agent-based systems and PDM systems. Three particular application areas with industrial use cases are presented. A discussion about research challenges and further developments closes this chapter.

Multidisciplinary design optimization (MDO) has been a field of research for 25 years. It refers to the formulation of the design problem in mathematical models and applying optimization techniques to find the minimum or maximum of a predefined objective function, possibly subject to a set of constraints. MDO has become an important tool in concurrent engineering (CE), with the ability to handle many design variables (DV) across various disciplines. Advances in computer technologies and software engineering have facilitated the practical application of MDO in industry, including aerospace, automotive, shipbuilding, etc. However, active research and development in MDO continues. The creative input of the human designer to the design process is critical and must be integrated in the MDO process. For MDO to be effective in the design of modern complex systems it must also incorporate non-technical disciplines, such as finance, environment, operational support, etc. It remains a challenge to do model them with adequate fidelity. Simulations and analytical models have imbedded assumptions, inaccuracies and approximations. How do we deal with these in an MDO environment? This chapter gives an introduction to MDO with an historical review, a discussion on available numerical optimization methods each with their specific features, the various MDO architectures and decompositions and two case studies where MDO has been applied successfully.

Product lifecycle management (PLM) is widely understood as concept for the creation, storage, and retrieval of data, information and, ideally, knowledge throughout the lifecycle of a product from its conceptualization or inception to its disposal or recovery. PLM is seen in industry as one of the core concepts to fulfill a number of business requirements in the manufacturing industry with respect to completeness, high transparency, rapid accessibility, and high visibility of all product data during a product’s lifecycle. Those requirements are related to financial aspects such as cost management and revenue growth; to the product itself like innovation, time to market, quality, and high productivity; and to regulatory aspects such as compliance and documentation. PLM is implemented by deploying IT systems such as product data management (PDM) systems and induces a high level of interoperability of related applications. With PLM, industrial companies attempt to gain advantages in shorter cycles, lower costs, better quality by avoiding errors, and misunderstanding. After reviewing basic concepts and building blocks of PLM, we provide empirical evidence of implementation scenarios and use case studies for different integrations to build up PLM solutions. We have evaluated applications in automotive, aerospace and consumer electronic industries focused on engineering design, change management, simulation data management integration and communication with partners. Emphasis is on the organizational and IT implications and the business benefit of the provided solutions.

The global market, different and changing environmental laws, the customer wish for individualization, time-to-market, product costs, and the pressure on manufacturers to discover new product niches, to name only a few variability drivers, result in an ever increasing number of product variants in nearly all engineering disciplines as, for example, in car manufacturing. Mastering the related increasing product complexity throughout the whole product lifecycle is and remains one of the key advantages in competition for the future. Currently for a manufacturer, as for any other discipline, it is no option not to invest in an efficient and effective variability handling machinery able to cope with the arising challenges. Not only the task to invent, develop, introduce and manage new variants is important but also to decide which variant to develop, which to remove and which to not develop at all. The consequences of such decisions with respect to product-line variability have to be computed based on formalized bases such that an optimized product variability can assure on the one hand customer satisfaction and on the other hand cost reduction within the variability-related engineering processes. This chapter presents current research in the field of product variability configuration, analysis and visualisation. It presents solution sketches based on formal logic that were illustrated by some real world examples.

With the growth of the knowledge-based economy, intellectual property right (IPR) is recognized as a key factor to develop and protect strategic competitiveness and innovation of an enterprise. The increasing degree of collaboration in global relationships, ubiquitous digital communication techniques as well as tough competition has lead to an increasing importance of intellectual property protection (IPP) for enterprises. Since the law as well as ethical principles are not always adhered to, there are increasingly activities outside legal understanding. This situation is exacerbated in the context of rising crime through the misuse of modern ICT technologies (“Cyber Crime”) and now employs extensively state authorities. Piracy, counterfeits and unwanted know-how drain pose a significant problem for each market leader. Intellectual property is stored in product data too. Especially modern parametric and feature-based 3D-CAD systems have been enhanced towards acquiring, representing, processing and distributing knowledge to support knowledge-based engineering (KBE) within virtual product creation. However, it is very easy to exchange huge amounts of product data within a virtual enterprise that comprises an enterprise with its supplier network. There is an enormous threat that intellectual property could fall into the wrong hands and badly jeopardize the existence of the related company. This chapter contains an analysis of this conflict area, a picture of the legal framework, a discussion on the need for action in supply chain networks and attempts by research and development as well as best practices in industry for various aspects of IPP in the context of concurrent engineering (CE).

Today, the methods of model based product development are well-recognized and wide spread, at least, in the automotive industry as well as in the aerospace industry and their suppliers. But, current challenges of these industries like light weight design, electro mobility, modern mobility concepts plus those caused by rising product complexity bring this concept to its limits. An overall approach is progressively requested, which is able to continuously integrate requirements, functions, logic and physical product descriptions (RFLP). This should be possible not only for mechanical aspects but also for electronics and software development. The approach of system engineering addresses the continuous availability and linkage of product information. This concept, which is well-known in the aerospace industry for a long time, is only recently used in automotive industry. An example is the use of integrated development environments. Nonetheless, the realization of this concept in an automotive company is definitely a challenge. Examples for these problems are differently coined. Examples are detailed requirements (client requirements versus requirements to a complete vehicle and to components properties), consideration of configuration, validity and maturity, complexity management (complete vehicle to component, vertical integration, plus integration of early concept phases over development, verification, clearance to the production start-up, horizontal integration) and multi-disciplinarity (mechanics with calculation, electronics and software). The realization of systems engineering does not only create high demands to the design of the process-IT (authoring systems, TDM and PDM), but also has to consider organizational aspects (process and structure organization, integration of development partners and suppliers). Frequent acquisitions under IT system vendors, especially, in the CAD/PLM/CAE market as well as the selection of the systems for functional and economical aspects lead to increased requirements concerning open interfaces. In the present document, findings and experiences from the introduction of systems engineering for automotive processes are described. Effects on the process IT architecture are outlined. “Lessons learned” and necessary changes in process-IT, in form of selected examples and solution alternatives, are discussed.

With the increasing size and complexity of development projects at large companies and organizations in the aviation industry, concurrent engineering (CE) and integrated aircraft design has become of crucial importance in the design process of new products. In order to remain a competitive position and achieve a customer driven approach, aspects of the product’s life cycle should be adopted at an early stage in the design process. These aspects include, among others: the overall cost performance and the ability of new system integration. This chapter discusses the implementation of CE in the life cycle of aircraft and systems in general. Challenges related to process parallelization and multidisciplinary design, involving the exchange of knowledge and information throughout the design process, are covered. Supporting techniques along with practical case studies are presented to illustrate the implementation of CE and IAD in real life. Expected future developments with respect to CE as applied to aviation conclude this chapter.

The automotive industry is one of the most advanced industries using information technologies for product development. The product variety and complexity have grown dramatically over the last decades. These enhancements could only be achieved by using the full range of technologies and methods described in part two. Within automotive engineering companies are continuously looking for new ways to achieve economic growth. Trends show that this is often done by expansion of existing markets as well as entering new markets, providing niche products and increasing productivity. This effects significantly the continuous development of processes and IT solutions. Legacy Systems have to be integrated with modern solutions. Service oriented architectures (SOA) and semantic nets will lead to a new system landscape. This change is not only a technical one but  also an organizational paradigm shift which has to be handled carefully. To establish an international, multi-company concurrent engineering process, a common understanding of processes and business objects is required. The most efficient way to do this is standardization. The “Code of PLM Openness” (CPO) helps to find a common definition which lead to a better understanding of system integration and usage of standards. Two Standards play a significant role: ISO 10303 (STEP) with its new application protocol 242 which combines the known protocols for automotive and aerospace including model based system engineering and ISO 14306 (JT) for DMU and geometrical collaboration. The continuous enhancements of CAD systems lead to a knowledge-based engineering (KBE) approach by handling parametrics and associativity.

Application of concurrent engineering (CE) to machinery has to consider the type of production (individual, serial), product complexity and level of design. Product development (PD) involves four characteristic levels of design that requires specific activities. The characteristic design levels require definitions of the activities for providing the necessary software and other support for all phases of the design process. The following four levels of the design process have become established in the professional literature: original, innovative, variation and adaptive. Systematic analyses of product development processes (PDP), workflows, data and project management, in various companies, has shown that specific criteria have to be fulfilled for CE to be managed well. It is very important to consider the involvement of customers and suppliers, communication, team formation, process definition, organisation, and information system to fulfil minimum threshold criteria. The quality of communication and team formation, for example, primarily affects the conceptual phase. An information system is useful predominantly in the second half of the design process. It is shown with typical examples what is important in each PD phase. In the second part of this chapter reference models for CE methods are presented for PD in individual production (CE—DIP), in serial production of modules or elements (CE—DSPME) and in the manufacture of mass products (CE—DMMP) with an example from household appliances. The reference models for CE methods map PD phases and CE criteria for each type of production and have to be used together with case studies. They help to recognise strong and weak points of a CE application and show a way to improve processes and supporting CE methods.

The shipbuilding process generally consists of concept and preliminary design, basic design, detailed design, production design and production. Design information is generated in each phase to shape products and operations in the shipyard. For each process the design activities are carried out with a high level of concurrency supported by various computer software systems, though quality of products and efficiency of the concurrent development process highly depend on experiences and insights of skilled experts. The detailed design information is difficult to be shared and design conflicts are solved in a common effort by design engineers in downstream design stages. Data sharing across design sections and simulation of the construction process to predict time and cost are the key factors for concurrent engineering (CE) in shipbuilding industry. The CE process in shipbuilding will be getting more and more accurate and efficient along with accumulation of design knowledge and simulation results. This chapter gives insight into the different phases of the shipbuilding product creation process and demonstrates practical usage through typical, comprehensive use cases from design and manufacturing. Finally, it draws some expected future directions for CE in shipbuilding.

Product design and development (PDD) has shifted its focus from addressing functional and technological issues to user-centric and consumer-oriented concerns in recent years. More specifically, the experiential aspect of design has taken a crucial role in creating more consumer-focused products. Often, customer research or user-involvement studies are conducted to explore necessary knowledge and gain an insight into user experience. Unlike functional requirements, experiential customer requirements are usually more tacit, latent and complex. As such, the issues concerning user experience exploration in consumer goods design deserve more attention. These will be the focus of this chapter. In this regard, a prototype context-based multi-sensory experience system (CMSES) with a scenario co-build strategy (SCS) is proposed to facilitate user experience exploration in designing consumer goods. A three-stage case study is employed to illustrate the proposed prototype system. Potential of the proposed approach in the context of concurrent engineering (CE) and collaborative product development (CPD) is discussed.

With the research presented in this chapter we aim to investigate the importance of the concurrent engineering (CE) philosophy in the engineering-medical multidisciplinary environment for integrated product development process (IPDP) of medical equipment. We address the requirements of a health professional user as well as patient’s needs. We have identified and contextualized the medical equipment lifecycle, the importance of CE in the IPDP of medical equipment and present propositions for the insertion of software tools that support product development phases. A discussion is included on the use of CE and IPDP oriented towards medical equipment conception and development, perspectives of engineering modular development and interface between Health and Engineering information areas for increasing technical, clinical and economic quality.

Countries and government regions are promoting renewable energy to effectively reduce carbon emissions. However, the carbon footprint of a given industry in a specific region is hard to measure and the long-term effect of an untested green policy for carbon reduction is difficult to predict. This chapter introduces an approach that combines economic input-output life cycle assessment (EIO-LCA) and a location quotient (LQ) to measure regional carbon footprints using local environmental and industrial data. The results enable government policy makers to accurately formulate policies that target critical contributors while simulating the economic impact using system dynamics (SD) modeling. In the case study, policy scenarios are simulated to evaluate the time-varying impacts of proposed green transportation strategies for Taiwan’s low carbon island (Penghu Island) pilot project. The methodology provides a generalized tool for green energy policy assessment. This chapter is the extension of the original research reported by the authors in Trappey et al. (Energy Policy 45:510-515 [1], Concurrent engineering approaches for sustainable product development in a multi-disciplinary environment. Springer, London, pp. 367–377 [2]).

Considering sustainable mobility, the electrical powertrain of road vehicles has an increasingly significant role. Besides delivering benefits in air and noise pollution, it encompasses huge challenges in practical usability, reliability and total costs of ownership combined with novel models of exploitation. Therefore, sustainable mobility is a typical field of application for Concurrent Engineering. The design of electric vehicles requires bringing components from different domains together in order to integrate them in the overall vehicle concept. The domains involved utilize their own specific methods, processes as well as software tools in order to create partial models of an overall system. This leads to dependencies between several disciplines and, therefore, to the need to track the impact of model interactions to avoid data inconsistency as well as design errors. The focus of this paper lies on the project “Process Chain Battery Module” that has been conducted at EDAG Engineering AG to capture the challenges related to the electrical battery when designing electric vehicles. Thermal management, which is one of the critical challenges to be tackled in the area of electro mobility, is discussed and solution approaches are presented. Requirements are defined and linked with functional analysis as well as geometrical, behavioral and FEM models. Thus, changes can be traced from each partial model back to the initial requirements. Interface management between the domains and partial models is realized to enable an analysis of the entire vehicle. Complex simulations are performed in a very early stage of development in order to determine the range of an e-vehicle model (EDAG Light Car).

Despite a long pedigree and many positive reports on its use and benefits, concurrent engineering (CE) and its associated research (sub)domains still experience significant development. In this final chapter, a socio-technical framework is applied to classify and analyze challenges identified as part of the foundations, methods and applications discussed in this book. Existing properties and means of CE are abstracted. Subsequently, the main trends and developments in CE research and practice are discussed, followed by expectations for the future. Findings and trends have been identified for strategic issues visible in product requirements and product portfolios, stakeholders including companies involved, multiple functions and disciplines, current and future technologies that are expected to solve at least some of the existing problems, knowledge and skills as brought by people and teams, and structures necessary for making collaboration work, while dealing also with the still very difficult cultural differences. As the chapter shows, CE as a concept is very much alive, requiring even more advanced tools, techniques and methods to contribute to less waste in resources and efforts world-wide and improve quality.