Product Lifecycle Management (Volume 6)

This chapter gives a definition of Product Lifecycle Management (PLM), describes the PLM Paradigm, and outlines the resources in the scope of PLM. It provides a PLM background to the innovative technologies described in the following chapters.

This chapter explores the transformative potential of integrating Artificial Intelligence (AI) into Product Lifecycle Management (PLM) systems. AI's emergence as a powerful trend offers exceptional opportunities to leverage data-driven insights for enhanced decision-making, increased efficiency, and innovation. From prediction and recommendation to intelligent automation, and design process assistance, the chapter investigates the applications of AI in PLM, and presents the benefits. Considerations and challenges are also discussed. Ultimately, the chapter offers insights into the aptitude of AI in redefining the landscape of PLM encouraging organizations to embrace this dynamic partnership, as a guiding force in product development and management.

This chapter looks at the role of Big Data in the world of PLM. The concept of Big Data appeared in the 1990s, although many companies didn’t start to address the subject until later. Big Data, and the related Analytics, offer companies opportunities to rapidly manage and analyse huge volumes of data and gain deep insights. Section 3.1 introduces Big Data in the PLM environment. Section 3.2 clarifies the meaning of Big Data. Section 3.3 gives examples of Big Data across the product lifecycle. Section 3.4 of the chapter describes why it’s important to understand Big Data in the PLM environment. Section 3.5 describes opportunities available with Big Data, as well as the expected benefits and value. Section 3.6 identifies application areas of Big Data in each phase of the product lifecycle. Section 3.7 of the chapter outlines issues that arise around Big Data. Sections 3.8 and 3.9 address typical issues and success factors of Big Data projects. Section 3.10 addresses the relationship between a Big Data project and the PLM Initiative.

The international community has been aware of the climate emergency it is facing since the early 1990s, and a sustainable approach to development, including product development, clearly needs to be adopted. Tools such as the United Nation’s Sustainable Development Goals enable various players—including engineering organizations developing products—to adopt a sustainable approach to development, encourage rational resource management while minimizing adverse effects on the environment, and promote various end-of-life strategies for products. The concept of ecodesign is defined as the integration of environmental aspects into product design with the aim of reducing products’ adverse environmental impacts throughout their life cycle. Different types of ecodesign tools exist, some qualitative in nature, and others, quantitative. Some are assessment tools that focus on a single environmental impact indicator, while others look at several impact indicators over the entire product life cycle. Life cycle assessment (LCA) falls into the latter category. It is used to assess all the environmental impacts of a product or service, from raw material extraction through to ultimate product disposal. LCA makes it possible to identify the most environmentally critical aspects of a product’s life cycle so that improvements can be targeted. Therefore, ecodesign and life cycle assessment tools should help product designers make the most sustainable decisions taking LCA results into account. Since designers typically use CAD tools and PLM platforms, this chapter offers a short review of how CAD and PLM can contribute to ecodesign and LCA tool use. The review reveals that the coupling of CAD tools and LCA functionalities is promising. However, the LCA results produced are often simplified, and there are inherent problems associated with CAD and LCA data interoperability. As for PLM platforms, combining PLM and LCA also seems relevant since most of the data required to perform LCA are available from the PLM system. However, coupling LCA functionalities with a PLM solution is complex and challenging. Moreover, while ecodesign takes into account the environmental dimension of sustainable development, the social and economic dimensions are also very important, and ecodesign is far from sufficient to achieve product development that truly respects the planet’s limits.

The increasing interoperability of an organisation’s PLM system of systems affords productivity gains through the ability to share, synchronise and process data and information across the product lifecycle. This ensures a single-source-of-truth where the right data is made available at the right time to the right people and through the right mechanism. The result is better and more effective decision making. However, the sheer number of combinations and permutations of how product lifecycle data can be connected and integrated across PLM presents a considerable challenge in developing an appropriate solution architecture. Architecting solutions to this challenge is being called ‘The Digital Thread’ and in this chapter, we discuss its emergence, definition, taxonomy, benefits, technologies and practices, and how one might go about architecting a solution for an organisation.

This chapter introduces Digital Transformation, then looks at Digital Transformation from the point of view of a passenger transport company, a bus and coach operator that designs and produces some parts for its vehicles. The company’s current operations are outlined. Then, various digital technologies proposed both for the company’s vehicles and its maintenance and production facilities are described.

This chapter defines and visualises a Digital Twin and gives examples of uses of Digital Twins. It then positions Digital Twins relative to Product Lifecycle Management (PLM).

This Chapter starts with an introduction to the background and current situation of Industry 4.0. It then describes the opportunities that Industry 4.0 offers. The fourth part of the chapter looks at Industry 4.0 in relation to Product Lifecycle Management (PLM). The final part outlines some Industry 4.0 technologies.

This chapter looks at the role of the Internet of Things from the PLM viewpoint. The concept of the IoT emerged in the 1990s, although many companies didn’t start to address the subject until later. The Internet of Things, and the related Smart Products, offer companies and their customers many potential benefits. The first section of the chapter introduces the Internet of Things in the PLM environment. The second section looks, in detail, at its components. The next section describes why it’s important to understand the IoT in the PLM environment. The two following sections describe the opportunities and potential benefits of the Internet of Things. Section 9.6 of the chapter describes the potential impact of the Internet of Things in each phase of the product lifecycle. Section 9.7 outlines issues that arise around the IoT. The two following sections address typical issues and success factors of IoT projects. The final section addresses the relationship between an IoT project and the PLM Initiative.

Technological advancements of the recent decades, mainly through more powerful computer hardware and extensive software solutions, led to an exponential increase in the amount of digitally available data and have finally paved the way for the Internet of Things. In the IoT world smart devices can receive, store, and send information through internet gateways and be connected to online IoT-platforms. Consequently, companies nowadays not only face themselves in situations of managing processes, but also in managing data and information. Next to IoT, Product Lifecycle Management is a strategic approach for the integrated data and information management along a product´s lifecycle from the first idea to disposal. The synergies between IoT and PLM are evident: Through IoT devices real-time data of a product can flow directly into the PLM system and provide insights for improvements in product and process development. Both, IoT and PLM have become highly relevant subjects in today’s engineering education. This chapter dives into the fundamentals of IoT and PLM and introduces teaching methods and practical exercises for students also including the prerequisites and challenges of each exercise.

This chapter introduces the need for PLM to become a profession. It outlines the resulting benefits for industry, individual practitioners, and educational organisations. The concept of a PLM Body of Knowledge is introduced. The Professional PLM initiative, which aims to achieve a PLM profession, is described.

The Paris 2016 climate agreement has been the starting point for many companies and organizations to fight climate change and implement measures to protect the planet’s resources for future generations. The aim to reduce global warming by 1.5 °C above pre-industry levels by 2030 seems unachievable. There is a drastic economic and behavioral change needed to reach these objectives. Innovation, new products and processes, and regulations will be needed in the upcoming years. All these topics make PLM the foundational domain for a sustainable future, as it addresses the circular economy and the environmental impact of products during manufacturing, operation and compliance with more and more restrictive regulations. This chapter will focus on the major interactions between PLM and Sustainability, implying the need for digital transformation in the PLM domain.

Systems engineering concerns itself with the creation, sustainment and retirement of complex engineered systems. This chapter will go over the motivations behind systems engineering and how engineering students and practitioners should think about it. Given the challenges typically experienced in defining a field with such a large scope, the chapter proposes an axiomatic approach to delineating the domain of systems engineering. The chapter then discusses the various stages in system development lifecycle, using commercial product development process as the testbed. This is following by a discussion of some critical domain-independent knowledge that all systems engineers should possess. Finally, the increasing importance of systems concepts as a result of new technologies such as digital twins, AR/ VR, human–robot collaboration, is discussed.

The topic of Product Lifecycle Management (PLM) should be nowadays part of any engineering degree course in every university worldwide. In an increasingly digital and connected world, students and prospective engineers need to know the interrelationships of holistic product development. Excellent expertise in a discipline such as mechanical engineering is still necessary, but no longer sufficient. This article explains why this is the case and what universities can do to address this issue. It describes in detail the PLM course of the OWL University of Applied Sciences and Arts located in Lemgo, Germany. In addition, suggestions are made on how to improve the course content, based on many years of experience. As such, this article is a valuable source of information for anyone teaching PLM today or intending to do so in the future.

This is the first of three chapters of the book that look at the emergence of PLM in the twentieth century, its development in the first quarter of the twenty-first century, and its future evolution. This chapter outlines experience between 1979 and 2001 that led to identification of the scope of PLM and a corresponding definition.

This is the second of three chapters of the book that look at the emergence of PLM in the twentieth century, its development in the first quarter of the twenty-first century, and its future evolution. This chapter looks at the development of PLM between 2002 and 2023. It identifies, at a high level, the enablers and drivers of change in the PLM domain during that period.

This is the third of three chapters of the book that look at the emergence of PLM in the 20th Century, its development in the first quarter of the 21st Century, and its future evolution. This chapter looks at the future evolution of PLM after 2024.