TY - CHAP A1 - Leicht-Scholten, Carmen A1 - Steuer-Dankert, Linda T1 - Educating engineers for socially responsible solutions through design thinking T2 - Design thinking in higher education: interdisciplinary encounters N2 - There is a broad international discussion about rethinking engineering education in order to educate engineers to cope with future challenges, and particularly the sustainable development goals. In this context, there is a consensus about the need to shift from a mostly technical paradigm to a more holistic problem-based approach, which can address the social embeddedness of technology in society. Among the strategies suggested to address this social embeddedness, design thinking has been proposed as an essential complement to engineering precisely for this purpose. This chapter describes the requirements for integrating the design thinking approach in engineering education. We exemplify the requirements and challenges by presenting our approach based on our course experiences at RWTH Aachen University. The chapter first describes the development of our approach of integrating design thinking in engineering curricula, how we combine it with the Sustainable Development Goals (SDG) as well as the role of sustainability and social responsibility in engineering. Secondly, we present the course “Expanding Engineering Limits: Culture, Diversity, and Gender” at RWTH Aachen University. We describe the necessity to theoretically embed the method in social and cultural context, giving students the opportunity to reflect on cultural, national, or individual “engineering limits,” and to be able to overcome them using design thinking as a next step for collaborative project work. The paper will suggest that the successful implementation of design thinking as a method in engineering education needs to be framed and contextualized within Science and Technology Studies (STS). Y1 - 2020 SN - 978-981-15-5780-4 U6 - http://dx.doi.org/10.1007/978-981-15-5780-4 SP - 229 EP - 246 PB - Springer CY - Singapore ER - TY - CHAP A1 - Brauner, Philipp A1 - Vervier, Luisa A1 - Brillowski, Florian A1 - Dammers, Hannah A1 - Steuer-Dankert, Linda A1 - Schneider, Sebastian A1 - Baier, Ralph A1 - Ziefle, Martina A1 - Gries, Thomas A1 - Leicht-Scholten, Carmen A1 - Mertens, Alexander A1 - Nagel, Saskia K. T1 - Organization Routines in Next Generation Manufacturing T2 - Forecasting Next Generation Manufacturing N2 - Next Generation Manufacturing promises significant improvements in performance, productivity, and value creation. In addition to the desired and projected improvements regarding the planning, production, and usage cycles of products, this digital transformation will have a huge impact on work, workers, and workplace design. Given the high uncertainty in the likelihood of occurrence and the technical, economic, and societal impacts of these changes, we conducted a technology foresight study, in the form of a real-time Delphi analysis, to derive reliable future scenarios featuring the next generation of manufacturing systems. This chapter presents the organization dimension and describes each projection in detail, offering current case study examples and discussing related research, as well as implications for policy makers and firms. Specifically, we highlight seven areas in which the digital transformation of production will change how we work, how we organize the work within a company, how we evaluate these changes, and how employment and labor rights will be affected across company boundaries. The experts are unsure whether the use of collaborative robots in factories will replace traditional robots by 2030. They believe that the use of hybrid intelligence will supplement human decision-making processes in production environments. Furthermore, they predict that artificial intelligence will lead to changes in management processes, leadership, and the elimination of hierarchies. However, to ensure that social and normative aspects are incorporated into the AI algorithms, restricting measurement of individual performance will be necessary. Additionally, AI-based decision support can significantly contribute toward new, socially accepted modes of leadership. Finally, the experts believe that there will be a reduction in the workforce by the year 2030. Y1 - 2022 SN - 978-3-031-07734-0 U6 - http://dx.doi.org/10.1007/978-3-031-07734-0_5 SP - 75 EP - 94 PB - Springer CY - Cham ER - TY - CHAP A1 - Hinke, Christian A1 - Vervier, Luisa A1 - Brauner, Philipp A1 - Schneider, Sebastian A1 - Steuer-Dankert, Linda A1 - Ziefle, Martina A1 - Leicht-Scholten, Carmen T1 - Capability configuration in next generation manufacturing T2 - Forecasting next generation manufacturing : digital shadows, human-machine collaboration, and data-driven business models N2 - Industrial production systems are facing radical change in multiple dimensions. This change is caused by technological developments and the digital transformation of production, as well as the call for political and social change to facilitate a transformation toward sustainability. These changes affect both the capabilities of production systems and companies and the design of higher education and educational programs. Given the high uncertainty in the likelihood of occurrence and the technical, economic, and societal impacts of these concepts, we conducted a technology foresight study, in the form of a real-time Delphi analysis, to derive reliable future scenarios featuring the next generation of manufacturing systems. This chapter presents the capabilities dimension and describes each projection in detail, offering current case study examples and discussing related research, as well as implications for policy makers and firms. Specifically, we discuss the benefits of capturing expert knowledge and making it accessible to newcomers, especially in highly specialized industries. The experts argue that in order to cope with the challenges and circumstances of today’s world, students must already during their education at university learn how to work with AI and other technologies. This means that study programs must change and that universities must adapt their structural aspects to meet the needs of the students. Y1 - 2022 SN - 978-3-031-07733-3 U6 - http://dx.doi.org/10.1007/978-3-031-07734-0_6 SP - 95 EP - 106 PB - Springer CY - Cham ER - TY - CHAP A1 - Fateri, Miranda A1 - Gebhardt, Andreas T1 - Introduction to Additive Manufacturing T2 - 3D Printing of Optical Components N2 - Additive manufacturing (AM) works by creating objects layer by layer in a manner similar to a 2D printer with the “printed” layers stacked on top of each other. The layer-wise manufacturing nature of AM enables fabrication of freeform geometries which cannot be fabricated using conventional manufacturing methods as a one part. Depending on how each layer is created and bonded to the adjacent layers, different AM methods have been developed. In this chapter, the basic terms, common materials, and different methods of AM are described, and their potential applications are discussed. KW - Additive manufacturing KW - 3D printing KW - Digital manufacturing KW - Rapid prototyping KW - Rapid manufacturing Y1 - 2020 SN - 978-3-030-58960-8 U6 - http://dx.doi.org/10.1007/978-3-030-58960-8_1 SP - 1 EP - 22 PB - Springer CY - Cham ER - TY - CHAP A1 - Butenweg, Christoph A1 - Holtschoppen, Britta T1 - Seismic design of structures and components in industrial units T2 - Structural Dynamics with Applications in Earthquake and Wind Engineering N2 - Industrial units consist of the primary load-carrying structure and various process engineering components, the latter being by far the most important in financial terms. In addition, supply structures such as free-standing tanks and silos are usually required for each plant to ensure the supply of material and product storage. Thus, for the earthquake-proof design of industrial plants, design and construction rules are required for the primary structures, the secondary structures and the supply structures. Within the framework of these rules, possible interactions of primary and secondary structures must also be taken into account. Importance factors are used in seismic design in order to take into account the usually higher risk potential of an industrial unit compared to conventional building structures. Industrial facilities must be able to withstand seismic actions because of possibly wide-ranging damage consequences in addition to losses due to production standstill and the destruction of valuable equipment. The chapter presents an integrated concept for the seismic design of industrial units based on current seismic standards and the latest research results. Special attention is devoted to the seismic design of steel thin-walled silos and tank structures. KW - Industrial units KW - Seismic design KW - Tanks KW - Silos KW - Components Y1 - 2019 SN - 978-3-662-57550-5 U6 - http://dx.doi.org/10.1007/978-3-662-57550-5_5 SP - 359 EP - 481 PB - Springer CY - Berlin ER - TY - CHAP A1 - Giresini, Linda A1 - Butenweg, Christoph T1 - Earthquake resistant design of structures according to Eurocode 8 T2 - Structural Dynamics with Applications in Earthquake and Wind Engineering N2 - The chapter initially provides a summary of the contents of Eurocode 8, its aim being to offer both to the students and to practising engineers an easy introduction into the calculation and dimensioning procedures of this earthquake code. Specifically, the general rules for earthquake-resistant structures, the definition of design response spectra taking behaviour and importance factors into account, the application of linear and non-linear calculation methods and the structural safety verifications at the serviceability and ultimate limit state are presented. The application of linear and non-linear calculation methods and corresponding seismic design rules is demonstrated on practical examples for reinforced concrete, steel and masonry buildings. Furthermore, the seismic assessment of existing buildings is discussed and illustrated on the example of a typical historical masonry building in Italy. The examples are worked out in detail and each step of the design process, from the preliminary analysis to the final design, is explained in detail. KW - Seismic design KW - Eurocode 8 KW - Design examples KW - Response spectrum KW - Pushover analysis Y1 - 2019 SN - 978-3-662-57550-5 (Online) SN - 978-3-662-57548-2 (Print) U6 - http://dx.doi.org/10.1007/978-3-662-57550-5_4 SP - 197 EP - 358 PB - Springer CY - Berlin ER - TY - CHAP A1 - Gebhardt, Andreas A1 - Hoetter, Jan-Steffen T1 - Rapid Tooling T2 - CIRP Encyclopedia of Production Engineering Y1 - 2019 SN - 978-3-662-53120-4 U6 - http://dx.doi.org/10.1007/978-3-662-53120-4 SP - 39 EP - 52 PB - Springer CY - Berlin, Heidelberg ER - TY - CHAP A1 - Bozakov, Zdravko A1 - Sander, Volker T1 - OpenFlow: A Perspective for Building Versatile Networks T2 - Network-Embedded Management and Applications Y1 - 2013 SN - 978-1-4419-6769-5 U6 - http://dx.doi.org/10.1007/978-1-4419-6769-5_11 SP - 217 EP - 245 PB - Springer CY - New York, NY ER - TY - CHAP A1 - Ibanez-Sanchez, Gema A1 - Wolf, Martin T1 - Interactive Process Mining-Induced Change Management Methodology for Healthcare T2 - Interactive Process Mining in Healthcare N2 - The adoption of the Digital Health Transformation is a tremendous paradigm change in health organizations, which is not a trivial process in reality. For that reason, in this chapter, it is proposed a methodology with the objective to generate a changing culture in healthcare organisations. Such a change culture is essential for the successful implementation of any supporting methods like Interactive Process Mining. It needs to incorporate (mostly) new ways of team-based and evidence-based approaches for solving structural problems in a digital healthcare environment. KW - Methodology KW - Change culture KW - Lean thinking KW - Interactive process mining KW - Objective data Y1 - 2020 SN - 978-3-030-53993-1 (Online) SN - 978-3-030-53992-4 (Print) U6 - http://dx.doi.org/10.1007/978-3-030-53993-1_16 SP - 267 EP - 293 PB - Springer CY - Cham ER - TY - CHAP A1 - Altherr, Lena A1 - Leise, Philipp T1 - Resilience as a concept for mastering uncertainty T2 - Mastering Uncertainty in Mechanical Engineering Y1 - 2021 SN - 978-3-030-78353-2 U6 - http://dx.doi.org/10.1007/978-3-030-78354-9 N1 - Unterkapitel 6.3.1 des Kapitels "Strategies for Mastering Uncertainty" SP - 412 EP - 417 PB - Springer CY - Cham ER -