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Capability Configuration in Next Generation Manufacturing

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Forecasting Next Generation Manufacturing

Abstract

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.

[Abstract generated by machine intelligence with GPT-3. No human intelligence applied.]

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Acknowledgment

Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC-2023 Internet of Production – 390621612.

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Correspondence to Christian Hinke .

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Hinke, C. et al. (2022). Capability Configuration in Next Generation Manufacturing. In: Piller, F.T., Nitsch, V., Lüttgens, D., Mertens, A., Pütz, S., Van Dyck, M. (eds) Forecasting Next Generation Manufacturing. Contributions to Management Science. Springer, Cham. https://doi.org/10.1007/978-3-031-07734-0_6

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