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Big Picture of Next Generation Manufacturing

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Forecasting Next Generation Manufacturing

Part of the book series: Contributions to Management Science ((MANAGEMENT SC.))

Abstract

In our real-time Delphi survey, we present 24 projections for Next Generation Manufacturing. An international set of experts from multiple fields, e.g., engineering, information systems, social sciences, and management, evaluated these projections regarding their likelihood and their impact on manufacturing firms by the year 2030. The experts predict that in the coming decade, we will see a significant increase in the use of production data in the form of digital shadows, which will in turn shape both internal and external processes of manufacturing companies. The quantitative results of the Delphi study show that there is significant disagreement among the experts about the likelihood and impact of several of the projections. The most likely projection is the increased importance of environmental sustainability, while the least likely is the emergence of a central platform provider for Next Generation Manufacturing. The most impactful projections are those related to the roles of digital services, data sharing, hybrid intelligence, and environmental sustainability.

[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 Sebastian Pütz .

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Appendix

Appendix

Table 1 List of the 24 projections with descriptive statistics of the expert assessments

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© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Pütz, S., Van Dyck, M., Lüttgens, D., Mertens, A. (2022). Big Picture of 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_3

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