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Changeable Manufacturing: A Comparative Study of Requirements and Potentials in Two Industrial Cases

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Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems (APMS 2021)

Abstract

Today’s global manufacturing environment is characterized by intense competition in dynamic and uncertain markets. Consequently, manufacturers are required to accommodate a higher variety of products with frequent new introductions and shorter life-cycles in a rapid and cost-efficient way, to sustain competitiveness. In light of these requirements, changeable manufacturing systems appear promising. However, empirically founded research is limited in regard to how different requirements lead to different applications and resulting potentials in various industrial settings. Therefore, this paper presents a comparative study of requirements, enablers, and potentials of changeability in two industrial cases (i) a Danish manufacturer of capital goods for the energy sector, (ii) a Danish manufacturer of sporting goods for the maritime sector. The objective of the paper, is to generate insights which can support various industrial settings in the transition towards changeable manufacturing. Findings include: (i) in high-volume contexts, reconfigurability is suitable to accommodate a production mix with increasing dimensions of parts, with potential to improve equipment utilization to reduce capital expenses (ii) in global manufacturing contexts, reconfigurability is suitable to accommodate frequent changes of production location, with potential to improve demand proximity to gain a competitive advantage.

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Acknowledgements

The research presented in this paper is supported by the REKON research project and the MADE research program. REKON is funded by the Danish Industry Foundation and MADE is funded by the Innovation Fund Denmark.

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Correspondence to Stefan Kjeldgaard .

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Kjeldgaard, S., Napoleone, A., Andersen, AL., Brunoe, T.D., Nielsen, K. (2021). Changeable Manufacturing: A Comparative Study of Requirements and Potentials in Two Industrial Cases. In: Dolgui, A., Bernard, A., Lemoine, D., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. APMS 2021. IFIP Advances in Information and Communication Technology, vol 631. Springer, Cham. https://doi.org/10.1007/978-3-030-85902-2_48

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  • DOI: https://doi.org/10.1007/978-3-030-85902-2_48

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-85901-5

  • Online ISBN: 978-3-030-85902-2

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