Abstract
The rising demand for customization and increasing convergence of the physical and digital worlds have led manufacturing companies to seek solutions to maintain competitiveness in the global business landscape. Distributed manufacturing (DM) enables small volume customized production in geographically dispersed locat and drives the supply chain (SC) to become more agile, flexible, and sustainable. This review paper aims to present future research opportunities and challenges for the facilitation of DM for digital supply chain (DSC) by emerging digital technologies and artificial intelligence (AI). After a review of DM, we identify three distinct types of DM platforms that may facilitate DSC based on transaction mechanisms. These are then explored from a technological perspective, in terms of enabling technologies and data analysis methods that support DM for DSC. We conclude by highlighting the need for empirical studies to investigate the motivations for DM platform adoption and identify a key challenge to their adoption, that is the lack of privacy-preserving AI algorithms in facilitating DM.
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Tang, W., Peng, T., Tang, R., Brintrup, A. (2022). Distributed Manufacturing for Digital Supply Chain: A Brief Review and Future Challenges. In: Kim, D.Y., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Smart Manufacturing and Logistics Systems: Turning Ideas into Action. APMS 2022. IFIP Advances in Information and Communication Technology, vol 664. Springer, Cham. https://doi.org/10.1007/978-3-031-16411-8_51
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DOI: https://doi.org/10.1007/978-3-031-16411-8_51
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