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• W4387232912 abstract "The implementation of Industry 4.0 enabling technologies to optimize supply chain processes has become an essential aspect of modern manufacturing. Supply chain optimization (SCO) through additive manufacturing technology (AMT) is one area where Industry 4.0 is having a considerable impact. This study, therefore, explores the aspects of Industry 4.0 enabled by the incorporation of AMT into the production system that contribute to supply chain optimization. Ten such features have been identified and analyzed in this study using the novel Grey Influence analysis (GINA) technique. GINA methodology in this research helps to circumvent the restrictions of contemporary causal modeling methods such as the Decision-making trial and evaluation laboratory (DEMATEL) and Interpretative structural modeling (ISM) with the cumulative integration of responses, thus mitigating data loss. The results of the investigation demonstrate that cloud manufacturing, sustainable manufacturing, on-demand manufacturing, and distributed manufacturing are the predominant features of Industry 4.0 enabled by AMT. The findings of this study can be utilized by businesses to take informed decisions concerning incorporation, investment, and optimal application of AMT as well as to determine the significance of AMT to optimize their supply chains." @default.
• W4387232912 created "2023-10-02" @default.
• W4387232912 creator A5027863322 @default.
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• W4387232912 date "2023-10-02" @default.
• W4387232912 modified "2023-10-16" @default.
• W4387232912 title "Examining the Role of Industry 4.0 in Supply Chain Optimization Through Additive Manufacturing" @default.
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• W4387232912 doi "https://doi.org/10.1007/978-981-99-6062-0_62" @default.
• W4387232912 hasPublicationYear "2023" @default.
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