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Measuring the Complexity of Additive Manufacturing Supply Chains

[+] Author Affiliations
Ardeshir Raihanian Mashhadi, Sara Behdad

University at Buffalo, Buffalo, NY

Paper No. MSEC2017-2871, pp. V002T01A037; 10 pages
doi:10.1115/MSEC2017-2871
From:
  • ASME 2017 12th International Manufacturing Science and Engineering Conference collocated with the JSME/ASME 2017 6th International Conference on Materials and Processing
  • Volume 2: Additive Manufacturing; Materials
  • Los Angeles, California, USA, June 4–8, 2017
  • Conference Sponsors: Manufacturing Engineering Division
  • ISBN: 978-0-7918-5073-2
  • Copyright © 2017 by ASME

abstract

Complexity has been one of the focal points of attention in the supply chain management domain, as it deteriorates the performance of the supply chain and makes controlling it problematic. The complexity of supply chains has been significantly increased over the past couple of decades. Meanwhile, Additive Manufacturing (AM) not only revolutionizes the way that the products are made, but also brings a paradigm shift to the whole production system. The influence of AM extends to product design and supply chain as well. The unique capabilities of AM suggest that this manufacturing method can significantly affect the supply chain complexity. More product complexity and demand heterogeneity, faster production cycles, higher levels of automation and shorter supply paths are among the features of additive manufacturing that can directly influence the supply chain complexity. Comparison of additive manufacturing supply chain complexity to its traditional counterpart requires a profound comprehension of the transformative effects of AM on the supply chain. This paper first extracts the possible effects of AM on the supply chain and then tries to connect these effects to the drivers of complexity under three main categories of 1) market, 2) manufacturing technology, and 3) supply, planning and infrastructure. Possible impacts of additive manufacturing adoption on the supply chain complexity have been studied using information theoretic measures. An Agent-based Simulation (ABS) model has been developed to study and compare two different supply chain configurations. The findings of this study suggest that the adoption of AM can decrease the supply chain complexity, particularly when product customization is considered.

Copyright © 2017 by ASME

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