期刊
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
卷 17, 期 2, 页码 757-765出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2020.3029541
关键词
Additive manufacturing (AM) supply chain; location-allocation; make-to-order (MTO); mixed-integer linear programming (MILP); p-median; supply chain design
类别
资金
- European Unions Horizon 2020 research and innovation programme
- Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa [777096]
This article introduces a new method for designing additive manufacturing supply chains using optimization methods to address the challenges brought by new technologies. The approach, which includes p-median and mixed-integer linear programming models, is suitable for making decisions on deploying productive resources in specific locations.
In the current industrial revolution, additive manufacturing (AM) embodies a promising technology that can enhance the effectiveness, adaptability, and competitiveness of supply chains (SCs). Moreover, it facilitates the development of distributed SCs, thereby enhancing product availability, inventory levels, and lead time. However, the wide adoption of AM in industrial SCs creates various challenges, leading to new difficulties for SC design. In this context, this article proposes a new design approach to AM SCs using optimization methods. More specifically, the proposed approach, comprising the p-median and mixed-integer linear programming models, considers the decision of deploying productive resources (3-D printers) in specific locations of generic spare part SCs. The approach was evaluated in a real-world use case of an elevator maintenance service provider. The obtained results demonstrated the promising capabilities of the proposed design approach in managing the challenges arising from the forthcoming widespread use of 3-D printers in manufacturing SCs.
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