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Optimal design of additive manufacturing supply chains

J.P. Tavares Vieira Basto, J. Soeiro Ferreira, S. Gomes Soares Alcalá, E. Morosini Frazzon, S. Moniz

3rd European International Conference on Industrial Engineering and Operations Management - EU IEOM 2019, Pilsen (República Checa). 23-26 julio 2019


Resumen:

Additive Manufacturing (AM) is one of the most trending production technologies, with a growing number of companies looking forward to implementing it in their processes. Producing through AM not only means that there are no supplier lead times needed to account for, but also enables production closer to the end customer, reducing then the delivery time. This is especially true for companies with a wide range of low and variable demand products. This paper proposes a mixed integer linear programming (MILP) model for the optimal design of supply chains facing the introduction of AM processes. In the addressed problem, the 3D printers allocation to distribution centers (DC), that will make or customize parts, and the Suppliers-DC-Customers connections for each product need to be defined. The model aims at minimizing the supply chain costs, exploring the trade-offs between safety stock and stockout costs, and between buying and 3D printing a part. The main relevant characteristics of this model are the introduction of stock service levels as decision variables and the use of a linearization of the cumulative distribution function to account for demand uncertainty. A real-world problem from a maintenance provider is solved, showing the applicability of the model. 


Palabras clave: Additive manufacturing; Inventory management; Mixed integer linear programming; Supply chain network design


DOI: DOI icon https://doi.org/10.46254/EU03.20190244

Fecha de publicación: 2019-07-23.



Cita:
J.P. Tavares Vieira Basto, J. Soeiro Ferreira, S. Gomes Soares Alcalá, E. Morosini Frazzon, S. Moniz, Optimal design of additive manufacturing supply chains, 3rd European International Conference on Industrial Engineering and Operations Management - EU IEOM 2019, Pilsen (República Checa). 23-26 julio 2019.

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