The Impact of Additive Manufacturing on Supply Chain Management from a System Dynamics Model-Scenario: Traditional, Centralized, and Distributed Supply Chain

[EN] In order to describe the impact that the appropriation of additive manufacturing (AM) has on the supply chain (SC), a validated system dynamics model representing vectorially multiple products and multiple demands in different periods was used as a basis to apply to a case study of medical implant manufacturing, configuring three chain scenarios: 1. traditional supply chain with subtractive manufacturing, 2. centralized supply chain with additive manufacturing, and 3. decentralized supply chain with additive manufacturing. It was possible to notice that the production time is longer in additive manufacturing compared to traditional manufacturing and the cycle time and total demand closure were lower in traditional manufacturing. In addition, it was observed that the AM performance is significantly better in conditions of lower demand, which can be attributed to the characteristics of customization and small batches that this type of production approach implies.Nuñez Rodriguez, J.; Andrade Sosa, HH.; Villarreal-Archila, SM.; Ortiz Bas, Á. (2022). The Impact of Additive Manufacturing on Supply Chain Management from a System Dynamics Model-Scenario: Traditional, Centralized, and Distributed Supply Chain. Processes. 10(12):1-38. https://doi.org/10.3390/pr10122489138101

System Dynamics Modeling in Additive Manufacturing Supply Chain Management

A system dynamics model was developed with the primary purpose of visualizing the behavior of a supply chain (SC) when it adopts a disruptive technology such as additive manufacturing (AM). The model proposed a dynamic hypothesis that defines the following issue: what is the impact of the AM characteristics and processes in the SC? The model was represented through a causal diagram in thirteen variables related to the SC, organized in two feedback cycles and a data flow diagram, based mainly on the three-essential links of the SC and the order display traceability: supplier–focal manufacturer–distribution Network. Once proposed, the model was validated through the evaluation of extreme conditions and sensitivity analysis. As a result, the dynamic behavior of the variables that condition the chain management was analyzed, evidencing reduction times in production, especially in products that require greater complexity and detail, as well as reductions in inventories and the amount of raw material due to production and storing practices from AM. This model is the starting point for alternative supply chain scenarios through structural operating policies and operating policies in terms of process management