Little is known about the impact of additive manufacturing in the spare part supply chain. A few studies are available, but they focus on specific parts and their applications only. A general model, which can be adapted to different applications, is nonexistent. This dissertation proposes a decision making framework that enables an interested practitioner/manager to decide whether using additive manufacturing to make spare parts on demand is economical when compared to conventional warehousing strategy. The framework consists of two major components: a general discrete event simulation model and a process of designing a wide range of simulation scenarios. The goal of the dissertation is to help verify existing as well as gain new knowledge about operations of additive manufacturing and the cost implication in the spare parts supply chains. Particularly, the proposed model enables simulation based analysis with various strategies, setups, specific parts, machines and system operating parameters. Furthermore, the process related issues of interest are the influence of building speed, building space volume, material price, machine purchase price and cool down time. Strategy related issues are multi-machine and multi-material production strategies in several setups. Also simulation investigation of different spare part stock properties are executed and analyzed by using different part size distributions. This dissertation establishes fundamental understanding of the characteristics of the additive manufacturing system for spare part supply strategies. This model could directly help the decision-making processes in whether to adopt additive manufacturing technology, and also helps the evaluation of different additive manufacturing strategies when the technology is adopted. Both decisions (adoption and strategies) are made based on cost analysis for spare parts in a broader supply chain.
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Spare parts on demand using additive manufacturing : a simulation model for cost evaluation.