Abstract

Additive manufacturing is increasingly being used for satisfying spare parts needs of capital products using a nearby 3D printer. Such a technology allows inventory managers to start manufacturing after the demand realization which eliminates significant portion of spare parts inventory being held due to random nature of component breakdowns. Quality difference between printed and original parts, which is one of the biggest problems of using 3D printers, can be decreased by the use of laser polishing which alleviates surface roughness and increases reliability of parts in exchange of an additional cost term. Using different parameters, reliability of parts can be altered depending on needs of capital products and systems’ status. In this study, the problem where surface roughness and reliability of printed parts are jointly optimized with inventory levels of original spare parts is considered. In the problem setting, a machine part consisting of a constant number of identical products which are subject to random breakdowns over a finite planning horizon is considered. Using mathematical analysis and exhaustive numerical experiments, the relationship between optimum control policy and cost parameters was shown, which might be critical for cost-effective management of the system.

Full Text
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