Stock or Print? Impact of 3D Printing on Spare Parts Logistics



We present a general framework to study the design of spare parts logistics in the presence of 3D printing technology. We consider multiple parts facing stochastic demands. To minimize long-run average system cost, our model determines which parts to stock and which part to print. We derive various structural properties of the problem to gain insights. In some cases, we obtain closed-form optimal solutions; in other cases, we devise efficient algorithms to obtain near optimal solutions. We demonstrate that the optimal printer utilization is generally low, suggesting complementarity between stock and print in cost minimization. (Joint work with Yue Zhang)