Approximation methods for the analysis of a multicomponent, multiproduct assemble-to-order system

Abstract

In this article, we consider the performance evaluation of a multicomponent, multiproduct assemble-to-order (ATO) system. Each component is managed independently using a base-stock policy at a supply facility with limited production capacity and an infinite buffer. The arrivals of demands follow a multivariate Poisson process and unfilled demands are backlogged. Because exact analysis of the proposed system is not feasible, we propose two approximation methods which provide upper and lower bounds for various performance measures such as fill rate, average waiting time, and average number of backorders of the proposed system. Our computational experiments demonstrate the effectiveness of the two approximation methods under various system settings. In this article, we consider an assemble-to-order (ATO) system in which multiple components are produced to meet demands of multiple products. Each component supply facil- ity has limited production capacity with i.i.d. exponential processing time; its inventory is replenished using a base- stock policy; and the replenishment orders for the component are placed in a queue with an infinite buffer size. The arrivals of demands follow a multivariate Poisson process, in which an arriving order of a certain product will request a num- ber of components with a fixed probability. The demand orders are filled on first-come-first-serve basis and unfilled orders, due to shortage of one or more components, will be backlogged. Throughout this article, we will call the above- described system the infinite buffer ATO system, or IBS in short. We are interested in the analysis of three order-based per- formance measures of the IBS, namely, average waiting time of an order, the average number of backorders, and