THROUGHPUT ANALYSIS IN MANUFACTURING NETWORKS

The throughput of a plant is a measure of major importance when assess ing its ability to compete successfully in the market place. Managers often rely on changes in capacity (production rate) and process improv ements as two major factors that impact throughput. The optimal alloca tion of resources to these two factors is difficult to determine witho ut the support of appropriate mathematical models. In this paper we at tempt to quantify the tradeoffs between capacity and process improveme nts, through variance reductions, and throughput. We consider multipro duct manufacturing systems modeled by open networks of queues and form ulate the throughput characterization (TC) and variability reduction ( VR) problems as nonlinear programs. These formulations are based on th e decomposition approach for estimating the work-in-progress in open q ueueing networks. We show, by demonstrating the applicability of greed y-type heuristics for the TC and VR problems, that the overall impact of a wide variety of process improvement practices on WIP and throughp ut can be evaluated very efficiently.