THE INFLUENCE OF EXPEDITED FABRICATION RATE, UNRELIABLE MACHINES, SCRAP, AND REWORK ON THE PRODUCTION RUNTIME DECISION IN A VENDOR-BUYER COORDINATED ENVIRONMENT

Transnational manufacturing firms operate in highly competitive marketplaces. This means that they are continuously seeking ways to reduce order response and fabrication cycle times, maintain the desired product quality, manage unanticipated machine failures, and provide timely delivery to effectively minimize overall operating cost and maintain a competitive advantage over their intra-supply chains. To assist firms in achieving these operational goals, we examine a buyer-vendor coordinated system with an expedited fabrication rate, unreliable machines, scrap, and rework, with the objective of minimizing the overall operating costs. An imperfect manufacturing process is assumed, which arbitrarily produces repairable and scrap items, with the latter being reworked in each fabrication cycle. Additionally, the process is subject to a Poisson-distributed machine breakdown. The corrective action is undertaken immediately when the machine fails, and the production of unfinished/interrupted lot resumes when the process is restored. The expedited fabrication rate option is used at an extra cost to reduce the cycle length. We built a fabrication-shipment model to characterize the problem’s features explicitly. Mathematical and optimization approaches assist us in determining the optimal fabrication runtime policy. A numerical example illustrates the capability/applicability of our outcomes. Furthermore, it exposes a diverse set of information relating to the collective/individual effect of differences in the expedited rates, mean-time-to-breakdown, frequency of shipment, and rework/disposal rates of defective items on the optimal policy, utilization, total operating cost, and various cost contributors. This information can contribute to facilitating better decision-making.

Quality Analysis in Acyclic Production Networks

The production network under examination consists of a number of workstations. Each workstation is a parallel configuration of machines performing the same kind of tasks on a given part. Parts move from one workstation to another and at each workstation a part is assigned randomly to a machine. We assume that the production network is acyclic, that is, a part does not return to a workstation where it previously received service. Furthermore, we assume that the quality of the end product is additive, that is, the sum of the quality contributions of the machines along the production path. The contribution of each machine is modeled by a separate random variable. Our main result is the construction of estimators that allow pairwise and multiple comparison of the means and variances of machines in the same workstation. These comparisons then may lead to the identification of unreliable machines. We also discuss the asymptotic distributions of the estimators that allow the use of standard statistical tests and decision making.