Managers of today’s transnational firms, facing competitive global business environments, always intend to optimize their intra-supply chain systems to meet customers’ multiproduct demands with perfect quality goods, timely delivery, and minimum fabrication-shipping expenses. In the production units of intra-supply chain systems, random scraps are inevitable due to various unforeseen factors. Also, since the in-house capacity is limited, implementing a partial outsourcing plan can help release machine workloads, smooth production schedule, and reduce fabrication uptime. Inspired by these facts, this study explores an intra-supply chain system with random scraps and an external source. We build a mathematical model to portray the characteristics of the studied problem. Model analyses and the renewal reward theorem help us to obtain the expected system cost function. Optimization techniques and Hessian matrix equations are used to jointly decide the optimal cycle time and shipment policy that minimize the expected system cost. Through numerical illustration, we expose the individual and joint impact of diverse system features on the optimal operating policies and other crucial parameters of the studied problem, thus, facilitate managerial decision makings.

No abstract

This study examines a multi-item manufacturing problem with a single machine, an outsourcer, and random defective items. To cope with the increasing multi-product demands from global markets, modern manufacturing firms must make an efficient production plan to satisfy customer’s needs with quality goods and smooth the in-house fabrication schedule and utilization. Outsourcing is an effective option to avoid machine overloads and smooth fabrication schedules. Further, the fabrication of random defective products is inevitable because of unanticipated factors in real manufacturing environments. These products must be identified, separated and discarded to retain the desired quality of the finished lot. To address the above-mentioned concerns, this study develops a mathematical model to represent a hybrid stock refilling system, employs mathematical derivations to find long-run average system expenses, and uses an optimization technique to derive a closed-form common rotation time for this hybrid system. The results of this study show the individual and combined impacts of variations in outsourcing percentages and scrap rates on optimal rotation time and diverse core system parameters (such as machine utilization, specific cost component, etc.) to facilitate planning, controlling, and decision making in such a particular hybrid fabrication system.