Operating in today's highly competitive global markets, transnational enterprises always seek to optimize internal vendor-buyer coordinated systems to ensure timeliness and quality deliveries, given the reality of unreliable machines and limited capacity. To facilitate accurate decision making to help organizations gain competitive advantages in such situations, this study explores an intra-supply-chain problem featuring a partial outsourcing batch fabrication plan, random scrap, Poisson-distributed breakdown rate, and multiple shipments of end-product. First, we build a model to characterize the problem clearly. Then, we carry out formulations, analyses, and derivations of the model to attain the problem's cost function. We then use differential calculus and propose a specific algorithm to confirm the convexity of the obtained cost function and derive the optimal runtime. Finally, we offer a numerical illustration to demonstrate the result's applicability for other business circumstances. Additional elements of the problem are then discussed, including the individual and combined influence of variations in scrap, outsourcing, breakdown, and shipping frequency. The features of an optimal operating policy and cost relevant parameters are now revealed to assist management with strategic planning and decision making in real-world intra-supply-chain environments.
This study investigates a multi-item fi nite production rate-(FPR-) based system incorporating a delayed product differentiation policy and common parts' outsourcing strategy. A two-stage fabrication scheme is proposed, wherein, in stage one, all common parts of the end products (assuming they have a known completion rate as compared with the fi nished products) are partially produced in-house and partially supplied by an outside contractor with an extra unit outsourcing; in stage two, all end products are fi nished in sequence, under a rotation fabrication cycle time discipline. An explicit model is developed to clearly represent the proposed problem. Through the optimization technique, the optimal rotation cycle decision is obtained. Thus, diverse characteristics of this particular multi-item, FPR-based system with postponement and outsourcing strategies can now be revealed. As demonstrated by numerical illustrations, these characteristics include the (i) convexity of the system cost function, (ii) impact of common parts' outsourcing strategy on the utilization, (iii) breakup of system cost components, (iv) combined impact of the outsourcing ratio and common parts' completion rate on the system cost function, and (v) effect of the outsourcing ratio on optimal rotation cycle decision. Our decision-support-type system can facilitate production managers in achieving their goals of reducing orders' response times and minimizing the overall system cost.
This study examines the collective impact of postponement, scrap, and subcontracting standard components on the multiproduct replenishing decisions. Rapid response, desirable quality, and various goods guide the client’s demands in today’s competitive market. Therefore, many manufacturing firms search for alternative fabrication and outsourcing strategies during the production planning stage to satisfy the client’s expectations, minimize fabrication-inventory costs, and smoothen machine utilization. To effectively help producers meet today's client's needs and enhance their competitive advantage, we develop a two-stage multiproduct replenishing system incorporating scraps, standard parts subcontracting, commonality, and delayed differentiation. To reduce the production uptime, stage one has a hybrid fabrication process for the common components (i.e., a partial outsourcing strategy), and stage two manufactures the finished multiproduct. In-house fabrication processes in both stages are imperfect; a screening process detects and removes scraps to maintain the finished batch quality. We determine the cost-minimized operating cycle. The findings reveal the collective impact of postponement, scrap, and external suppliers on this multi-product replenishment problem and can be used to facilitate production planning and decision-making.
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