This study examines the joint impact of outsourcing, overtime, multi-delivery, rework, and postponement on a multiproduct fabrication problem. A growing/clear trend in today’s customer requirements turned into rapid response and desired quality of multi-merchandises and multiple fixed-amount deliveries in equal-interval time. To satisfy customers’ expectations, current manufacturing firms must effectively design/plan their multiproduct production scheme with minimum fabrication-inventory-shipping expenses and under confined capacity. Motivated by assisting manufacturing firms in making the right production decision, this study develops a decision-support delayed-differentiation model considering multi-shipment, rework, and dual uptime-reducing strategies (namely, overtime and outsourcing). Our delayed-differentiation model comprises stage one, which makes all common/standard parts of multi-end-merchandises, and stage two, which produces multiple end merchandise. For cutting making times, the study proposes subcontracting a portion of the common/standard part’s lot size and adopting overtime-making end merchandise in stage two. The screening and reworking tasks identify and repair faulty items to ensure customers’ desired quality. The finished lots of end merchandise are divided into a few equal-amount shipments and distributed to customers in equal-interval time. We employ mathematical derivation and optimization methodology to derive the annual expected fabrication- inventory-shipping expense and the cost-minimized production-shipping policy. A numerical demonstration is presented to exhibit our research scheme’s applicability and exposes the studied problem’s critical managerial insights, which help the management make beneficial decisions.

Internal supply chains exist in many global enterprises, where manufacturing tasks and sales jobs operate separately, but the management needs to integrate their financial performance reports. In addition, the fabrication planning must meet specific operational goals, such as meeting external clients’ requirements on quality and short order due dates, avoiding internal fabricating interruptions due to inevitable equipment breakdowns, and minimizing overall manufacturing and stock holding costs. Motivated by helping multinational corporations deal with the issues mentioned earlier, this study aims to optimize a finite production rate (FPR)-based supplier-retailer cooperative problem with multi-shipment, rework, subcontracting, probabilistic failure, and expedited rate. Wherein using an outsourcer and expedited-rate help shorten the needed batch producing time significantly; the rework of defects and corrective action on unanticipated breakdown assist in up-keeping the quality and avoiding fabricating delay. We develop an FPR-based model to cautiously represent the considered manufacturing features and activities involved in transporting end products and retailers’ stock holding. Model’s formulating and investigating assists us in gaining the function of operating costs. In addition, optimization procedures with a proposed algorithm help us verify its convexity and decide the model’s best fabricating runtime solution. Finally, we validate how this study works and what important information our model can disclose using a numerical example to facilitate management’s decision-making to end our work.

Transnational producers facing the present-day competitive global supply-chain environments need to pursue the most appropriate manufacturing scheme, quality screening task, and stock shipping plan to satisfy customer’s timely multi-item requirements under minimum overall product fabrication-delivery expenses. This study develops a producer-retailer incorporated multi-item two-stage economic production quantity- (EPQ-) based system with delayed differentiation, expedited-rate for common parts, multiple deliveries plan, and random scrap. It aims to assist current manufacturing firms in achieving the aforementioned operating goals. Mathematical methods help us build an analytical model to explicitly portray the studied problem’s features and derive its overall system expenses. Hessian matrix equations and optimization approaches help us prove convexity and derive the cost-minimized fabrication- delivery decision. This study gives a simulated example to illustrate the research outcome’s applicability and the proposed model’s capabilities numerically. Consequently, diverse crucial information becomes obtainable to the manufacturers to facilitate various operating decision makings as follows: (i) the cost-minimized fabrication-delivery policy; (ii) the behavior of system’s overall expenses and operating policy regarding mean scrap rate, and different relationships between common part’s values and completion-rate; (iii) the system’s detailed cost components; (iv) the system’s overall expenses, utilization, and common part’s uptime concerning different common part’s expedited rates; and (v) the collective effects of critical system features on the overall expenses, uptime, and optimal cycle length, etc.

The study applies a postponement strategy to a multi-item fabrication-shipment decision making in a vendor-buyer coordinated environment with multi-delivery, quality reassurance, and overtime. To cope with the recent client demand trend asking for rapid response, quality, and diversified goods, today’s manufacturers require a multi-item production-shipping scheme to satisfy customers’ needs in cost-saving, quality, and timely matter. In our model, we first produce all needed mutual components and postpone manufacturing of finished goods in the second phase. To expedite mutual parts’ fabrication time, overtime is used. Product quality is reassured through screening the defeats and reworking repairable defectives in both fabrication phases. To decide the optimal fabrication-shipment policy, we build a math model and apply the cost minimization technique to the problem. Upon deriving the optimal policy, we utilize an example to demonstrate how our model works and its capability in exposing various previously inaccessible information to the problem. These detailed results can facilitate managerial decision-making and boost the performance of such a specific multi-item postponement fabrication-shipment system in cost-saving, product quality, and timely response.