Manufacturing firms operating in today’s competitive global markets must continuously find the appropriate manufacturing scheme and strategies to effectively meet customer needs for various types of quality of merchandise under the constraints of short order lead-time and limited in-house capacity. Inspired by the offering of a decision-making model to aid smooth manufacturers’ operations, this study builds an analytical model to expose the influence of the outsourcing of common parts, postponement policies, overtime options, and random scrapped items on the optimal replenishment decision and various crucial system performance indices of the multiproduct problem. A two-stage fabrication scheme is presented to handle the products’ commonality and the uptime-reduced strategies to satisfy the short amount of time before the due dates of customers’ orders. A screening process helps identify and remove faulty items to ensure the finished lot’s anticipated quality. Mathematical derivation assists us in finding the manufacturing relevant total cost function. The differential calculus helps optimize the cost function and determine the optimal stock-replenishing rotation cycle policy. Lastly, a simulated numerical illustration helps validate our research result’s applicability and demonstrate the model’s capability to disclose the crucial managerial insights and facilitate manufacturing-relevant decision making.

This study presents a multiproduct fabrication cost-minimization model featuring external providers, commonality, rework, and postponement in the supply chain environment. Customers’ requirements simultaneously emphasize quality, variety, and fast response time in current markets. To satisfy customer needs, most manufacturers in various industries (e.g., clothing, household goods, automotive, etc.) plan their multiproduct fabrication by incorporating a postponement strategy, rework process, and an outsourcing option. Motivated by the viewpoints above, this study offers a decision support system to address customers’ external expectations while optimizing internal operating expenses and machine utilization. We propose a single-machine, two-stage delayed differentiation system under a rotation cycle policy. All needed common parts are made in stage one, and stage two fabricates different end products. An external provider is hired to supply partially needed common parts to shorten uptime. The defective items are inevitably produced in both stages. They are categorized and reworked to maintain the desired product quality. Finally, we derive an optimal cost-minimization rotation cycle for our model and use a numerical example to investigate the collective and individual influences of reworking, postponement, and outsourcing to external providers on the multiproduct fabrication problem. In summary, this study can offer an optimization solution for production planning in various modern industries.