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EN
Facing severely competitive global markets, managers of the modern transnational corporations must effectively integrate its intra-supply chain system to meet customers’ multiproduct demands with good quality items, minimum operating expenses, and in a timely delivery matter. Inspired by assisting current transnational firms to achieve the mission, this study builds a mathematical model to explore a multiproduct fabrication-shipment problem incorporating an accelerated rate and ensured product quality. A single machine production scheme under a common cycle policy and with random defects, rework, and an accelerated fabrication rate is considered. The speedy rate option is associated with extra setup and linear variable costs, which aims to cut short the common cycle time. Mathematical derivation is employed to find the long-run average system expense. The optimization method is used to jointly derive the decision for common length and delivery frequency per cycle for the problem. Numerical illustration is offered to confirm the applicability of the results and expose the individual/combined influences of diverse crucial system features on the problem, thus facilitate the intra-supply chain’s fabrication-shipment decision making.
EN
To increase their competitive advantage in turbulent marketplaces, contemporary manufacturers must show determination in seeking ways to: fulfill buyer orders with quality merchandise; meet deadlines; handle unexpected production disruptions; and lower the total relevant expense. To tackle the abovementioned challenges, this study explores an economic manufacturing quantity (EMQ) model with machine failure, overtime, and rework/disposal of nonconforming items; the goal is to find the best fabrication uptime that minimizes total relevant expenses. Specifically, we consider a production unit with overtime capacity as an operational feature that is linked to higher unit and setup costs. Further, its EMQ-based process is subject to random nonconforming items and failure rates. Extra screening separates the reworkable nonconforming items from scrap, and the rework is executed at the end of each cycle of regular fabrication. The failures follow a Poisson distribution, and a machine repair task starts as soon as a failure occurs; the fabrication of the lot that was interrupted resumes after the repair has been carried out. A decision model is built to capture the characteristics of the problem. Mathematical and optimization processes help in determining the optimal fabrication uptime. A numerical example not only illustrates the applicability of the research outcomes, but also reveals a diverse set of information about the individual or joint influences of deviations in mean-time-to-failure, overtime factors, and rework/disposal ratios linked to nonconforming rates related to the optimal replenishment uptime, total operating expenses, and various cost contributors; this facilitates better decision making.
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