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EN
It is essential for manufacturers to consider the interrelation among quality, inventory, and maintenance decisions to detect imperfect quality products, keep the production system in good operating condition, and manage quality and inventory costs. Hence, this paper aims to develop an integrated model of inventory planning, quality engineering, and maintenance scheduling in which the expected total cost per time unit is minimised by determining the sample size, sampling interval, control limit coefficient, along with production cycle time. In this regard, an imperfect multi-product manufacturing system is considered, in which the inventory shortage in satisfying the demand for each product type and the idle time during the production cycle are not allowed. It is assumed that the process starts in an in-control condition where most produced units are conforming. However, due to the occurrence of an assignable cause (AC), the process mean moves to an out-of-control condition in which a significant fraction of non-conforming units is produced. The efficiency of the proposed mathematical model is evaluated by a numerical example, and then the sensitivity of the proposed model to important inputs is analysed. Finally, a comparative study based on the Taguchi design approach is given to confirm the capability of the proposed model to achieve remarkable cost savings.
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.
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