Abstract
Increasing business competitiveness forced companies to improve their business. Therefore, industry managers have found that it is necessary to focus on the supply of products in according to the wishes of the customer the quality and the cost of their intended use. We consider a three-stage supply chain involving multiple suppliers, manufacturer producing multiple type of product and a final customer. At each order, the manufacturer receives the raw material from a supplier based on optimal policy in a lot of size Q. The production process could produce additional nonconforming products, the manufacturer could be unavailable due to failures (following a general time-to failure distribution), and repair operations (following a general time-to-repair distribution) propose a control policy, which coordinates supplier selection, replenishment, production and quality inspection decisions. Upon reception, the manufacturer applies a simple lot-by-lot acceptance-sampling plan with attributes. This plan is characterized by a random sample of size n and an acceptance criterion c. Based on this inspection plan if the number of non-conforming items d found in this sample is equal to or less than c the lot will be accepted. Otherwise, the lot will be refused and returned to its original supplier and then a new order is placed. At this instant the manufacturer is not obliged to keep the same supplier. He can choose any one that offers better replenishment conditions. In this work. we aim to determine the optimal control policy for supplier selection replenishment and optimal quality control decisions that minimizes the total cost which includes inventory, backlog, inspection, replenishment and production costs. Coordinating decisions along the entire chain is critical since it requires determining carefully what to manufacture as well as what when and from whom to order. So simulation-based optimization is one of the methods for solving this problem. Numerical examples show the efficiency of the proposed method.
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