Abstract

We develop simple models for understanding how the dynamics of quality may affect customer satisfaction and profitability in make-to-stock manufacturing systems. We study a Markovian, single stage system facing random demand. Any demand not satisfied immediately from stock is lost to competitors. The market is assumed to be finite and comprises both regular and occasional customers. Regular customers have higher mean demand rates than occasional customers. Each outgoing product is inspected and classified as high quality, medium quality, or nonconforming. The customer who purchases an item joins the regular or the occasional class, with corresponding probabilities which depend on the quality level and on past customer state. The higher the quality level, the higher the probability for a customer to remain or become a regular customer. Our goal is to investigate the structure of the optimal production, order satisfaction and quality control policy in order to maximize the average profit rate of the system. We investigate numerically the structure of the optimal policy using stochastic dynamic programming.

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