AbstractThe purpose of this paper is to develop a general model for controlling the percent defective of an ongoing production process. The model is developed in a Bayesian decision theory framework so that, using dynamic programming, optimal (least cost) control decisions can be found. An application of the model to a real world production process is described in detail. The problems of estimating the model parameters are discussed along with some approaches to overcoming the estimation problems. Finally, the optimal control policies for the real world process are presented and are shown to be straightforward and easily implemented.