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Abstract
Recent technological advances have rendered dynamic process control a viable alternative. A dynamic programming approach is proposed for the modeling and cost minimization of statistical process control activities. The decision parameters of the control chart are allowed to change dynamically as new information about the process becomes available. This general approach has been known as a theoretical possibility for many years, but its practical performance is explicitly investigated in this paper. It is shown with numerical examples that the dynamic programming solution can be much more economical than the conventional static solution with fixed control chart parameters. The substantial potential cost savings and the feasibility of a dynamic control procedure suggest that dynamic process control should replace standard statistical or economic design of control charts as the preferred method in automated production processes.