Abstract
Previously, it has been held that statistical process control and engineering process control were two distinct domains for process improvement. However, we design four control policies to integrate the two approaches using a proportional-integral-derivative feedback controller and Shewhart or moving centerline exponentially weighted moving average charts. We specifically consider the impact of these policies for a system with response lags modeled by a second-order dynamic process and autocorrelated nonstationary outside disturbances. These policies are implemented using simulation and applied in a case study of a liquid tank system. Our investigation shows this approach is effective with respect to overall system performance, including quality and cost.
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