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Automatic process control (APC) based on design of experiment (DOE) is a cost-efficient approach for variation reduction. The process changes both in mean and variance owing to online parameter adjustment make it hard to apply traditional SPC charts in such DOE-based APC applied process. An adaptive SPC scheme is developed, which can better track the process transitions and achieve the possible SPC run cost reduction when the process is stable. The control law of SPC parameters is designed by fully utilizing the estimation properties of the process model instead of traditionally using the data collected from the production line. An example is provided to illustrate the proposed adaptive SPC design approach.
Automatic process control (APC) based on design of experiment (DOE) is a cost-efficient approach for variation reduction. The process changes both in mean and variance due to online parameter adjustment make it hard to apply traditional SPC charts in such DOE-based APC applied process. An adaptive SPC scheme is developed, which can better track the process transitions and achieve the possible SPC run cost reduction when the process is stable. The control law of SPC parameters is designed by fully utilizing the estimation properties of the process model instead of traditionally using the data collected from the production line. An example is provided to illustrate the proposed adaptive SPC design approach.