Quality Control via Model-Free Optimization for a Type of Batch Process with a Short Cycle Time and Low Operational Cost

Abstract

Proper settings of key process variables are critical to the product quality control of mass-producing batch processes. The most widely used method in searching for the optimal process condition is the model-based optimization method (MBO). However, model development could be a challenging task in many cases. The accuracy of the model may deteriorate when the process conditions are changed. A systematic, model-free optimization method (MFO) for a type of batch process with a short cycle time and low operational cost is proposed to improve the efficiency of quality control. Instead of building a quality model, a direct search for the optimum process condition using experimental measurements is applied. Optimization algorithm is implemented as well to improve the search efficiency; both the gradient-based and the gradient-free optimization methods are discussed. The simultaneous perturbation stochastic approximation (SPSA) and the simplex search algorithm are incorporated in the MFO. The MFO method was appl...