Determining method for controlling parameters interval of process stability based on multivariable controlling-detecting linear model

Through establishing a multi-variable relationship between process controlling parameters and detecting parameters, a process stability control model was proposed. Based on process physical laws or process statistical data, a multi-variable linear model between process controlling parameters and detecting parameters was established. Through parameter estimation, the prediction ellipsoid and joint confidence intervals of detecting parameters, as well as the expected value of multi-variable controlling parameters which met the detecting parameters stability requirements were acquired. In view of three commonly used objective functions in actual process, by considering model error and parameter fluctuations, the genetic algorithm was adopted to solve the fluctuation range of controlling parameters that meet the detecting parameters' stability requirements at a given confidence. The feasibility of the proposed method was illustrated by a typical manufacturing process of a product.