Method of Identifying Key Quality Characteristics in Multistage Manufacturing Process Based on PLSR

Abstract

To improve the existing methods of identifying the key quality characteristics in multistage manufacturing process, the partial least squares regression (PLSR) method is combined with the state space model that a new method of identifying the key quality characteristics in multistage manufacturing process based on PLSR is proposed. According to the feature of multistage manufacturing process, the state space model is introduced to build the key quality characteristics identifying model for multistage manufacturing process, using the PLSR method to solve the problem of the quality characteristics such as multicollinearity, do model analyzing and identify the key quality characteristics. At last, the cigarette production process is presented as an example to introduce the application of this method. The result shows that this method can not only identify the key quality characteristics in multistage manufacturing process, but also establish the model of output quality effecting of all levels on the final product quality and its quality characteristics relationship, which reflect the structure of the multistage manufacturing process and causal relationship between quality characteristics at all process levels, provide the basis for quality analysis and control in multistage manufacturing process.