Multivariate process capability analysis based on the principal component analysis method

作者：Zhao Kai^*; He Zhen; Zhang Min

来源：Journal of Northwestern Polytechnical University, 2011, 29(5): 745-750.

• Dimension reduction
• Independent iomponent analysis
• Multivariate process
• Nonconforming proportion
• Principal component analysis method

Multivariate process capability analysis is needed to study the variation in manufacturing process relative to the designed tolerances when multiple quality characteristics are monitored simultaneously in practice. Due to the complicated joint probability density function between multiple quality characteristics, the dimensions reduction is used to solve the problems, such as strong correlation. In this paper principal component analysis method is used to reduce the dimensions of multiple quality characteristics at first. Based on the specification region, the specification center vector and target vector of principal components (PCs), three kinds of nonconforming proportion of multivariate process are proposed and defined, which are latent non-conforming, performance non-conforming and Taguchi non-conforming, respectively. Compared with the allowed process non-conforming by customers, these non-conforming calculations can be used to be the guideline on how to improve the manufacturing process for the engineers and operators. At last, a case study of a spindle motor process is presented.

• 出版日期2011
• 单位天津大学