%0 Journal Article
%A CHEN Zhen-hao
%A YU Kai-xiang
%A ZHANG Si-hai
%T A Key Variable Detection Algorithm in Multivariate Manufacturing Process
%D 2019
%R 10.13190/j.jbupt.2019-172
%J Journal of Beijing University of Posts and Telecommunications
%P 98-104
%V 42
%N 6
%X A key variable detection algorithm based on machine learning in multivariate manufacturing process was proposed. It uses the machine learning classifier to mathematically model the multivariate manufacturing process. And the performance change of the classifier after the process variable shuffled randomly is used as an evaluation index to detect the key variables that lead to relatively abnormal product quality. Simulation data of the multivariate manufacturing process is designed and generated. The performance of the algorithm was verified by simulation data set and two actual production case data sets based on a factory in China. Both verifications show that the algorithm has good detection performance.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2019-172