A Key Variable Detection Algorithm in Multivariate Manufacturing Process

doi:10.13190/j.jbupt.2019-172

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2019, Vol. 42 ›› Issue (6): 98-104.doi: 10.13190/j.jbupt.2019-172

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A Key Variable Detection Algorithm in Multivariate Manufacturing Process

YU Kai-xiang¹, CHEN Zhen-hao², ZHANG Si-hai¹

1. School of Information, University of Science and Technology of China, Hefei 230022, China;
2. Chang Xin Memory Technologies, Inc., Hefei 230000, China

Received:2019-08-21 Online:2019-12-28 Published:2019-11-15

Abstract

Abstract: 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.

Key words: multivariate manufacturing process, machine learning, key variable detection

CLC Number:

TN929.53

YU Kai-xiang, CHEN Zhen-hao, ZHANG Si-hai. A Key Variable Detection Algorithm in Multivariate Manufacturing Process[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2019, 42(6): 98-104.

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A Key Variable Detection Algorithm in Multivariate Manufacturing Process

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