Multivariate Statistical process Control Using Wavelet Approach

Document Type : Research Paper

Authors

1 malek ashtar university of technology

2 Industrial Engineering Faculty - Malek-Ashtar University of Technology

10.22070/jqepo.2023.16027.1230

Abstract

This paper attempts to monitor the mean vector of multivariate processes using a wavelet-based model. In the case of monitoring several related technical specifications, wavelet approach is an attractive contribution to analyze the performance of the multivariate process over time statistically. This advanced approach of signal processing enables more effectiveness the process monitoring compared to the traditional methods. The wavelet capability is capable of leading practitioners to a root cause analysis sooner than the traditional schemes when the process shifts to an out-of-control condition. In this paper a new statistic addressed by TMO-WAVE name is proposed to analyze the variation of a multivariate process. The capability of the proposed scheme is compared numerically with different methods in this paper. The numerical comparative reports address the high capability of the proposed wavelet-based method compared to the models of literature in average run length (ARL) term.

Keywords

Journal of Quality Engineering and Production Optimization

Articles in Press, Accepted Manuscript
Available Online from 08 April 2023

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