Title: Grey relation pattern recogniser for X-bar control charts

Authors: Hsi-Mei Hsu, Yan-Kwang Chen

Addresses: Institute of Industrial Engineering, National Chiao Tung University, 1001, Ta Hsueh Road, Hsinchu, Taiwan 30050, Republic of China. Institute of Industrial Engineering, National Chiao Tung University, 1001, Ta Hsueh Road, Hsinchu, Taiwan 30050, Republic of China

Abstract: This paper has developed an on-line pattern recogniser to detect unnatural patterns on control charts. The recogniser can assist in the correction of assignable causes. The recogniser presented here is based on the grey relation model which is used to calculate the degree of relative similarity between observations routinely collected from X-bar charts and each unnatural pattern, such as a trend or cycle. According to the degree of relative similarity, the recogniser will identify whether an unnatural pattern exists in the data. To explain the design process and the evaluation of the performance of the recogniser, a set of commonly encountered unnatural patterns, such as trends, cycles, systematic, stratification, mixtures and sudden-shifts, was applied in this paper. The performance of the recogniser was evaluated by simulation. The results showed that the recogniser has effectiveness in detecting the following patterns trend, cycle, sudden-shift, systematic, and stratification.

Keywords: grey relation model; pattern recogniser; control charts.

DOI: 10.1504/IJMTM.2000.001341

International Journal of Manufacturing Technology and Management, 2000 Vol.1 No.2/3, pp.271-287

Published online: 02 Jul 2003 *

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