Mechanical Engineering Science

Computing Method of Multivariate Process Capability Index Based on Normalized Pretreatment

YingGuangqi, RanYan, ZhangGenbao, LiuYuxin, ZhangShengyong

Abstract


For the traditional multi-process capability construction method based on principal component analysis, the process variables are mainly considered, but not the process capability, which leads to the deviation of the contribution rate of principal component. In response to the question, this paper first clarifies the problem from two aspects: theoretical analysis and example proof. Secondly, aiming at the rationality of principal components degree, an evaluation method for pre-processing data before constructing MPCI using PCA is proposed. The pre-processing of data is mainly to standardize the specification interval of quality characteristics making the principal components degree more reasonable and optimizes the process capability evaluation method. Finally, the effectiveness and feasibility of the method are proved by an application example.

Keywords


Multivariate process capability index; The standard range; Contribution degree; Specification intervals

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References


Juran J M, Gryna F M and Bingham R S. Quality Control Handbook. McGraw-Hill Higher Education 1974.

Chan L K, Cheng SW and Spiring FA. A new measure of process capability: Cpm. Journal of Quality Technology 1988; 20(3): 162-175. https://doi.org/10.1080/00224065.1988.11979102

Shahriari H, Hubele N and Lawrence F P. A multivariate process capability vector. Proceedings of the 4th industrial engineering research conference, Institute of Industrial Engineers 1995; 304-309.

Wang S. X, Yeh. A. B. A spatial multivariate process capability index. IEEE International Conference on industrial Engineering &. En-gineering Management 2010; 1443-1445. https://doi.org/10.1109/IEEM.2010.5674321

Wierda SJ. Multivariate quality control-estimation of the percentage of good products. The Netherlans: Dept. of Econometrics, University of Groningen 1992.

Bothe D R. Composite capability index for multiple product characteristics. Quality Engineering 2000; 12(2): 253-258. https://doi.org/10.1080/08982119908962582

Chen K S, Pearn W L and Lin P C. Capability measures for processes with multiple characteristics. Quality and Reliability Engineering lnternational 2003; 19(2): 101-110. https://doi.org/10.1002/qre.513

Wang K F and Chen J C. Capability index using principal component analysis. Quality Engineering 1998; 11(1): 21-27. https://doi.org/10.1080/08982119808919208

Wang F K and Du T C. Using principal component analysis in process performance for multivariate data. Omega International Journal of Management Science 2000; 28(2): 185-194. https://doi.org/10.1016/S0305-0483(99)00036-5

MA Yizhong. Multivariate Quality Process Capability Index.Industrial Engineering 2001; 4(4))22-24.

Wang Rang C H. Constructing multivariate process capability indices for short-run production. lnternational Journal of Advanced Man-ufacturing Technology 2005; 26 (11-12): 1306-1311. https://doi.org/10.1007/s00170-004-2397-8

Shinde, R. L. and K. G. Khadse. Multivariate Process Capability Using Principal Component Analysis. Quality And Reliability Engi-neering International 2009; 25(1) : 69-77. https://doi.org/10.1002/qre.954

Zhang, M., et al. Modified Multivariate Process Capability Index Using Principal Component Analysis. Chinese Journal of Mechanical Engineering 2014; 27(2): 249-259. https://doi.org/10.3901/CJME.2014.02.249

Shahriari H, Abdollahzadeh M. A new multivariate process capability vector. Quality Engineering 2009; 21(3): 290-299. https://doi.org/10.1080/08982110902873605

Jeh-Nan Pan and Chun-Yi Lee. New capability indices for evaluating the performance of multivariate manufacturing processes. Quality and Reliability Engineering International, 2010; 26(1): 3-15. https://doi.org/10.1002/qre.1024




DOI: https://doi.org/10.33142/me.v1i1.654

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Copyright (c) 2019 Guangqi Ying, Yan Ran, Genbao Zhang, Yuxin Liu, Shengyong Zhang

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