Multivariate process capability using principal component analysis

Ramkrishna Lahu Shinde · Kailas Govinda Khadse

57 citations0/0 files storedQuality and Reliability Engineering International

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Advanced Statistical Process Monitoring Statistical Methods and Applications Fault Detection and Control Systems

Abstract

Abstract Wang and Chen (Qual. Eng. 1998; 11:21–27) have defined process capability indices (PCIs) for multivariate normal processes data using principal component analysis (PCA). Veevers (Statistical Process Monitoring and Optimization. Marcel Dekker: New York, NY, 1999; 241–256) has suggested a multivariate capability index based on the first principal component (PC). In this paper we demonstrate the problem in the definition of PCIs given by Wang and Chen (Qual. Eng. 1998; 11:21–27) and the non‐suitability of PCI given by Veevers (Statistical Process Monitoring and Optimization. Marcel Dekker: New York, NY, 1999; 241–256) through some examples. We also suggest an alternative method for assessing multivariate process capability based on the empirical probability distribution of PCs. This method has been performed on industrial and simulated data. Copyright © 2008 John Wiley & Sons, Ltd.

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References

1993A note on multivariate capability indices 2000Using principal component analysis in process performance for multivariate data 2000Comparison of Three Multivariate Process Capability Indices 2009A New Multivariate Process Capability Vector 1998CAPABILITY INDEX USING PRINCIPAL COMPONENTS ANALYSIS

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