A new process capability index for multiple quality characteristics based on principal components

作者：Dharmasena L S; Zeephongsekul P^*

来源：International Journal of Production Research, 2016, 54(15): 4617-4633.

DOI：10.1080/00207543.2015.1091520

• multivariate process capability index
• manufacturing
• process yield
• hypothesis tests
• confidence intervals

This paper presents a new multivariate process capability index (MPCI) which is based on the principal component analysis (PCA) and is dependent on a parameter beta which can take on any real number. This MPCI generalises some existing multivariate indices based on PCA proposed by several authors when beta = 0 or 1. One of the key contributions of this paper is to show that there is a direct correspondence between this MPCI and process yield for a unique value of beta. This result is used to establish a relationship between the capability status of the process and to show that under some mild conditions, the estimators of this MPCI is consistent and converge to a normal distribution. This is then applied to perform tests of statistical hypotheses and in determining sample sizes. Several numerical examples are presented with the objective of illustrating the procedures and demonstrating how they can be applied to determine the viability and capacity of different manufacturing processes.

• 出版日期2016
• 单位迪肯大学