Title: Multivariate statistical methods and Six-Sigma

Authors: Kai Yang

Addresses: Department of Industrial and Manufacturing Engineering, Wayne State University, Detroit, MI 48201, USA

Abstract: Multivariate statistical methods are very powerful methods that are playing important roles in many fields. Data mining and chemimetrics are among the successful applications of multivariate statistical methods in business and industry. However, multivariate statistical methods are seldom applied in Six-Sigma practice as well as quality assurance practice in general. With the advancement of information and computer technology, the barriers in applying multivariate statistical methods are disappearing. In this paper, we will show that multivariate statistical methods can play important roles in Six-Sigma (DMAIC) practice.

Keywords: multivariate statistical methods; multivariate analysis; data mining; six sigma; DMAIC; quality improvement; quality assurance.

DOI: 10.1504/IJSSCA.2004.005279

International Journal of Six Sigma and Competitive Advantage, 2004 Vol.1 No.1, pp.76 - 96

Published online: 19 Sep 2004 *

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