Monitoring location and scale of multivariate processes subject to a multiplicity of assignable causes. Issue 5 (2nd September 2020)

• Record Type: Journal Article
• Authors: Tasias, Konstantinos A.; Nenes, George
• Is Part Of: Quality technology & quantitative management. Volume 17:Issue 5(2020)
• Page Start: 592
• Page End: 608
• Publication Date: 2020-09-02
• Subjects: Quality control -- Statistical Process Control (SPC) -- correlation -- multiple assignable causes -- multivariate analysis; Quality control -- Periodicals; Quality control -- Statistical methods -- Periodicals; Industrial management -- Periodicals; Industrial management; Management -- Research -- Methodology -- Periodicals; Qualitative research -- Periodicals; Management; Quality control; Quality control -- Statistical methods; Periodicals; 658.00721
• DOI: 10.1080/16843703.2019.1702753
• Languages: English
• ISSNs: 1684-3703

Abstract

ABSTRACT: This paper presents a fully adaptive multivariate statistical process control scheme for processes where multiple assignable causes may occur. The assignable causes affect both the mean vector and the covariance matrix, monitored by a T 2 chart and a control chart based on entropy, respectively. Markov chain theory is employed to model the stochastic operation of the proposed scheme and optimize its economic-statistical operation. A numerical investigation and a sensitivity analysis are conducted in order to evaluate the performance and investigate the robustness of the model. A real example is employed to illustrate the operation of the scheme.