Title: Non-parametric change-point approach for monitoring shifts in process location and variability

Authors: Rotimi Felix Afolabi; Peter A. Osanaiye; Onoja Matthew Akpa

Addresses: Department of Epidemiology and Medical Statistics, College of Medicine, University of Ibadan, Nigeria; Department of Statistics, University of Ilorin, Nigeria ' Department of Statistics, University of Ilorin, Nigeria ' Department of Epidemiology and Medical Statistics, College of Medicine, University of Ibadan, Nigeria

Abstract: In statistical process control, detecting if the process is in control and the position of shift in an out-of-control process are critical research problems. If the normality assumption is satisfied, work has advanced in detecting shifts in mean and/or variance. However, the normality assumption is often not satisfied in many real life situations. We suggest a non-parametric Lepage-type change-point (LCP) control chart for jointly detecting process shifts in mean and variance, under non-normality. A comparison between our proposed method and a generalised likelihood ratio (GLR)-based method was made. Process data were simulated following normal and Laplace distributions. The performances of LCP and GLR were assessed and presented, using evaluated average run lengths, under the distributions considered. The LCP competed favourably with the GLR in a normal distribution. However, LCP outperformed GLR under the heavy-tailed distribution considered. We recommend the new approach for short-run situations where the underlying distributions are usually unknown.

Keywords: statistical process control; SPC; non-parametric control charts; LCP control charts; Lepage-type change point; generalised likelihood ratio; GLR; process monitoring; process location; process variability.

DOI: 10.1504/IJQET.2015.069234

International Journal of Quality Engineering and Technology, 2015 Vol.5 No.1, pp.40 - 56

Received: 20 Oct 2014
Accepted: 20 Jan 2015

Published online: 01 May 2015 *

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