Title: Performance of Max-HEWMAMS control chart for simultaneous monitoring of process mean and variability in the presence of measurement errors
Authors: Maziar Saemian; Mohammad Reza Maleki; Ali Salmasnia
Addresses: Department of Industrial Engineering, University of Eyvanekey, Semnan, Iran ' Industrial Engineering Group, Golpayegan College of Engineering, Isfahan University of Technology, Golpayegan, 87717-67498, Iran ' Department of Industrial Engineering, Faculty of Engineering, University of Qom, Iran
Abstract: In recent years, the simultaneous monitoring of the process mean and variability has received increasing attention in statistical process monitoring (SPM). Most of control charts in this context have been carried out under the assumption of no measurement errors. This paper develops the Max-HEWMAMS chart for simultaneous detection of mean and variance shifts when the measurements are imprecise due to the gauge inaccuracy. Multiple measurements approach is employed to reduce the impact of measurement errors on detecting ability of Max-HEWMAMS chart. Extensive simulations are conducted to explore the impact of measurement errors on run length properties of Max-HEWMAMS chart. The results indicate under different out-of-control scenarios including mean, variance, and joint shifts, the measurement error has an undesired impact on detecting efficiency of the Max-HEWMAMS chart. It is also confirmed that taking multiple measurements per item improves the performance of Max-HEWMAMS chart when the observations are contaminated with measurement errors. Finally, the adverse impact of gauge imprecision on sensitivity of the Max-HEWMAMS chart is probed by a real-life data example.
Keywords: Max-HEWMAMS control chart; measurement errors; multiple measurements approach; simultaneous monitoring; run length.
International Journal of Applied Decision Sciences, 2023 Vol.16 No.2, pp.165 - 188
Received: 16 Oct 2021
Accepted: 23 Nov 2021
Published online: 10 Mar 2023 *