The Use of Multivariate Parametric Hotelling–T2 and Nonparametric Bootstrap Charts in Quality Control Using Simulation

Post by: Muthanna mjdes
November 7, 2022
Comments off

Asma Ghalib Jaber ^*a & Fahd Hussein Enad^b

a University of Baghdad , college of Administration and Economics.

Abstract

Quality control is an effective statistical tool in the field of controlling the productivity to monitor and conform the manufactured products to the standard qualities and the certified criteria for some products and services . Its main purpose is to cope with the production and industrial development in the business and competition market. Quality control charts are used to monitor the qualitative properties of the production procedures in addition to detect the abnormal deviations in the production procedure. The parametric Hotelling–T2 control charts and the nonparametric multivariate Bootstrap control charts methods are used. The latter one is one of the nonparametric methods that doesn’t require any assumptions regarding the distribution of the data or determine the control limits in monitoring the production procedure when the data does not follow the normal distribution or has an unknown distribution. The aim of this paper is to monitor the production procedure throughout a number of variables simultaneously to reflect the quality of the produced material. Simulation experiments were used with deferent significance levels to illustrate the way in which the multivariate Hotelling–T2 and Bootstrap charts methods work while adopting the average range length criterion to demonstrate the performance and efficiency of the used methods. The results show that the method of nonparametric Bootstrap charts had a good performance especially at significance levels with long range.