Journal Published Online: 26 March 2019
Volume 48, Issue 4

On Designing Distribution-Free Homogeneously Weighted Moving Average Control Charts

CODEN: JTEVAB

Abstract

There are many practical situations in which the underlying process distribution is either completely unknown or partially known but deviates from normality. In such cases, the performance of the traditional parametric control charts deteriorates, and nonparametric control charts are considered as a robust alternative for monitoring the process. In this article, two new nonparametric homogeneously weighted moving average (NPHWMA) control charts are proposed for monitoring the deviations in process location from the target value. The proposed charts assign a specific weight to the current sample information, and the remaining weight is equally distributed among the previous samples. The proposed NPHWMA charts are based on sign test and Wilcoxon signed-rank test for process monitoring under the skewed and symmetric distributions, respectively. The Monte Carlo simulations are used to study the run length properties and compare the performance of the proposed charts with some existing control charts. It is found that the proposed charts outperform their existing counterparts. Empirical illustrations are provided for practical implementation of the proposed charts.

Author Information

Raza, Muhammad Ali
Department of Statistics, Government College University Faisalabad, Faisalabad, Pakistan
Nawaz, Tahir
School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai, China Department of Statistics, Government College University Faisalabad, Faisalabad, Pakistan
Han, Dong
School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai, China
Pages: 18
Price: $25.00
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Details
Stock #: JTE20180550
ISSN: 0090-3973
DOI: 10.1520/JTE20180550