2016Quality and Reliability Engineering InternationalRequires access

A New Nonparametric Control Chart for Monitoring Variability

Maoyuan Zhou, Qin Zhou, Wei Geng

Open publisher page 34 citations

Abstract

Statistical process control is widely used in industrial processes, service fields, among others. While parametric control charts are useful in certain processes, there is often a lack of enough knowledge about the process distribution. So, nonparametric control charts are needed in such situations. This paper develops a new nonparametric control chart based on the Ansari–Bradley nonparametric test and the effective change point model. Simulation results show that our proposed control chart is superior to other nonparametric control charts in monitoring process variability for most cases. Our proposed control chart is easy in computation, and powerful for monitoring process variability. Copyright © 2016 John Wiley & Sons, Ltd.

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What this paper is about

Statistical process control is widely used in industrial processes, service fields, among others. While parametric control charts are useful in certain processes, there is often a lack of enough knowledge about the process distribution. So, nonparametric control charts are needed in such situations. This paper develops a new nonparametric control chart based on the Ansari–Bradley nonparametric test and the effective change point model. Simulation results show that our proposed control chart is superior to other nonparametric control charts in monitoring process variability for most cases. Our proposed control chart is easy in computation, and powerful for monitoring process variability. Copyright © 2016 John Wiley & Sons, Ltd.

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Available abstract

Statistical process control is widely used in industrial processes, service fields, among others. While parametric control charts are useful in certain processes, there is often a lack of enough knowledge about the process distribution. So, nonparametric control charts are needed in such situations. This paper develops a new nonparametric control chart based on the Ansari–Bradley nonparametric test and the effective change point model. Simulation results show that our proposed control chart is superior to other nonparametric control charts in monitoring process variability for most cases. Our proposed control chart is easy in computation, and powerful for monitoring process variability. Copyright © 2016 John Wiley & Sons, Ltd.

Key concepts: Control chart, Nonparametric statistics, Shewhart individuals control chart, Statistical process control, Chart, Parametric statistics, Computer science, Control limits

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