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A New Nonparametric Control Chart for Monitoring Variability
Author(s) -
Zhou Maoyuan,
Zhou Qin,
Geng Wei
Publication year - 2016
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.1949
Subject(s) - control chart , nonparametric statistics , shewhart individuals control chart , statistical process control , chart , parametric statistics , computer science , control limits , process (computing) , \bar x and r chart , control (management) , ewma chart , statistics , mathematics , artificial intelligence , operating system
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.