599 – Some Current Research Problems in Statistical Process Control
Nonparametric Control Charts for Monitoring Location Based on the Exceedance Statistic
Subha Chakraborti
The University of Alabama
Marien Graham
University of Pretoria
Amitava Mukherjee
Indian Institute of Technology, Madras
Nonparametric control charts are useful when there is lack of knowledge about the underlying distribution. Two nonparametric control charts, based on the exceedance statistics, are considered for detecting a shift in the location parameter of a continuous distribution; the one being a cumulative sum (CUSUM)-type chart and the other being an exponentially weighted moving average (EWMA)-type chart. Advantages of the nonparametric charts include robustness to the violation of distributional assumptions and resistance to outliers. The fact that the exceedance statistics can save testing time and resources, as they can be applied as soon as a certain order statistic of the reference sample is available, may be a plus. A comparison with a number of existing control charts, comprising of the traditional (normal theory) CUSUM and EWMA charts for subgroup averages and the nonparametric CUSUM and EWMA charts based on the Wilcoxon rank-sum statistics, is made. It is seen that the proposed charts perform well in many cases and thus can be a useful alternative chart in practice.
