Nonparametric adaptive EWMA-type control chart with variable sampling intervals

Abstract

A nonparametric process monitoring scheme with Variable Sampling Intervals (VSI) is investigated to monitor the median in this paper. The proposed scheme is based on the sign test statistic and used a new adaptive-type exponentially weighted moving average control chart. A discrete-state Markov Chain method is presented, and the exact Average Time to Signal (ATS) properties are discussed. The comparative results indicate that the proposed chart can reduce the time in detecting shifts than the corresponding schemes for the fixed sampling interval and provide higher sensitivity for detecting shifts with various magnitudes. The proposed chart’s in-control robustness is demonstrated for different continuous distributions using numerical results based on the Monte-Carlo simulation. The implementation of this VSI nonparametric chart is also explained through an illustrative example.

Keywords:

• Adaptive EWMA
• Average time to signal
• Nonparametric control chart
• Variable sampling intervals

Acknowledgement

The authors express their sincere thanks to the editor and the reviewers for their helpful suggestions and comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work is supported by National Nature Science Foundation of China, Grant/Award Numbers: 71904078, 72101123; Philosophy and Social Sciences Foundation of Jiangsu Universities, Grant/Award Number: 2020SJA0090; Natural Science Foundation of Jiangsu Province, Grant/Award Number: BK20200750