On the performance of the adaptive EWMA chart for monitoring time between events

ABSTRACT

In high-quality processes, events related to non-quality rarely occur and the times between these events (TBE) is likely to follow a skewed distribution like the gamma distribution. In order to monitor TBE data, an Adaptive Exponential Weighted Moving Average (AEWMA) control chart is proposed in this paper. This chart is designed to perform well over a range of shifts instead of being only efficient for a particular shift. An extensive performance analysis shows that, for most shifts, the Average Run Length (ARL) of the proposed chart performs better than other already existing control charts. In order to help the quality practitioner, some guidelines for choosing the most effective scheme in practice are provided. Finally, an illustrative example of the proposed scheme is also presented. Supplementary materials for this article are available online.

Keywords:

• AEWMA chart
• TBE
• gamma distribution
• average run length

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by National Natural Science Foundation of China [ 71802110;71801049], Natural Science Foundation of Jiangsu Province [BK20170894], Humanity and Social Science Youth Foundation of Ministry of Education of China [17YJC630231]  and The Project of Philosophy and Social Science Research in Colleges and Universities in Jiangsu Province [2020SJA0090] and Key Research Base of Philosophy and Social Sciences in Jiangsu—Information Industry Integration Innovation and Emergency Management Research Center.