Modified one-sided EWMA charts for monitoring time between events

Abstract

Control charts based on Time Between Events (TBE) have been shown to be effective in high quality processes, where the defects or failures (events) occur at a very low probability. The occurrences of events are usually modeled as a homogeneous Poisson process. The TBE data is likely to follow a skewed distribution, such as the gamma distribution. In order to monitor high quality processes, this study focuses on the development of modified one-sided Exponentially Weighted Moving Average (EWMA) TBE charts. The Monte-Carlo simulation method is used to evaluate the Run Length (RL) properties of the proposed schemes. The results show that the proposed schemes are more sensitive to process shifts than some competitive procedures. Finally, a real data example is provided to illustrate the implementation of the proposed charts.

Keywords:

• Gamma distribution
• Modified one-sided EWMA
• Time between events
• Charts

Additional information

Funding

The authors are grateful to the AE and the anonymous reviewers for their useful suggestions, which enabled the quality of the present manuscript to be improved from the original version. This work are supported by the National Natural Science Foundation of China (No. 71802110, 71801049, 11701437, 71872088, 72072080), National Social Science Fundation of China (No. 20BGL182), Key Research Base of Philosophy and Social Sciences in Jiangsu-Information Industry Integration Innovation and Emergency Management Research Center.