Self-starting monitoring of the progressive type II censoring data based on goodness-of-fit test

ABSTRACT

Censoring is a common occurrence in life testing and reliability analysis, primarily due to constraints such as time and cost. In this paper, we construct control charts using goodness-of-fit test statistics to monitor novel and effective progressive Type II censoring data. In practice, scenarios where the number of samples in Phase I is insufficient often arise, prompting the proposal of self-starting exponentially weighted moving average (EWMA) control charts based on goodness-of-fit test statistics to monitor such processes. Numerous Monte Carlo simulation experiments demonstrate the excellent performance of the control charts proposed in this paper under different settings. A breakdown time of an insulating fluid example is utilized to illustrate the proposed EWMA and self-starting EWMA control charts.

KEYWORDS:

• Self-starting control chart
• exponentially weighted moving average
• goodness-of-fit test
• progressive type II censoring scheme

Disclosure statement

No potential conflict of interest was reported by the author (s).

Supplementary data

Supplemental data for this article can be accessed online at https://doi.org/10.1080/16843703.2023.2300020.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [11871324] and the Fundamental Research Funds for the Central Universities [CXJJ-2023-392].

Notes on contributors

Wei Zhao

Wei Zhao received her B.S. and Ph.D degrees from the School of Statistics and Management, Shanghai University of Finance and Economics in 2017 and 2022, respectively. Currently, she is working as a Post-Doctoral Fellow in the Department of Industrial Engineering, Tsinghua University. Her main research interests include statistical process control, survival analysis, design of experiments and reliability analysis.

Jiao Yu

Jiao Yu is currently a PhD student at the School of Statistics and Management, Shanghai University of Finance and Economics, China. She received her B.S. degree from Beijing Jiaotong University in 2021. Her research interests include statistical quality control of survival data.

Chunjie Wu

Chunjie Wu is a professor in the School of Statistics and Management, Shanghai University of Finance and Economics, China. His research focuses on statistical process monitoring and applied statistics.