A study of attribute control charts for censored lifetime data

Abstract

In many recent articles authors have advocated the use of attribute charts based on the number of censored values for monitoring censored lifetime data. In this article we compare the average run-length performance of one-sided and two-sided Shewhart charts based on the conditional expected value (CEV) with the corresponding attribute charts. The overall findings indicate that using an attribute chart to monitor the mean of a Weibull lifetime probability distribution with right censoring does not perform as well as the CEV-based chart.

Keywords:

• conditional expected value
• Monte Carlo simulation
• Shewhart chart
• type-I censoring

Acknowledgment

The authors are thankful to the anonymous reviewers for providing useful comments that have led to an improved version of the article.

Disclosure statement

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

Additional information

Notes on contributors

Abdul Haq

Abdul Haq is an Associate Professor at the Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan. His research interest is in Statistical Process Monitoring.

William H. Woodall

William H. Woodall is an Emeritus Professor with the Department of Statistics, Virginia Tech. He is a fellow of the American Statistical Association, a fellow of the American Society for Quality, and an Elected Member of the International Statistical Institute. He was a recipient of the Box Medal in 2012, the Shewhart Medal in 2002, the Hunter Award in 2019, the Youden Prize in 1995 and 2003, the Brumbaugh Award in 2000 and 2006, the Bisgaard Award in 2012, the Nelson Award in 2014, the Ott Foundation Award in 1987, and the Best Paper Award for IIE Transactions on Quality and Reliability Engineering in 1997. He was the Editor of the Journal of Quality Technology from 2001 to 2003. He is currently Editor-Elect of Quality Engineering.

Stefan H. Steiner

Stefan H. Steiner is a Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. His primary research interests include quality improvement, process monitoring, experimental design and measurement system assessment. He is a Fellow of the American Statistical Association and the American Society for Quality.