We are pleased to announce the paper entitled “Comparing methods for assessing reliability uncertainty based on pass/fail data collected over time”, authored by Jeff I. Abes, Michael S. Hamada, and Charles R. Hills, published on Quality Engineering, 30:694–700, 2018, has won the 2018-2019 ASQ RRD Best Reliability Paper Award.
One of the ASQ Reliability & Risk Division’s missions is to encourage the publication of reliability papers that are both technically sound and easy to be understood by reliability professionals. In this paper, the authors compare three statistical methods – logistic regression, Weibull failure time analysis and the RADAR method proposed by Vander Wiel et al. – for analyzing pass/fail data collected over time and use them to assess reliability of weapon systems. It is shown that these three methods may provide quite different uncertainty bounds on reliability.
Quality Engineering is a technical journal of ASQ published by Taylor & Francis. It is directed to professionals in all engineering and management fields interested in quality improvement and reliability. For additional information of ASQ RRD Best Reliability Paper Award, please contact Dr. Rong Pan at rong.pan@asu.edu.
