Challenges and new methods for designing reliability experiments

Abstract

Engineers use reliability experiments to determine the factors that drive product reliability, build robust products, and predict reliability under use conditions. This article uses recent testing of a howitzer to illustrate the challenges in designing reliability experiments for complex, repairable systems. We review research in complex system reliability models, failure-time experiments, and experimental design principles. We highlight the need for reliability experiments that account for various intended uses and environments. We leverage lessons learned from current research and propose methods for designing an experiment for a complex, repairable system.

Keywords:

• reliability experiments
• complex system reliability
• experimental design
• restricted randomization
• power analysis

Additional information

Notes on contributors

Laura J. Freeman

Laura J. Freeman is an Assistant Director of the Operational Evaluation Division at the Institute for Defense Analyses. In that position, she established and developed an interdisciplinary analytical team of statisticians, psychologists, and engineers to advance scientific approaches to DoD test and evaluation. Dr Freeman has a BS in Aerospace Engineering, a MS in Statistics, and a PhD in Statistics, all from Virginia Tech. Her PhD research was on design and analysis of experiments for reliability data.

Rebecca M. Medlin

Rebecca Medlin is a Research Staff Member in the Operational Evaluation Division at the Institute for Defense Analyses. She supports the Air Warfare Test and Evaluation Task providing expertise in statistics. Her areas of emphasis include design of experiments and reliability analysis. She received her PhD in statistics from Virginia Tech.

Thomas H. Johnson

Thomas H. Johnson is a Research Staff Member in the Operational Evaluation Division at the Institute for Defense Analyses, Alexandria, VA, where he supports the Live Fire Test and Evaluation Task providing expertise in statistics. His areas of emphasis include sample size determination, sensitivity experiments, and acceptance sampling plans. He received a BS degree from Boston University, and MS and PhD degrees from Old Dominion University, all in Aerospace Engineering.