Portal de Periódicos da CAPES

An Enhanced Parenting Process: Predicting Reliability in Product's Design Phase

2011; Taylor & Francis; Volume: 23; Issue: 4 Linguagem: Inglês

10.1080/08982112.2011.603110

1532-4222

Luis Mejia Sanchez, Rong Pan,

Optimal Experimental Design Methods

ABSTRACT The philosophy of build-in reliability (BIR) or design for reliability (DFR) emphasizes the value of reliability prediction at a product's very early design stage. Due to the lack of reliability data, the reliability prediction in this phase often utilizes auxiliary information such as the reliability information of similar products or components. In this article, we propose an enhanced parenting process, which consists of rigorous mathematical formulations and provides statistical inference on the failure rate of the new product. An example is given to demonstrate our proposed method. KEYWORDS: design for reliabilityearly reliabilityexpert opinion elicitationimportance index ACKNOWLEDGMENT We thank two anonymous referees for their constructive comments and suggestions on the previous version of this article. Notes 1If the combination rule is such that the probabilities are unaffected by refinements of the partition of alternatives (i.e., parameters to be estimated), then the rule is said to possess the marginalization property (Cooke Citation1991). 2All values are presented in repairs per one hundred. Additional informationNotes on contributorsLuis Mejia Sanchez Luis Mejia Sanchez is a PhD candidate in the School of Computing, Informatics, and Decision Systems Engineering at Arizona State University. He received a master degree in Industrial Engineering from Arizona State University in 2010 and a master degree in Quality and Productivity from Tecnologico de Monterrey, Mexico in 2006. His research interests include quality and reliability engineering, integration of information and design of experiments. Rong Pan Dr. Rong Pan is an Associate Professor in the School of Computing, Informatics, and Decision Systems Engineering at Arizona State University. He received his doctorate in Industrial Engineering from the Pennsylvania State University in 2002. Prior to Arizona State University in 2006, he was an assistant professor of Industrial Engineering at the University of Texas at El Paso. His research interests include quality and reliability engineering, design of experiments, time series analysis, and statistical learning theory.