![Sample our Engineering & Technology journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5933/TOC-Subject-Sample-2021-Engineering-Tech.jpg"})
Abstract
Polymer-composite materials have become key components in the transportation and alternative-energy industries, as they are more lightweight than homogeneous metals and alloys yet still retain comparable levels of strength and endurance. To understand how these polymer composites perform after long periods of use, material manufacturers commonly use cyclic fatigue testing. The current industrial standards include test plans with balanced designs and equal spacing of stress levels which, in many cases, are not the most statistically efficient designs. In this paper, we present optimal designs with the goal of minimizing the weighted sum of asymptotic variances of an estimated lifetime percentile at selected design stress levels. These designs are based on a physical model adapted from the fatigue literature, which is more suitable for modeling cyclic fatigue of polymer composites than the model used in the current industrial standards. We provide a comparison between our optimal designs and the traditional designs currently in use and ultimately propose a compromise design for use by practitioners in order to ensure robustness against deviations from the underlying assumptions.
Additional information
Notes on contributors
Caleb B. King
Dr. King is a Research Statistician at Sandia National Labs. His email address is [email protected].
Yili Hong
Dr. Hong is an Associate Professor at Virginia Tech. His email address is [email protected]. He is the corresponding author.
Stephanie P. Dehart
Dr. DeHart is a Principal Statistician at Eastman Chemical Company. She is a full member of ASQ. Her email address is [email protected].
Rong Pan
Dr. Pan is an Associate Professor at Arizona State University. He is a Senior Member of ASQ. His email address is [email protected].
