讲座时间：2018年10月11日(周四)15:00-16:00  

主讲人：洪益力

讲座题目：Sequential Test Planning for Polymer  Composites

讲座地点：综合大楼601会议室

摘要：Polymer composite materials are widely used in areas  such as aerospace and alternative energy industries, due to their lightweight  and comparable levels of strength and endurance. To ensure that the material can  last long enough in the field, accelerated cyclic fatigue tests are commonly  used to collect data and then make predictions for the field performance. Thus,  a good testing strategy is desirable for evaluating the property of polymer  composites. While there has been a lot of development in optimum test planning,  most of the methods assume that the true parameter values are known (i.e., the  true values are used as the planning values). However, in reality, the true  model parameters may depart from the planning values. In this paper, we propose  a sequential strategy for test planning, and use a Bayesian framework for the  sequential model updating. We also use extensive simulations to evaluate the  properties of the proposed sequential test planning strategy. Finally, we  compare the proposed method to traditional optimum designs. Our results show  that the proposed strategy is more robust and efficient, as compared to the  optimum designs, when true values of parameters are unknown.

主讲人简介： Yili Hong received a BS in statistics in 2004  from University of Science and Technology of China. He received his MS in  statistics in 2005 and PhD in statistics in 2009 from Iowa State University. He  is currently an Associate Professor in the Department of Statistics at Virginia  Tech. His research mainly focuses on statistical reliability. Areas include  lifetime data analysis, field failure prediction, accelerated life test planning  and analysis, accelerated degradation test planning and data analysis, system  health monitoring, and applications in engineering, chemistry and material  sciences. His research has been published in top journals such as  Technometrics, JQT,  Annals of Applied  Statistics, JASA,  IEEE Transactions on Reliability, and  Quality Engineering. He is one of the  recipients of the 2011 DuPont Young Professor Award. He is an associate editor  for Technometrics and  JQT. He is a co-guest editor for a  special issue on big data in reliability for JQT. He is an  elected member of International Statistical Institute.