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Advanced Methods for Modeling Accelerated Life Testing Data and Expediting Reliability Growth of Complex Systems

Release time:June 27, 2017 / Siying He

Topic:Advanced Methods for Modeling Accelerated Life Testing Data and Expediting Reliability Growth of Complex Systems    

Speaker:Haitao Liao    

Date:June 28 14:30 -16:00    

Venue:Weimin Building Room 320    

 

Abstract:In this talk, a new method for modeling Accelerated Life Testing (ALT) data using phase-type (PH) distributions and a general life-stress relationship formulation is introduced. The general method creates a new avenue to modeling ALT data for situations where the data-generating mechanisms are unknown or difficult to analyze using existing ALT models. A comparison study is presented to compare the performance of this method with a method based on a mixture of Weibull distributions. Another research to be presented is focused on reliability growth of complex engineering systems, for which the key components and subsystems may be developed, tested and improved independently during product development. To maximize the effectiveness of a reliability growth program, a selective Bayesian accelerated reliability growth method is developed to wisely accelerate potential failure modes and aggregate the results from component-level and subsystem-level tests for speeding up system reliability growth and determining subsequent corrective actions.    

 

Bio of the Speaker:Dr. Haitao Liao is a Professor and Hefley Endowed Chair in Logistics and Entrepreneurship in the Department of Industrial Engineering at University of Arkansas. He received a Ph.D. degree from Rutgers University. His research interests include reliability models, maintenance and service logistics, prognostics, probabilistic risk assessment, and data analytics. He has authored over 50 refereed journal publications. He currently serves as Associate Editor for the Journal of Quality Technology and IISE Transactions on Quality and Reliability Engineering. He was the Chair of INFORMS Quality, Statistics and Reliability (QSR) Section, and the President of IIE Quality Control and Reliability Engineering (QCRE) Division. He received a National Science Foundation CAREER Award in 2010, William A.J. Golomski Best Paper Awards in both 2010 and 2013, 2013 QCRE Track Best Paper Award,and 2015 Stan Ofsthun Best Paper Award.    

 

School of Reliability and System Engineering