【Title】Semi-parametric Bayesian Accelerated Life-Test Modeling for Nanoelectronics

【Speaker】Tao Yuan, Ph.D., Assistant Professor,Department of Industrial and Systems Engineering,Ohio University,Athens, Ohio, USA 

【Host】Dr. Zhizhong Li 

【Time】November 12, 2012（Monday）, 14:00 – 15:00 

【Location】Room 510, Shun-de Building 

【Abstract】Semi-parametric Bayesian models are developed to model accelerated life-testing (ALT) data of nanoelectronic devices. Reliability is a critical factor in determining the success of nanoelectronics manufacturing. As new generations of nanoelectronic devices are invented almost daily, design engineers and reliability engineers become less familiar with the failure mechanisms of these devices because of the involvement of nano-scale structures, novel materials, and new fabrication processes. This poses a serious challenge in modeling the reliability of nanoelectronics using traditional reliability analysis methods, which rely on the assumption of a restrictive parametric model to describe the well-known failure mechanism. The difficult challenge associated with the reliability modeling in nanoelectronics, however, constitutes a fertile ground for nonparametric Bayesian methods. The proposed semi-parametric ALT models combine the nonparametric Dirichlet process mixture models to describe the failure-time distribution at a given stress condition and the log-linear stress-life relationship in a Bayesian framework. The proposed models have been applied to analyzereliability data of two newly developed nanoelectronic devices, doped high-k dielectric MOS capacitorsand nanocrystals embedded doped high-k dielectric MOS memories, collected from a constant-stress ALT and a step-stress ALT, respectively. The results demonstrate the efficiency and flexibility of the proposed models.

【Brief bio】Dr. Tao Yuan is an assistant professor in the Industrial and Systems Engineering Department at Ohio University. He received the Bachelor of Engineering degree in Thermal Engineering from Tsinghua University with honorsin 2000. He obtained the Master of Science degree in Aerospace Engineering in 2003 and the Master of Engineering degree in Industrial Engineering in 2004 from Texas A&M University, College Station, and the Ph.D. degree in Industrial Engineering from The University of Tennessee, Knoxville in 2007. He joined the Industrial and Systems Engineering Department of Ohio University in September 2008. His research interests are in yield, quality, and reliability issues related to nanoelectronics manufacturing, fatigue behavior of advanced engineering materials, applied statistics and stochastic processes, and Bayesian statistics. 

Looking forward to your attendance.