Dr. Feng-Bin (Frank) Sun is currently a Reliability Engineering Technologist at Hitachi Global Storage Technologies (HGST). Prior to joining HGST, he had more than 23 years of working experience in both academia and industry. He published two books, both by Prentice Hall, and near 30 papers in various areas of reliability, maintainability and quality engineering. His expertise and interests include reliability modeling and risk assessment, product quality and reliability spec determination, RDT/ORT test procedure development, accelerated life test planning and quantification, parametric reliability testing and quantification, burn-in and ESS quantification and optimization, quality improvement through 6-Sigma, reliability-maintainability evaluation, preventive maintenance scheduling and spare parts provisioning for both components and systems. Dr. Sun served in the editing board as an Associate Editor for the IEEE Transactions on Reliability from 1999 to 2003. He is currently the secretary for Society of Reliability Engineers Silicon Valley Chapter, a committee member and session moderator of several international conferences on reliability. He received his B.S. degree in Mechanical Engineering from Southeast University (China), M.S. degree in Reliability from Shanghai University (China), and Ph.D. in Reliability from University of Arizona.
Parametric-Degradation-Based Virtual Failures and Reliability Assessment and Monitoring (基于参数退化的虚拟失效概念和可靠性评估及监测)
Dr. Feng-Bin (Frank) Sun is currently a Reliability Engineering Technologist at Hitachi Global Storage Technologies (HGST). Prior to joining HGST, he had more than 23 years of working experience in both academia and industry. He published two books, both by Prentice Hall, and near 30 papers in various areas of reliability, maintainability and quality engineering. His expertise and interests includ...read more
This talk presents a parametric perspective of product reliability in terms of virtual failures quantified by time degradation of product failure-governing critical parameters (CP). Traditionally, product reliability is quantified and measured by the confirmed failures through failure analysis (FA); i.e., a product is characterized by two distinctive states: either "functioning" ("surviving") or "failed". However, similar to human being, inside a product there is an ongoing health degrading process that could cause the product to a critical, or "near-death" condition. Depending on the degree of such sub-healthy condition, a product may not manifest itself as a physical failure on the macro level during a life test, but it can soon become a true failure after a short time of field operation.To account for the field reliability impact of such invisible but sub-healthy product, the concept of "virtual failure" is proposed and its impact on the product long-term reliability is quantified based on the correlation between the incident of each CP exceeding the trigger limit and the incident of its actual failing in reliability life test. The objective of this paper is to describe the importance of tracking product parametric performance during reliability life test, the identification of failure-indicative critical parameters, their degradation pattern, measurement algorithm, triggering mechanism and limits, and quantification of their impact on long-term reliability.
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