Michael Pecht, Elviz George, Arvind Vasan
Center for Advanced Life Cycle Engineering, University of Maryland, College Park, MD 20742, United States
The rapid evolution of electronic products has resulted in numerous choices for customers. This has made for intense competition between manufacturers to reduce costs and minimize the time to market for their products. One bottle neck in getting products to market is the qualification process, which has traditionally been time consuming and often inadequate to prevent failures in field. In particular, in the past decade there have been significant numbers of microelectronic devices that have passed qualification tests but failed in the field. The resulting costs of these failures have been in billions of dollars. Thus, there is a need to develop approaches to quantification methodologies that quicken the development time but also prevent product failures in the field. This paper discusses the current state of qualification practices in the electronic industry. Then an alternative approach, called fusion prognostics for qualification is presented that can make the process more efficient and cost effective. This approach involves an in-situ qualification process that incorporates a fusion of machine learning techniques are used to monitor the degradation behaviour during testing. On the other hand, the physics of failure techniques identify critical failure mechanisms and the acceleration factors.Complete article available from the publisher and to the CALCE Consortium Members.
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