Diganta Das
Dr. Diganta Das, is a member of the research staff at the Center for Advanced Life Cycle Engineering. His other research interests include electronic parts supply chain, part recycling and reuse, LED failure mechanisms, power electronics reliability, applications of prognostics to electronic components remaining life assessment and qualification. Dr. Das has published more than 100 articles on the...read more
Prognostics and health management (PHM) is an enabling discipline consisting of technologies and methods to assess the reliability of a product in its life cycle conditions to determine the advent of failure and mitigate system risk. PHM provides functions for components prioritizing, early fault detection, fault diagnosis, remaining useful life prediction, uncertainty assessment, and life cycle cost analysis. Prognostics can be implemented through physics of failure based degradation models, analysis of collected data from the systems and their environment and more often by a combination of both approaches.
In this Webinar, Dr. Diganta Das explore some of the fundamentals of prognostics and their applications and then discuss two examples of such applications used for detection of anomaly in behavior of IGBTs and LEDs. In both cases, the data collection, analysis and the algorithms used to make the detection will be described.
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