ÿþ<html><head> <title>A Hybrid Prognostics Methodology for Electronic Products </title></head> <body bgcolor="#ffffff"> <center><i>Special Session on Computational Intelligence for Anomaly Detection, Diagnosis, and Prognosis, IEEE World Congress on Computational Intelligence (WCCI 2008)</i> <br><h2>A Hybrid Prognostics Methodology for Electronic Products </h2> <br><br><b>Y. C. Chan</b><br> Electronic Packaging and Assemblies (EPA) Centre<br> Department of Electronic Engineering<br> City University of Hong Kong, HK<br><br> <b>Sachin Kumar</b><br> Prognostics and Health Management Laboratory<br><br> <b>Myra Torres</b><br> Prognostics and Health Management Laboratory<br><br> <b>Michael Pecht</b><br> Center for Advanced Life Cycle Engineering (CALCE)<br> University of Maryland<br> College Park, MD 20742, USA<br><br> </center> <b>Abstract:</b> <p>Prognostics and health management enables in-situ assessment of a product s performance degradation and deviation from an expected normal operating condition. A unique hybrid prognostics and health management methodology combining both data-driven and physics-of-failure models is proposed for fault diagnosis and life prediction. The shortcomings of using data-driven and physics-of-failure methodologies independently are discussed. These approaches estimate future system health, based on a systems current health status, historical performance, and operating environmental conditions. Although these methodologies are applicable to legacy, current, and future electronics, and ranging from components to circuit assemblies and electronic products, the hybrid approach is preferred due to its capability to include potential failure precursor parameters with failure mechanism, thus improving accuracy in prognostic estimates. Various works on data-driven and physics-of-failure approaches to prognostics for electronics are summarized and a hybrid methodology case study is presented. </p> <p><a href="../../fulltext/2008/08_Sachin_hybridProgntcs_WCCI.pdf">Complete article</a> is available to CALCE PHM Consortium Members.</p> <p><font size="-2"><font color="red">© IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.</font></font> </p> <hr><br> <center> [<a href="http://www.calce.umd.edu">Home Page</a>] [<a href="../../">Articles Page</a>] </center> <center><font size="-1">Copyright ýÿ 2008 by CALCE and the University of Maryland, All Rights Reserved </font></center> </body></html>