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Predictive reliability, prognostics and risk assessment for power modules

Predictive reliability, prognostics and risk assessment for power modules

Bailey, C., Lu, H., Yin, C. and Ridout, S. (2008) Predictive reliability, prognostics and risk assessment for power modules. CIPS 2008: 5th International Conference on Integrated Power Electronics Systems. Proceedings, March, 11-13, 2008 Nuremberg/Germany. ETG-Fachbericht (111). VDE Verlag GmbH, Berlin-Offenbach, Germany, pp. 19-26. ISBN 9783800730896

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Abstract

This paper describes a framework that is being developed for the prediction and analysis of electronics power module reliability both for qualification testing and in-service lifetime prediction. Physics of failure (PoF) reliability methodology using multi-physics high-fidelity and reduced order computer modelling, as well as numerical optimization techniques, are integrated in a dedicated computer modelling environment to meet the needs of the power module designers and manufacturers as well as end-users for both design and maintenance purposes. An example of lifetime prediction for a power module solder interconnect structure is described. Another example is the lifetime prediction of a power module for a railway traction control application. Also in the paper a combined physics of failure and data trending prognostic methodology for the health monitoring of power modules is discussed.

Item Type: Book Section
Additional Information: [1] Invited Paper, for Session 1: Robustness Validation. Presented at the 5th International Conference on Integrated Power Electronics Systems, CIPS 2008, held 11-13 March 2008, in Nuremberg, Germany.
Uncontrolled Keywords: Power Electronic Module (PEM), predictive reliability, risk assessment
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Q Science > QA Mathematics
Pre-2014 Departments: School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis
School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis > Computational Mechanics & Reliability Group
School of Computing & Mathematical Sciences > Department of Computer Systems Technology
School of Computing & Mathematical Sciences > Department of Mathematical Sciences
Related URLs:
Last Modified: 14 Oct 2016 09:03
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/1257

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