Predicting the reliability of a system in its actual life cycle conditions and estimating its time to failure is helpful in decision making to mitigate system risks. There are three approaches to prognostics: the physics-of-failure approach, the data-driven approach, and the fusion approach. A key requirement in all these approaches is the identification of the appropriate parameter(s) to monitor the collection of the data that can be employed to assess impending failure. This article presents the physics-of-failure approach, which uses failure modes, mechanisms, and effects analysis (FMMEA) to enhance prognostics planning and implementation. This article also presents the fusion approach to prognostics and the applicability of FMMEA to this approach. As an example, a case of generating FMMEA information, and using that to identify appropriate parameters to monitor, is presented.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
Tax calculation will be finalised during checkout.
Pecht, M.: Prognostics and Health Management of Electronics. Wiley-Interscience, New York, NY (2008)
DoD 5000.2 Policy Document: Defense Acquisition Guidebook, Chapter 5.3—Performance Based Logistics (2004)
Vichare, N., Pecht, M.: Prognostics and health management of electronics. IEEE Trans. Compon. Packag. Technol. 29(1), 222–229 (2006)
Pecht, M., Dasgupta, A.: Physics-of-failure: an approach to reliable product development. J. Inst. Environ. Sci. 38, 30–34 (1995)
Ganesan, S., Eveloy, V., Das, D., Pecht, M.: Identification and utilization of failure mechanisms to enhance FMEA and FMECA. In: Proceedings of the IEEE Workshop on Accelerated Stress Testing & Reliability (ASTR), Austin, Texas, October 2–5, 2005
IEEE Standard 1413.1-2002: IEEE Guide for Selecting and Using Reliability Predictions Based on IEEE 1413. IEEE Standard (2003)
JESD659-A: Failure-Mechanism-Driven Reliability Monitoring. EIA/JEDEC Standard (1999)
JEP143A: Solid-State Reliability Assessment and Qualification Methodologies. JEDEC Publication (2004)
JEP150: Stress-Test-Driven Qualification of and Failure Mechanisms Associated with Assembled Solid State Surface-Mount Components. JEDEC Publication (2005)
JESD74: Early Life Failure Rate Calculation Procedure for Electronic Components. JEDEC Standard (2000)
JESD94: Application Specific Qualification Using Knowledge Based Test Methodology. JEDEC Standard (2004)
JESD91A: Method for Developing Acceleration Models for Electronic Component Failure Mechanisms. JEDEC Standard (2003)
SEMATECH, #00053955A-XFR: Semiconductor Device Reliability Failure Models. SEMATECH Publication (2000)
SEMATECH, #00053958A-XFR: Knowledge-Based Reliability Qualification Testing of Silicon Devices. SEMATECH Publication (2000)
SEMATECH, #04034510A-TR: Comparing the Effectiveness of Stress-Based Reliability Qualification Stress Conditions. SEMATECH Publication (2004)
SEMATECH, #99083810A-XFR: Use Condition Based Reliability Evaluation of New Semiconductor Technologies. SEMATECH Publication (1999)
Gu, J., Pecht, M.: Prognostics and Health Management Using Physics of Failure. In: 54th Annual Reliability and Maintainability Symposium (RAMS), Las Vegas, Nevada, January 2008
Cheng, S., Pecht, M.: A Fusion Prognostics Method for Remaining Useful Life Prediction of Electronic Products. In: 5th Annual IEEE Conference on Automation Science and Engineering, Bangalore, India, August 22–25, 2009
Brown, G.: How PC power supplies work [Online]. http://computer.howstuffworks.com/power-supply.htm. Accessed 24 Jan 2011
Chen, Y., Chou, M., Wu, H.: Electrolytic capacitor failure prediction of LC filter for switching-mode power convertors. In: Industry Applications Conference, pp. 1464–1469 (2005)
Orsagh, R., Brown, D., Roemer, M., Dabney, T., Hess, A.: Prognostic health management for avionics system power supplies. In: IEEE Aerospace Conference, Big Sky, MT, pp. 3585–3592 (2005)
Goodman, D., Vermeire, B., Spuhler, P., Venkatramani, H.: Practical application of PHM/prognostics to COTS power convertors. In IEEE Aerospace Conference, Big Sky, MT, pp. 3573–3578 (2005)
The authors would like to thank the Center for Advanced Life Cycle Engineering (CALCE) at the University of Maryland, and the more than 100 companies and organizations that support its research annually. The authors thank the members of the Prognostics and Health Management Consortium (PHMC) at CALCE for providing their support for this study. The authors thank Mr. Carl Carlson (Reliasoft Corp.) for his comments and suggestions. The authors thank Mr. Mark Zimmerman (CALCE) for editing this article.
About this article
Cite this article
Mathew, S., Alam, M. & Pecht, M. Identification of Failure Mechanisms to Enhance Prognostic Outcomes. J Fail. Anal. and Preven. 12, 66–73 (2012). https://doi.org/10.1007/s11668-011-9508-2
- Failure mechanisms
- Precursor parameters
- Remaining life
- Fusion prognostics