Challenges in Reliability Assessment for Electronics

Article Preview

Abstract:

There has been a growing interest in assessing the ongoing reliability of electronics and systems in order to predict failures and provide warning to avoid catastrophic failure. Methods based on prognostics and health management shows an enabling technology to assess the reliability of electronics and systems under its actual application conditions. However, many challenges in implementation of methods based on PHM still remain including: environmental and usage profiles for life-cycle loads, identification of failure mechanism, identification of failure PoF model, identification of parameters to be monitored, approaches to anomaly detection. These challenges were presented and discussed, and would be carried out by developing methodologies and techniques.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 118-120)

Pages:

419-423

Citation:

Online since:

June 2010

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2010 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] M. Pecht. Prognostics and Health Management of Electronics, Wiley-Interscience, NY(2008).

Google Scholar

[2] Jie Gu, Daniel Lau and M. Pecht: IEEE RAMS, Chongqing(2009), pp.912-919.

Google Scholar

[3] IEEE Standard 1413. 1. IEEE Guide for Selecting and Using Reliability Predictions Based on IEEE 1413, NY(2002).

DOI: 10.1109/ieeestd.2003.94232

Google Scholar

[4] N. Vichare: Prognostics and health management of electronics by utilizing environmental and usage loads, University of Maryland, USA(2005).

Google Scholar

[5] J. Gu and M. Pecht: IEEE RAMS, Las Vegas(2008), pp.481-487.

Google Scholar

[6] S. Mathew: Health status assessment methodology for electronic hardware, University of Maryland, USA(2005).

Google Scholar

[7] J. Gu, D. Barker and M. Pecht: Microelectronics Reliability, Vol. 47(2007), pp.1849-1856.

Google Scholar

[8] S. Kumar, M. Torres, M. Pecht and Y. C. Chan: Intelligence for Anomaly Detection, Diagnosis, and Prognosis, Hong Kong(2008).

Google Scholar

[9] C. Sankavaram, B. Pattipati, A. Kodali, K. Pattipati, M. Azam, S. Kumar and M. Pech: IEEE Conference on Automation Science and Engineering, India(2009), pp.96-101.

DOI: 10.1109/coase.2009.5234108

Google Scholar

[10] S. F. Cheng and M. Pecht: IEEE Conference on Automation Science and Engineering Bangalore, India(2009), pp.102-107.

Google Scholar

[11] N. Vichare, P. Rodgers, V. Eveloy, M. Pecht1: Quality Technology & Quantitative Management, Vol. 4 (2007), pp.235-250.

Google Scholar

[12] S. Kumar and M. Pecht: IEEE Transactions on components and packaging technologies, Vol. 32 (2009), pp.667-676.

Google Scholar

[13] N. Vichare and M. Pecht: IEEE Transactions on Components and Packaging Technologies, Vol. 29 (2006): 222-229.

Google Scholar

[14] Sathyanarayan Ganesan, V. Eveloy, D. Das and M. Pecht: IEEE Workshop on Accelerated Stress Testing & Reliability, Austin(2005).

Google Scholar

[15] S. Mathew, D. Das, R. Rossenberger and M. Pecht: International Conference on Prognostics and Health Management(2008), pp.1-6.

DOI: 10.1109/phm.2008.4711438

Google Scholar

[16] Jin Qin: A new physics-of-failure based VLSI circuits reliability simulation and prediction methodology, University of Maryland, USA(2007).

Google Scholar

[17] J. Gu, N. Vichare, E. Tinsley, M. Pecht: IEEE Transactions on components and packaging technologies, 32(3)(2009), pp.550-556.

DOI: 10.1109/tcapt.2009.2013202

Google Scholar