APU FMEA Validation Using Operation and Maintenance Data

##plugins.themes.bootstrap3.article.main##

##plugins.themes.bootstrap3.article.sidebar##

Published Mar 26, 2021
Chunsheng Yang Sylvain Letourneau Elizabeth Scarlett Marvin Zaluski

Abstract

FMEA(Failure Mode and Effects Analysis) is a systematic method of identifying and preventing system, product and process problems. As a standard document, FMEA is produced during the design of products or systems. However, FMEA documentation is rarely validated or updated in practice after it was generated. FMEA validation remains a challenge. In this technical report, we propose to validate FMEA using historical operation and maintenance data. First, we need to verify linkages between FMEA and corresponding operational and maintenance data. Based on statistical results obtained from historic operational data, we update useful FMEA parameters such as Failure Rate and Failure Mode Probability. The updated FMEA can provide more reliable information that could benefit the decision-making process and making maintenance a more efficient practice. The paper briefs the initial investigation and some preliminary results from APU FMEA case study

How to Cite

Yang, C., Letourneau, S., Scarlett, E., & Zaluski, M. (2021). APU FMEA Validation Using Operation and Maintenance Data. Annual Conference of the PHM Society, 1(1). Retrieved from http://papers.phmsociety.org/index.php/phmconf/article/view/1466
Abstract 251 | PDF Downloads 181

##plugins.themes.bootstrap3.article.details##

Keywords

electronic systems, failure modes effects and criticality analysis (FMECA), PHM system design and engineering

References
A. Bouti, K. D. Att, and K. Dhouib (1994), Automated Manufacturing Systems Failure Analysis Based on a Functional Reasoning. In Proceedings of 10 th ISPE IFAC International Conference on CAD/Cam, Robotics and Factories of the Future CARs & FOF’94, Information Technology for Modern manufacturing, Kanata, Ontario, Canada, pp. 423-429

H. C. Chen (1996), Failure Modes and Effects Analysis Training Manual, Personal communication, Hen Technology Inc, USA.

G. Peter and D. Rosner (1999), Towards TaskOriented User Support for Failure Mode and Effects Analysis, in Proceeding of IEA/AIE 1999, pp. 266-275.

M. Murri, M. Tavassi and A. D. Marzo( 2005), Online Plant Diagnosis system Combining FMEA Techniques and Data-Models, in Proceedings of international Conference on Experiment, Process, System Modeling, Simulation, Optimization, Athens, July, 2005.

N. D. Abajo and A. B. Diez ( 2004), ANN Quality Diagnostic Models for Packaging manufacturing: An Industrial Data Mining Case Study, InProceeding of KDD 2004, pp. 799-804.

P.C. Teoh and K. Case (2005), An Evaluation of Failure Modes and Effects Analysis Generation Method for Conceptual Design. International Journal of Computer Integrated Manufacturing. Vol. 18, No. 4, pp.279-293

I. Ruiz, E. Paniagua, J. Alberto, and J. Sanabria (2000), State Analysis: An Alternative Approach to FMEA, FAT and Markov Analysis. In Proceedings of the Annual Reliability and maintainability Symposium, pp. 370-375

N. Sellappan and R. Sivasubramanian (2008), Modified Method for Evaluation of Risk Priority Number in Design FMEA, The Icfai Journal of Operations Management, Vol. 7, No. 1, pp. 43-52, February 2008

ASENT FMEA Software (2009), FMEA RPN, available at http://www.fmea-fmeca.com/fmea-rpn.html, 200
Section
Technical Research Papers