Generating a diagnostic system from an automated FMEA



Published Mar 26, 2021
Neal Snooke


This paper builds on the ability to produce a comprehensive automated Failure Modes and Effects Analysis using qualitative model based reasoning techniques. From the FMEA output a diagnostic system comprised of a set of symptoms and associated potential faults can be generated and used as the basis of an on-board or off-board diagnostic system. This makes it is easy to propose additional sensing possibilities for the system, however a method is required to allow an appropriate set of sensors to be selected that provide the required level of diagnosability. The large number of competing factors outside of the scope of the modelling combined with the additional system knowledge required makes it difficult to optimise automatically. This paper therefore documents a semi automated technique that provides an engineer with easy access to information about diagnostic capability via a matrix visualisation technique. The focus of the project was the fuel system of an Uninhabited Aerial Vehicle(UAV) although the system has also been used on an automotive electrical system, and is applicable to a wide range of schematic and component based systems.

How to Cite

Snooke, N. (2021). Generating a diagnostic system from an automated FMEA. Annual Conference of the PHM Society, 1(1). Retrieved from
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(ASTRAEA, 2009) ASTRAEA., April 2009.
(Bell and Snooke, 2004) J. Bell and N. A. Snooke. Describing system functions that depend on inter- mittent and sequential behavior. In Proceedings 18th International Workshop on Qualitative Rea- soning, QR2004, pages 51–57, 2004.
(Bell et al., 2007) J. Bell, N. A. Snooke, and C. J. Price. A language for functional interpretation of model based simulation. Advanced Engineering In- formatics, 21(4):398–409, Oct 2007.
(Debouk et al., 1999) Rami Debouk, Ste ́phane Lafor- tune, and Demosthenis Teneketzis. On an optimiza- tion problem in sensor selection for failure diagno- sis. In in Proc. of the 38th IEEE Conf. on Deci- sion and Control, pages 4990–4995. University of Michigan, 1999.
(Lee and Ormsby, 1991) Mark H. Lee and Andrew R. T. Ormsby. A qualitative circuit simulator. In Second Annual Conference on AI Simulation and Planning in High Autonomy Systems. IEEE, 1991.
(Lee, 2000) Mark H. Lee. Qualitative modelling of linear networks in engineering applications. In Pro- ceedings 14th European Conference on Artificial Intelligence ECAI 2000, pages 161–165, Berlin, 2000.
(Maul et al., 2007) William A. Maul, George Kopasakis, Louis M. Santi, Thomas S. Sowers, and Amy Chicatelli. Sensor selection and optimization for health assessment of aerospace systems. Tech- nical Report NASA/TM—2007-214822, NASA,, 2007.
(Mushini and Simon, 2005) R. Mushini and Dan Si- mon. On optimization of sensor selection for air- craft gas turbine engines. In 18th International Conference on Systems Engineering, pages 9–14. ISBN: 0-7695-2359-5, August 2005.

(Price et al., 1997) C. J. Price, D. R. Pugh, N. A. Snooke, J. E. Hunt, and M. S. Wilson. Combining functional and structural reasoning for safety anal- ysis of electrical designs. Knowledge Engineering Review, 12(3):271–287, 1997.

(Price et al., 2003) Christopher J. Price, Neal A. Snooke, and Stuart D. Lewis.
Adaptable modeling of electrical systems. In Paulo Salles and Bert Bredeweg, editors, Proceedings of 17th In- ternational Workshop on Qualitative Reasoning (QR2003), pages 147–153, Brasilia, Brazil, 2003.
(Price et al., 2006) C. J. Price, N. A. Snooke, and S. D. Lewis. A layered approach to automated elec- trical safety analysis in automotive environments. Computers in Industry, 57(5):451–461, 2006.
(Snooke and Bell, 2002) Neal A. Snooke and Jonathan Bell. Abstracting automotive system models from component-based simulation with multi level behaviour. In Sixteenth International Workshop on Qualitative Reasoning (QR02), pages 151–160, Barcelona, Spain, 2002.
(Snooke, 2007) N. A. Snooke. M2cirq: Qualitative fluid flow modelling for aerospace fmea applica- tions. In Proceedings 21st international workshop on qualitative reasoning, pages 161–169, 2007.
(Spanache et al., 2004) Stefan Spanache, Teresa Es- cobet, and Louise Trave ́-Massuye`s. Sensor place- ment optimisation using genetic algorithms. In Pro- ceeding DX04, pages 179–183, 2004.
(Thompson et al., 1999) H. A. Thompson, A. J. Chip- perfield, P. J. Flemming, and C. Legge. Distributed aero-engine control systems architecture selection using multi-objective optimisation. Control Engi- neering Practice, 7(5):655–664, 1999.
(Trave-Massuyes et al., 2006) L. Trave-Massuyes, T. Escobet, and X. Olive. Diagnosability anal- ysis based on component-supported analytical redundancy relations. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, 36(6):1146–1160, 2006.
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