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A new tool for prioritising the risk of failure modes for marine machinery systems

A new tool for prioritising the risk of failure modes for marine machinery systems
A new tool for prioritising the risk of failure modes for marine machinery systems

Failure Mode Effect and Analysis (FMEA) is one of the most powerful techniques for performing risk analysis for marine machinery systems, with risk being quantified through evaluating Risk Priority Numbers (RPNs) for all failure modes of the systems. The RPN is traditionally evaluated as the product of three risk criteria; occurrence (O), severity (S) and Detection (D). FMEA has several limitations such as the challenge of aggregating experts' risk criteria rating that may be imprecise or incomplete. In this paper some of the limitations in the conventional FMEA technique are addressed using two approaches; AVeraging technique integrated with conventional Risk Priority Number (AVRPN) and AVeraging technique integrated with TOPSIS (AVTOPSIS). Both proposed techniques use a novel approach simple average in aggregating imprecise experts' risk criteria ratings. A case study illustrates the suitability of both techniques for use in risk prioritisation jointly or independently as the results generated by both techniques are very similar. Furthermore, the AVRPN technique has been applied to an example from the literature and it has been demonstrated to be both computationally simple and capable of producing results which almost completely match those generated by modified Dempster-Shafer evidence theory techniques.

Failure mode, FMEA, Risk criteria, Risk Priority Number (RPN), TOPSIS
The American Society of Mechanical Engineers
Emovon, Ikuobase
e0a51526-6e06-4c29-ba98-6ea531cee694
Norman, Rosemary A.
6d2518aa-ece8-498f-82dc-dee5ec7b1b37
Murphy, Alan J.
8e021dad-0c60-446b-a14e-cddd09d44626
Emovon, Ikuobase
e0a51526-6e06-4c29-ba98-6ea531cee694
Norman, Rosemary A.
6d2518aa-ece8-498f-82dc-dee5ec7b1b37
Murphy, Alan J.
8e021dad-0c60-446b-a14e-cddd09d44626

Emovon, Ikuobase, Norman, Rosemary A. and Murphy, Alan J. (2014) A new tool for prioritising the risk of failure modes for marine machinery systems. In Structures, Safety and Reliability. vol. 4A, The American Society of Mechanical Engineers.. (doi:10.1115/OMAE2014-23267).

Record type: Conference or Workshop Item (Paper)

Abstract

Failure Mode Effect and Analysis (FMEA) is one of the most powerful techniques for performing risk analysis for marine machinery systems, with risk being quantified through evaluating Risk Priority Numbers (RPNs) for all failure modes of the systems. The RPN is traditionally evaluated as the product of three risk criteria; occurrence (O), severity (S) and Detection (D). FMEA has several limitations such as the challenge of aggregating experts' risk criteria rating that may be imprecise or incomplete. In this paper some of the limitations in the conventional FMEA technique are addressed using two approaches; AVeraging technique integrated with conventional Risk Priority Number (AVRPN) and AVeraging technique integrated with TOPSIS (AVTOPSIS). Both proposed techniques use a novel approach simple average in aggregating imprecise experts' risk criteria ratings. A case study illustrates the suitability of both techniques for use in risk prioritisation jointly or independently as the results generated by both techniques are very similar. Furthermore, the AVRPN technique has been applied to an example from the literature and it has been demonstrated to be both computationally simple and capable of producing results which almost completely match those generated by modified Dempster-Shafer evidence theory techniques.

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More information

Published date: 1 October 2014
Venue - Dates: ASME 2014 33rd International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2014, , San Francisco, United States, 2014-06-08 - 2014-06-13
Keywords: Failure mode, FMEA, Risk criteria, Risk Priority Number (RPN), TOPSIS

Identifiers

Local EPrints ID: 483747
URI: http://eprints.soton.ac.uk/id/eprint/483747
PURE UUID: 639d457d-9ead-468e-9e83-ec5929a72c43

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Date deposited: 03 Nov 2023 18:09
Last modified: 10 May 2024 17:03

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Contributors

Author: Ikuobase Emovon
Author: Rosemary A. Norman
Author: Alan J. Murphy

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