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ANP/RPN: a multi criteria evaluation of the Risk Priority Number

ANP/RPN: a multi criteria evaluation of the Risk Priority Number This paper presents an advanced version of the failure mode effects and criticality analysis (FMECA), whose capabilities are enhanced; in that the criticality assessment takes into account possible interactions among the principal causes of failure. This is obtained by integrating FMECA and Analytic Network Process, a multi‐criteria decision making technique. Severity, Occurrence and Detectability are split into sub‐criteria and arranged in a hybrid (hierarchy/network) decision‐structure that, at the lowest level, contains the causes of failure. Starting from this decision‐structure, the Risk Priority Number is computed making pairwise comparisons, so that qualitative judgements and reliable quantitative data can be easily included in the analysis, without using vague and unreliable linguistic conversion tables. Pairwise comparison also facilitates the effort of the design/maintenance team, since it is easier to place comparative rather than absolute judgments, to quantify the importance of the causes of failure. In order to clarify and to make evident the rational of the final results, a graphical tool, similar to the House of Quality, is also presented. At the end of the paper, a case study, which confirms the quality of the approach and shows its capability to perform robust and comprehensive criticality analyses, is reported. Copyright © 2011 John Wiley and Sons Ltd. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality and Reliability Engineering International Wiley

ANP/RPN: a multi criteria evaluation of the Risk Priority Number

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References (39)

Publisher
Wiley
Copyright
Copyright © 2012 John Wiley & Sons, Ltd.
ISSN
0748-8017
eISSN
1099-1638
DOI
10.1002/qre.1217
Publisher site
See Article on Publisher Site

Abstract

This paper presents an advanced version of the failure mode effects and criticality analysis (FMECA), whose capabilities are enhanced; in that the criticality assessment takes into account possible interactions among the principal causes of failure. This is obtained by integrating FMECA and Analytic Network Process, a multi‐criteria decision making technique. Severity, Occurrence and Detectability are split into sub‐criteria and arranged in a hybrid (hierarchy/network) decision‐structure that, at the lowest level, contains the causes of failure. Starting from this decision‐structure, the Risk Priority Number is computed making pairwise comparisons, so that qualitative judgements and reliable quantitative data can be easily included in the analysis, without using vague and unreliable linguistic conversion tables. Pairwise comparison also facilitates the effort of the design/maintenance team, since it is easier to place comparative rather than absolute judgments, to quantify the importance of the causes of failure. In order to clarify and to make evident the rational of the final results, a graphical tool, similar to the House of Quality, is also presented. At the end of the paper, a case study, which confirms the quality of the approach and shows its capability to perform robust and comprehensive criticality analyses, is reported. Copyright © 2011 John Wiley and Sons Ltd.

Journal

Quality and Reliability Engineering InternationalWiley

Published: Feb 1, 2012

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