Title: A dynamic failure mode and effect analysis using Bayesian theory
Authors: Chemweno, Peter Kipruto ×
Pintelon, Liliane
Van Horenbeek, Adriaan
Muchiri, Peter
Wakiru, James #
Issue Date: 10-Jul-2014
Publisher: Institute of mathematics and its applications
Host Document: 8th IMA International Conference on Modelling in Industrial Maintenance and Reliability vol:1 issue:1 edition:8th pages:43-44
Conference: International Conference on Modelling in Industrial Maintenance and Reliability edition:8th location:St. Catherine's College, University of Oxford date:10-12 July 2014
Abstract: In recent years, the strategic role of risk assessment with respect to asset maintenance has drawn considerable research interest. Indeed, risk assessment presents a focused maintenance approach allowing prioritization of failure modes thus enabling the efficient deployment of otherwise scarce resources. One of the most popular risk assessment tools is the failure mode and effect analysis (FMEA). However, the FMEA is associated with several flaws, largely related to computation of the risk priority number (RPN), a key risk prioritization metric. Moreover, the FMEA is considered a static tool, in the sense that it seldom provides a means of updating risk factors based on new failure information. To overcome this, a dynamic FMEA methodology is proposed. The methodology uses the Bayes theory to pro-actively update the posterior failure density functions, while the impact on the detectability RPN metric of implementing condition monitoring is evaluated through a sensitivity analysis.
Description: no isbn
Publication status: published
KU Leuven publication type: IC
Appears in Collections:Centre for Industrial Management / Traffic & Infrastructure
× corresponding author
# (joint) last author

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