Development of a risk assessment selection methodology for asset maintenance decision making: An analytic network process (ANP) approach

Abstract

Risk assessment performs a critical decision support role in maintenance decision making. This is through assisting maintenance practitioners systematically identify, analyze, evaluate and mitigate equipment failures. Often, such failures are mitigated through formulating effective maintenance strategies. In asset maintenance, well-known risk assessment techniques include the Failure Mode and Effect Analysis (FMEA), Fault Tree Analysis (FTA), and Bayesian Networks (BN). In recent years, considerable research attention has been directed towards improving existing techniques, often at the expense of a structured framework for selecting suitable risk assessment techniques. Often, several criteria influence the selection process. Moreover, the criteria are closely linked to specific organizational competencies that vary from one firm to another. In this study, a selection methodology for risk assessment techniques in the maintenance decision making domain is proposed. In the methodology, generic selection criteria for the FMEA, FTA and BN are derived based on the risk assessment process outlined in the ISO 31000:2009 standard. The criteria are prioritized using the Analytic Network Process (ANP), taking into account the judgment and opinion of academic and industrial domain experts. The results illustrate the usefulness of the proposed methodology towards assisting maintenance practitioners discern important competencies relevant to the specific technique and as such select the technique best suited for the organization.