Development of a Risk Ranking System for Prioritizing Asset Maintenance Decisions

Abstract

This thesis presents a modified approach to prioritize asset maintenance decisions by evaluating the overall risk rating of engineering systems. Traditional methods rely on subjective assessments by experts, which potentially lead to greater subjectivity and inconsistency in risk prioritization, thus requiring improvements. The thesis performs a comparative analysis of existing risk prioritization techniques to understand the challenges in ranking systems.

Analytical Hierarchical process (AHP) and fuzzy logic are proposed to develop a risk ranking system. AHP is employed to compute the weights of multiple criteria, providing a structured framework for decision-making and enabling systematic prioritization of system components. The Mamdani Fuzzy Inference System is integrated to manage the inherent uncertainty and imprecision in assigning ranks.

The proposed AHP-Fuzzy model is applied to a plant aging management problem in the nuclear industry with various maintenance tasks, demonstrating its effectiveness in decision-making. The risk rating distribution and sensitivity analyses are studied. The results indicate that integrating AHP and Fuzzy Logic improves decision-making by effective risk prioritization.

The thesis contributes to the field of engineering management by providing practical, actionable strategies for enhancing risk management practices to ensure the safety of engineering systems.