Multi-criteria Analysis of Maintenance Management Performance Indicators

Abstract

Multi-criteria decision analysis (MCDA) has been widely applied in the most diverse problems and areas of knowledge. Among these applications, we observe the growth in their use related to studies on performance indicators. Performance indicators should provide reliable data on the activities measured and their current position in relation to goals and policies previously established by organizations. Establishing a set of performance indicators for functional areas of organizations allows for better achievement of investments and resources. Among these areas, maintenance management has assumed an important role and has become fundamental for asset management. Measurement of maintenance performance is a complex process that involves several indicators with multiple criteria and different levels. Therefore, it can be formulated as a multi-criteria decision problem. In this context, performance indicators, maintenance management, and MCDA have grown interesting the last few years. However, few research combines these three themes, simultaneously. First, this chapter presents the evolution of publications on maintenance management, multi-criteria analysis, and performance indicators. Then,we identify performance indicators adopted by a real-world company. These performance indicators are aligned with the literature on industrial maintenance. We applied Analytic Hierarchy Process (AHP) to find the weights of each indicator for the maintenance management process, and we applied the Technique of Order Preference for Similarity to the Ideal Solution (TOPSIS) to choose the best productive units based on data collected from indicators in the real-world company.