Plant Prioritization for Updating Maintenance Policies: A Power Sector Case Study

In order to reduce unnecessary maintenance services and return valuable time to industrial plants, several companies have been engaging in updating their maintenance schedules and strategies. Several techniques to achieve such a goal have been developed, for example, Reliability Centered Maintenance (RCM), Risk-based Maintenance (RBM) and Condition-based Maintenance (CBM). The complex process of implementing such techniques can, however, offer several challenges to companies, such as how to properly train maintenance teams; what are the best tools or software to use on a daily basis; which performance indicators to use for decision making; etc. After the implementation process, one of the first difficulties faced especially by large companies, composed of several plants, is where to start the RCM effectiveness evaluation aiming at identifying the possible needs for improvement to optimize maintenance strategies. In general, one of the plants in the company's asset portfolio should be chosen to be the first to receive the methodology improvement. In this way, the implementation process can be put to the test so that its successes and failures are properly recorded, allowing the lessons learned to be used to improve the implementation in the other plants of the company. The choice of the pilot plant must be made carefully, in order to highlight the advantages of the new maintenance strategy while allowing the implementation process to be optimized. In this context, this work proposes a method for choosing the pilot plant through the Analytic Hierarchy Process (AHP), which is a multi-criteria decision method widely used for ranking the alternatives of a decision problem. The proposed method will be implemented in a company in the Brazilian energy sector whose portfolio of assets is composed of several hydroelectric plants. The company already uses the RCM for the elaboration of the maintenance plans but intends to improve the methodology based on quantitative reliability analysis aiming at optimizing maintenance intervention intervals. The method will be used to evaluate RCM implementation maturity in each asset in order to define the most suitable plant to be used in the improvement process.