Use of failure data and criticality analysis in a maintenance management tool for electric power distribution company

Abstract

Electric power distribution companies are facing a challenging moment in time. Privatizations, scarce resources, low investments, and harsh penalties owing to inadequate quality force these companies to seek greater efficiency and control of their processes. Thus, decision-making based only on tacit knowledge and without a clear procedure, as was done by the maintenance company considered in this study, is not advisable. Accordingly, this work aimed to develop a support tool for maintenance decisions based on failure data and criticality analysis. The Failure Mode and Effect Analysis (FMEA) method was used to discover the riskiest failure modes, and the Multi-Attribute Utility Theory (MAUT) and Mudge method were used to rank the main criteria used by experts when deciding which transmission line (TL) is in a more critical condition. As a result, the study proposed a tool that guides decision-making in a systematic, impersonal, and collective knowledge-based manner for the specific situations encountered in TL maintenance. The results were approved and judged satisfactory by the members of a team of specialists from the maintenance area.