Abstract
Electric power distribution companies are facing a delicate moment. Privatizations, scarce resources, few investments and harsh penalties due to lack of quality force these companies to seek greater efficiency and control of their processes. Thus, making decisions based only on tacit knowledge and without a clear procedure, like the maintenance company that was part of this study, is not advisable. For this reason, this work aimed to develop a support tool for maintenance decisions, based on failure data and criticality analysis. The FMEA (Failure Mode and Effect Analysis) method was used to discover the riskiest failure modes, and the MAUT (Multi-Attribute Utility Theory) and the 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 systematized, 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 sector.
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