Abstract
This paper proposes a conceptual framework that conciliates tacit and explicit information from the maintenance function, generating a new knowledge base used in analyzing and improving decisions in deploying a customized RCM (Reliability Centered Maintenance) model. The transformation of raw information into formal knowledge must generate personalized records in a single database, being available for the RCM deployment phases. By identifying trends and applying Process Mining techniques, hidden patterns and relationships can be uncovered. MCDM/A (Multi Criteria Decision Making/Analysis) methods support the decisions in the stages of RCM implementations. Improving maintenance strategies is an important approach in increasing system reliability and reducing costs.
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