| dc.description.abstract | The demand to maintain machine performance at acceptable failure rates and low down time is due to the increasing interest and initiatives of the sector, where failure diagnosis and management are important parts of monitoring machine integrity, an indispensable function for industries of the future. The responsible use of strategies that help decision-making in the management and treatment of failures is essential to keep the equipment safe and reliable, without the risk of workplace accidents. In this respect, decision-making for failure management needs to include evidence as part of the information available to decision makers. Thus, the aim of the present study was to propose a method to help in the decision-making of failure management. To that end, Design Science Research was used to conduct the study, whose main finding supports the Evidence-Based Method for Managing Failures (EBMMF) and the Computational Prototype. The method is developed from a combination of resources obtained from a systematic literature review, stages of the approach based on evidence and requirements identified using analysis of existing methods. Its constructive process occurred by means of the improvement cycles conducted, whose criterion is the use of evidence-based management. It was validated using interviews with specialists from multidisciplinary areas. The interviews made it possible to identify the main opportunities for improvement and demonstrate the relevance of this proposal. Finally, the proposed method was refined and the computational prototype implementation process initiated. The aim of the prototype was to support failure management decision making, enabling evidence integration, enhanced performance, better productivity and efficiency, and, most importantly, process safety. | en |
