Utilization of FMECA to Optimize Predictive Maintenance

This paper explores the optimization of predictive maintenance in the aeronautical industry through the integration of Failure Mode, Effect, and Criticality Analysis (FMECA) with advanced technologies. It highlights the crucial importance of FMECA equipment in implementing predictive maintenance and shows how this approach can be used to identify and prioritize failures. By targeting high-risk failures, this innovative approach reinforces the predictive maintenance strategy by associating specific sensors. Integrating the Industrial Internet of Things (IIoT) and Artificial Intelligence (AI) is pivotal, enabling real-time equipment monitoring and data-driven decision-making. Moreover, the adoption of predictive maintenance from the manufacturing phase is emphasized as critical for manufacturers in a competitive environment, offering strategic advantages such as increased product reliability, reduced in-service failures, and lower maintenance costs. This not only enhances customer satisfaction and market reputation but also underscores a commitment to technological innovation and meeting market needs. Overall, this paper highlights an innovative approach to optimizing predictive maintenance in the aeronautical sector, aiming to reduce costs and improve safety through the strategic use of FMECA, IIoT, and AI. This synergy minimizes unplanned downtime, thereby enhancing operational efficiency and competitiveness in the aeronautical industry.