Sistema de manutenção preditiva para eixos mecânicos em ambientes industriais

Abstract

This work presents a methodology for calculating the lifecycle of mechanical shafts using the SN (Stress-Number) diagram, with a focus on implementing effective predictive maintenance. Traditionally, industrial maintenance was reactive, addressing failures only after their occurrence, which resulted in high costs and unexpected downtimes. Predictive maintenance, however, allows for the prediction of fatigue failures based on statistical analyses and past performance, facilitating timely interventions and extending the lifespan of components. The developed methodology involves the collection of geometric and material data of the shafts, application of loads, and performing stress and strength calculations. Using the SN diagram, the system predicts the durability of the shafts and stores this information in a continuously updated database. This database allows for accurate and predictive analysis of the components' condition, aiding in the identification of critical points and in planning maintenance interventions before catastrophic fatigue failures occur. The developed system not only contributes to the reduction of operational costs but also improves the efficiency and safety of industrial operations. By implementing a robust solution for the predictive maintenance of mechanical shafts, this work establishes a solid foundation for future research and advancements in the field of industrial maintenance.