Predictive Maintenance based on real-time monitoringof industrial assets

Abstract

Predictive maintenance has become an essential strategy in the industrial equipment management, revolutionizing classical maintenance methods. This article aims to discuss the integration of modern real-time monitoring technologies, including IoT, AI and machine learning, in the development of the predictive maintenance models. It examines the evolution of PdM from reactive to predictive models, highlighting the central role of these technologies in facilitating decision-making based in data. This discussion will address the practical implications of these advances, including significant cost reductions, increased equipment durability and optimized functional efficiency, leading to more accurate AI algorithms for autonomous systems and precise predictive analytics. This exploration shows the importance of real-time monitoring and advanced technologies in shaping the future of predictive maintenance, moving industries towards greater efficiency, minimized downtime and optimized asset management.