AI-Enabled Predictive Maintenance for Industrial Equipment: Enhancing Reliability and Reducing Downtime
Keywords:
Artificial Intelligence, Predictive Maintenance, Industrial Equipment, Downtime Reduction, Machine Learning, Industry 4.0, Internet of Things (IoT)Abstract
The growing sophistication of industrial systems and the high price of unplanned equipment breakdowns has increased the importance of sophisticated maintenance plans. Conventional methods, including reactive and preventive maintenance, tend to be ineffective, which results in excessive downtimes, wastage of resources and safety issues. Predictive maintenance is a transformative solution to artificial intelligence (AI) as it applies machine learning algorithms, sensor data, and real-time analytics to predict equipment failures before they happen. Predictive maintenance systems can be optimized, increase the asset lifespan, and decrease operational costs considerably thanks to the integration with the Industrial Internet of Things (IIoT), big data platforms, or digital twins. The paper will discuss the use of AI in predictive maintenance with its technological basis, industry use, advantages, and limitations and its future opportunities. The research underlines predictive maintenance as one of the foundations of Industry 4.0 and sustainable industrial development by showing how AI-based knowledge promotes better reliability and reduces downtimes.
