Abstract
Predictive maintenance (PdM) is an emerging field that uses Artificial Intelligence (AI) to predict equipment failures before they occur, enabling industries to minimize downtime and optimize maintenance costs. AI-based predictive maintenance systems leverage data from sensors, historical performance, and machine learning algorithms to detect patterns, predict failures, and suggest corrective actions. This paper explores the role of AI in predictive maintenance, discussing various AI techniques, the benefits of implementing PdM systems, challenges faced during adoption, and real-world applications across industries. The paper concludes with insights into future developments in AI-driven predictive maintenance and the potential for broader industry adoption.
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