The integration of Artificial Intelligence (AI) and the Internet of Things (IoT) is fundamentally transforming maintenance practices in manufacturing, shifting the paradigm from reactive and preventive approaches to predictive maintenance (PdM) (Deloitte, 2017). PdM utilizes real-time data collected from IoT-enabled devices to predict potential equipment failures before they occur, allowing for timely interventions that minimize unplanned downtime and optimize maintenance schedules (Upkeep, 2023). Research by Deloitte highlights that predictive maintenance can reduce maintenance costs by up to 40%, improve equipment reliability by 30–50%, and decrease equipment downtime by 50% (2017). Additionally, IoT sensors monitor key metrics such as vibration, temperature, pressure, and operational speed, generating valuable datasets for AI algorithms to analyze. These algorithms, often leveraging machine learning, identify failure patterns and forecast future equipment performance, enabling manufacturers to make informed, proactive decisions (Upkeep, 2023).