AI for Predictive Maintenance in Manufacturing

Artificial intelligence transforms manufacturing by using sensor data for early fault prediction and condition monitoring, reducing downtime and boosting efficiency. This work merges theoretical insights with practical methods in anomaly detection, model training, and real-time decision-making to optimize maintenance processes. Artificial intelligence is reshaping the manufacturing sector by enabling predictive maintenance—anticipating equipment failures before they occur. Through data-driven insights, industries can minimize downtime and enhance operational efficiency. AI for Predictive Maintenance in Manufacturing explores the intersection of AI, machine learning, and industrial analytics for maintenance optimization. It covers techniques such as anomaly detection, condition monitoring, and fault prediction using sensor data. The book also discusses data preprocessing, model training, and real-time decision-making systems. By integrating theoretical foundations with practical implementations, it provides engineers and researchers with the tools to build intelligent and reliable manufacturing systems.