Smart Maintenance: Implementing IoT-Enabled Predictive Maintenance in Automated Production Lines

Abstract

The emergence of Industry 4.0 has revolutionized the manufacturing sector by introducing advanced technologies such as the Internet of Things (IoT), which enables real-time data collection and intelligent decision-making. One of the most impactful applications of IoT in smart manufacturing is predictive maintenance, where sensor data is used to monitor the health of equipment, predict failures, and schedule maintenance proactively. This paper explores the integration of IoT in predictive maintenance strategies across automated production lines. It presents a comprehensive review of system architecture, sensor technologies, analytics methods, implementation frameworks, and industrial use cases. The goal is to reduce unplanned downtimes, increase equipment lifespan, and improve overall operational efficiency.

Keywords: IoT, Predictive Maintenance, Automated Production, Industry 4.0, Smart Manufacturing, Sensors, Downtime Reduction, Machine Learning, Data Analytics