An Integrated Approach to Predictive Maintenance Using Iot and Machine Learning in Manufacturing

Abstract

This article explores the integration of IoT and machine learning for predictive maintenance in manufacturing. 
The combined approach utilizes real-time data from IoT sensors to feed machine learning algorithms, allowing 
for proactive equipment maintenance. The benefits include increased reliability, minimized downtime, and 
improved overall equipment effectiveness. The article discusses key components, presents case studies, and 
addresses challenges in implementing this transformative strategy, emphasizing its potential to optimize 
manufacturing operations and enhance competitiveness.