Predictive Maintenance System Using IOT and Machine Learning for VMC

Predictive Maintenance System Using IOT and Machine Learning for VMC

Rushikesh Patil 1, Yashashree Nirmale 2, Apeksha Salokhe3, Saniya Pathan4,Padmavati Pise 5

1Project Guide, Dept. of Electronics & Telecommunication, D.Y. Patil College of Engineering & Technology, Kolhapur, Maharashtra, India.
2,3,4,5 Students, Dept. of Electronics & Telecommunication, D.Y. Patil College of Engineering & Technology, Kolhapur, Maharashtra, India.

ABSTRACT
This paper presents a predictive maintenance system designed for Vertical Machining Centers (VMC) utilizing Internet of Things (IoT) technology and Machine Learning (ML) algorithms. The system continuously monitors critical machine parameters such as temperature, vibration, and spindle load using IoT-based sensors. The collected data is transmitted in real-time to a cloud-based platform for preprocessing, analysis, and anomaly detection. A trained ML model predicts potential failures, allowing for timely maintenance scheduling and minimizing unplanned downtime. The proposed system enhances machine availability, reduces maintenance costs, and improves operational efficiency in manufacturing environments. With its scalable architecture and real-time feedback loop, this solution is suitable for Industry 4.0-compliant smart factories.

Keywords — Predictive Maintenance, Vertical Machining Center, IoT Sensors, Machine Learning, Industry 4.0, Real-Time Monitoring.