PYTHON BASED SMART FACTORY MONITORING DASHBOARD FOR PREDICTIVE MAINTENANCE

Author: Ms. S. Narmatha and Ms.S.Lithika

Published On: 2026-08-17

This paper presents a Python-Based Smart Factory Monitoring Dashboard for predictive maintenance. The proposed system monitors three important machine parameters: temperature, conveyor material flow, and machine vibration.. Newton's Law of Cooling and exponential decay models were used to derive analytical solutions. Python is used to generate and process simulated machine data, compare operating conditions with predefined threshold values, generate alerts, display machine status, and provide basic future-risk predictions and maintenance recommendations. NumPy is used for numerical calculations, Pandas for data organization, and Matplotlib for graphical visualization. The dashboard identifies overheating, low material flow, and bearing failure risk, while also simulating email alerts.

Key Words: Python, Smart Factory, Predictive Maintenance, Machine Monitoring, Industry 4.0, IoT, Data Analytics