In the recent decades, world economy experienced financial crises which effected industrial companies suffer in managing expenses of maintenance and replacement parts which may result in a production stoppage, damage to other system elements, or even safety issues. Out Tem in Predictive Management System (PMS) had decided to find a way to reduce the frequent replacement of the part by utilizing combination of Internet Of Things (IOT) and Artificial Neural Network (ANN) and eventually innovated 3D monitoring model of machines and equipment. Value proposition 1. Preventing break downs in a plant by warning the maintenance staff just before a system element fails in real-time and 24/7 2. Removing unnecessary part replacements due to timely prediction and as a result, reducing maintenance costs 3. Self-boosting of the Digital Twin accuracy over time using a combination of IoT and Deep Learning 4. The capability of data sharing between plants and supporting and improving each other's machine learning models 5. Remote condition monitoring of the system on a mobile device 6. Audit trail capability of tracking past faults and finding the root cause of issues and errors 7. We use vibration monitoring in conjunction with IoT.so it is not limited to simple rotating equipment. So the microprocessor-based systems used for vibration analysis can be used effectively on all sophisticated electromechanical equipment 8. When used with IoT and ML, vibration monitoring and analysis is the most potent predictive maintenance tool available 9. A superior predictive method to reduce the complexity by eliminating the collinearity problem reducing the predictor variables for the built model.