Online Monitoring System for Tool Wear and Fault Prediction Using Artificial Intelligence


With the advancement of technology and rise in the concept of intelligent machining, it is important to monitor the process in the real-time. Cutting Tool is one of the key element in the machining process. Cutting Tool wear is known to influence device life, surface quality and creation time. Due to this, an online device wears estimation and observing framework has been developed. This paper presents a robust method for the tool wear prediction using Artificial Intelligence. MATLAB programming is utilized as the stage programming to build up an easy to understand graphical UI (GUI) for real-time monitoring. The proposed methodology had a forecast accuracy of 95.7%, which might be considered as substantial and valid for Tool wear Monitoring.



Software And Hardware

• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL