SENSOR-BASED MONITORING FOR TOOL CONDITION AND MACHINING QUALITY

Sensor-based monitoring systems have emerged as a critical solution for real-time assessment of tool condition and machining quality in modern manufacturing. The integration of advanced sensor technologies, data acquisition systems, and machine learning techniques enables early detection of tool wear, breakage, and process anomalies, leading to improved productivity and cost efficiency. This study examines various sensor technologies, including acoustic emission, force, vibration, thermal, and optical sensors, and their role in monitoring machining processes. Additionally, data processing techniques, predictive analytics, and real-time decision-making frameworks are explored to enhance tool life and maintain machining precision. By implementing sensor-based monitoring, manufacturers can achieve higher reliability, reduced downtime, and superior machining performance, aligning with Industry 4.0 advancements.