Infrared Vision and Current Sensor for CNC Milling Using Internet of Things (IoT)

Abstract

This thesis delves into the synergistic intergration of infrared vision and current sensing technologies within CNC machine, leveraging the Internet of Things (IoT) for advanced monitoring and control capabilities. The primary objective is to address the critical need for heightened precision and efficiency in CNC milling processes. The research concentrates on two pivotal aspects: real-time temperature monitoring through infrared vision and continuous tool monitoring via current sensors. Employing a mixed-methods approach, the study conducts comprehensive experimental evaluations and quantitative analyses to gauge the efficacy of the IoT-based system in a practical CNC milling environment. The findings not only demonstrate the system’s potential in providing immediate insights into temperature variations and tool conditions but also highlight its broader impact on improving machining quality and operational efficiency while minimizing downtime. As a noteworthy contribution to the realm of smart manufracturing, this research lays the groundwork for future advancements in the design and implementation of IoT-given monitoring and control systems tailored for precision machining applications, thereby paving the ways for more efficient and reliable manufacturing pratices.