Open-Source Framework for Automated Milling Experiments: G-Code Adaptation and NC Data Acquisition with Siemens Industrial Edge

Abstract

In modern manufacturing, precise monitoring and control of milling processes are critical for ensuring process stability and efficiency. This paper introduces an open-source framework leveraging Siemens Industrial Edge technology to automate complex milling experiments while simultaneously acquiring NC signal data. A Python-based application enables dynamic G-code adaptation, facilitating autonomous stability investigations and beyond. Stability lobe diagrams are generated as an exemplary case study, demonstrating the feasibility of automated experiments. The open-source availability of G-code and Python scripts empowers users to adapt the solution, laying the foundation for deploying AI models on machine controls and support scalable smart manufacturing solutions