Intelligent Tools for Predictive Process Control

This paper first introduces comprehensive experimental studies regarding the relationship between tool wear progress and tool vibrations during milling. The investigations focus on long and slender ball nose milling cutters which are usually applied in die and mold manufacturing within semi-finishing and finishing process steps. An automated analysis setup was developed which allows recording the tool wear progress and milling behavior with a very high resolution. With respect to process simulations involving the tool wear state, a detailed database is provided by these experiments. Secondly, the paper presents a new approach for a sensor integrated long and slender ball nose milling tool which detects the process vibrations close to the cutting zone. By combination of the experimental data and the sensory tool, predictive process control strategies can be implemented in order to avoid critical wear and vibrations situations.