Tool Condition Monitoring for Ball Nose Milling - A Model Based Approach

Abstract

Tool condition monitoring for ball nose milling poses a new challenges compared to conventional machining processes, due to the complexity of the tool shape, variation of tool- workpiece contact point and cutting conditions. In this thesis, model based tool wear profile estimation for ball nose milling was proposed. A geometric model and estimated cutting force for fresh cutting tool were used in tool wear profile estimation. The geometric model was developed and pertinent features were extracted, such as chip load distribution about the rotation axis, chip load along the cutting edge, and frictions length. Such geometric features were related to the performance of the cutter in relation to the cutter path directions and workpiece inclination on tool life. Using the geometric feature of the chip load about the rotation axis, the cutting force was estimated. For cutting force estimation, a mechanistic model was used and a method for the identification of appropriate cutting coefficients was proposed. With the identified cutting coefficients, the cutting force was estimated for various inclined plane workpieces and hemispherical surface workpiece. From the estimated cutting force, the residual force feature was extracted. Finally, various tool wear profile estimation models were established using the geometric features and residual force feature. Established tool wear profile estimation models were verified with experiments.