This paper presents a method of measuring the volumetric tool wear by use of the image processing technique. A single CCD camera based stereo vision system is built to acquire the image pair. The crater wear’s boundary of the cutting tool is then detected, and then the 3D volumetric shape of the worn region on the rake face is reconstructed through the developed image matching algorithms, and the crater’s volume and depth is estimated. A Matlab software system is developed to perform image acquisition, calibration, image rectification, image adjustment, stereo matching, crater’s depth estimation, and the representation of the volumetric tool wear. The feasibility of the proposed method is verified through experiments.

This paper presents a method of estimating cutting forces of the tool by taking the tool’s run out into account during micro milling processes. The thickness of uncut chip is modelled based on the trochoidal trajectory synthesized from the rotational motion, the feed motion, and the run out of rotational micro tools. The strain gradient plasticity theory is then used in conjunction with the Johnson–Cook constitutive equation to calculate flow stresses, where the influence of the plough shear on the rake face and the elastic recovery on the flank face is considered. The calculated cutting forces using the proposed method for micro milling processes show a satisfactory agreement with existing experimental results.