Digital image processing for counting chips in micro-end-milling

In conventional milling, the cutting mechanism is dominated by shearing due to the sharp cutting edge. However, it is no longer possible to assume that the cutting edge is sharp in micro-end-milling since the size of the cutting edge of a micro-end-mill becomes comparable to the feed per tooth. As a result, more than one chip formation mechanism occurs in micro-end-milling at the tool-workpiece interface: shearing, elasto-plastic deformation, and ploughing. In the shearing-dominant chip formation, one chip per tooth cut occurs. However, the chip formation mechanism changes into the elasto-plastic deformation or ploughing when the cutting edge of a tool becomes dull due to the tool wear generating no chip per tooth cut. Therefore, the number of chips produced during a cutting operation can be an important indicator of the state of the interaction between a tool and a workpiece. In this paper, the chips from a slot micro-end-milling operation with a 200 tool are counted through digital image processing using Locally Adaptive Threshold Method. In order to count the chips, a chip counting system is developed. The chips are collected and images of the chips are taken by a digital USB microscope. Image processing is applied to the images using Locally Adaptive Threshold Method. The number of chips counted by Locally Adaptive Threshold Method shows less than 10 % counting error.