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In this paper, simulation of cutting edge wear rate model based on the chip production rate in micro-endmilling is conducted in order to understand the state of the interaction between the tool and the workpiece. In micro-endmilling, the chip production rate changes due to the cutting edge wear and it can be explained by the minimum chip thickness effect. If the cutting edge radius increases due to the tool wear until the minimum chip thickness becomes larger than the uncut chip thickness, the chips will not be generated with the cutting tooth sliding on the workpiece. If the new tool with the sharp cutting edge is used, the chips will be generated without the cutting tooth sliding on the workpiece. From this point of view, the cutting edge wear could be observed by measuring the chip production rate in micro-endmilling. Therefore, the cutting edge wear rate model is proposed and the simulation of the cutting edge wear rate estimation is conducted. Our proposed cutting edge wear rate model could be used in improving the tool life and the surface quality by estimating the cutting edge wear rate.

In this paper, the reliability of a new online cutting edge radius estimator for micro end milling is evaluated. This estimator predicts the cutting edge radius by detecting the drop in the chip production rate as the cutting edge of a micro end mill slips over the workpiece when the minimum chip thickness (MCT) becomes larger than the uncut chip thickness (UCT), thus transitioning from the shearing to the ploughing dominant regime. This study proposes a method of calibrating the cutting edge radius estimator by determining two parameters from training data: a ‘size filtering threshold’ that specifies the smallest-size chip that should be counted, and a ‘drop detection threshold’ that distinguishes the drop in the number of chips at the actual critical feedrate from the number drops at the other feedrates. This study then evaluates the accuracy of the calibrated estimator from testing data for determining the ‘critical feedrate’—the feedrate at which the MCT and UCT will be equal. It is found that the estimator is successful in determining the critical feedrate to within 1 mm/s in 84% of trials.

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