Micro-milling tool wear monitoring under variable cutting parameters and runout using fast cutting force coefficient identification method

Prediction of Nonlinear Micro-Milling Force with a Novel Minimum Uncut Chip Thickness Model

“…The equivalent cutting form in a previous study [15] is adopted to model the uncut chip thickness under tool runout. The UCT of the k − th equivalent radius at the cutting depth z could be written as:…”

“…At the beginning of the 21st century, Bao and Tansel [10] first investigated the micromilling force model. Over the past decade, different factors such as the tool runout [11], minimum uncut chip thickness (MUCT) [12], dead metal zone [13], chip thickness accumulation [14], tool wear [15] and elastic recovery [16] were included in the micro-milling force model, making the micro-milling force model more and more accurate. The MUCT, one of the most representative characteristics of the micro-cutting process, dividing the cutting zone into the shear and ploughing regions, has a significant effect on the cutting force of micro-milling.…”

An Improved Cutting Force Model in Micro-milling Considering the Comprehensive Effect of Tool Runout, Size Effect and Tool Wear

“…Because the axial cutting depth is much smaller than the length of tool, the radial tool runout could be regarded as the translation of the cutting part at the bottom of the micro-milling tool, and thus the tool runout could be represented by the length o r and the angle o  of the translation vector. According to studies [13,24], the IUCT of the kt h  equivalent radius at cutting depth at reference position angle could be written as: oo r  could refer to study [24].…”

“…Li et al [23] adopted the spatial analytic geometry method to analysis the combined effect of the tool runout and wear the micro-milling force. Liu et al [24] built a micro-milling force model including the tool runout and tool wear, and proposed a cutting force model-based tool wear monitoring method under varying tool runout. However, so far, to our best knowledge, no studies have considered the comprehensive effect of tool runout, cutting-edge radius and tool wear on the micro milling force.…”

Identification of eccentricity for disc milling cutter of indexable two sided inserts

“…Liu et al 22 use multi-objective optimization and make that the residual error of each harmonic of milling force frequency domain signal is minimized, and the optimal solution of milling force coefficient and eccentricity parameter is obtained by iteration. Liu et al 23 obtained the resultant force waveform of micro milling by fast Fourier transform, took the combination of resultant force waveform and cutting parameters as input, took the runout as objective, and identified the tool runout parameters by neural network method. Zhang et al 24 measured the eccentric displacement of the cutting tool and the actual radius difference of each cutting tooth by the laser displacement sensor, and then took the square sum of the difference between the actual radius difference and the theoretical radius difference for each cutting tooth as the objective to carry out iterative calculation to obtain the eccentric angle.…”