Mechanistic identification of cutting force coefficients in bull-nose milling process

An improved method to determine cutting force coefficients for bull-nose cutters is proposed based on the semi-mechanistic cutting force model. Due to variations of cutting speed along the tool axis in bull-nose milling, they affect coefficients significantly and may bring remarkable discrepancies in the prediction of cutting forces. Firstly, the bull-nose cutter is regarded as a finite number of axial discs piled up along the tool axis, and the rigid cutting force model is exerted. Then through discretization along cutting edges, the cutting force related to each element is recalculated, which equals to differential force value between the current and previous elements. In addition, coefficient identification adopts the cubic polynomial fitting method with the slice elevation as its horizontal axis. By calculating relations of cutting speed and cutting depth, the influences of speed variations on cutting force can be derived. Thereby, several tests are conducted to calibrate the coefficients using the improved method, which are applied to later force predictions. Eventually, experimental evaluations are discussed to verify the effectiveness. Compared to the conventional method, the results are more accurate and show satisfactory consistency with the simulations. For further applications, the method is instructive to predict the cutting forces in bull-nose milling with lead or tilt angles and can be extended to the selection of cutting parameters.

Indirect approach for predicting cutting force coefficients and power consumption in milling process

Accurate energy consumption modeling is an essential prerequisite for sustainable manufacturing.Recently,cutting-power-based models have garnered significant attention,as they can provide more comprehensive information regarding the machining energy consumption pattern.However,their implementation is challenging because new cutting force coefficients are typically required to address new workpiece materials.Traditionally,cutting force coefficients are calculated at a high operation cost as a dynamometer must be used.Hence,a novel indirect approach for estimating the cutting force coefficients of a new tool-workpiece pair is proposed herein.The key idea is to convert the cutting force coefficient calculation problem into an optimization problem,whose solution can be effectively obtained using the proposed simulated annealing algorithm.Subsequently,the cutting force coefficients for a new tool-workpiece pair can be estimated from a pre-calibrated energy consumption model.Machining experiments performed using different machine tools clearly demonstrate the effectiveness of the developed approach.Comparative studies with measured cutting force coefficients reveal the decent accuracy of the approach in terms of both energy consumption prediction and instantaneous cutting force prediction.The proposed approach can provide an accurate and reliable estimation of cutting force coefficients for new workpiece materials while avoiding operational or economic problems encountered in traditional force monitoring methods involving dynamometers.Therefore,this study may significantly advance the development of sustainable manufacturing.

A cortical bone milling force model based on orthogonal cutting distribution method

In orthopedic surgery,the bone milling force has attracted attention owing to its significant influence on bone cracks and the breaking of tools.It is necessary to build a milling force model to improve the process of bone milling.This paper proposes a cortical bone milling force model based on the orthogonal cutting distribution method(OCDM),explaining the effect of anisotropic bone materials on milling force.According to the model,the bone milling force could be represented by the equivalent effect of a transient cutting force in a rotating period,and the transient milling force could be calculated by the transient milling force coefficients,cutting thickness,and cutting width.Based on the OCDM,the change in transient cutting force coefficients during slotting can be described by using a quadratic polynomial.Subsequently,the force model is updated for robotic bone milling,considering the low stiffness of the robot arm.Next,an experimental platform for robotic bone milling is built to simulate the milling process in clinical operation,and the machining signal is employed to calculate the milling force.Finally,according to the experimental result,the rationality of the force model is verified by the contrast between the measured and predicted forces.The milling force model can satisfy the accuracy requirement for predicting the milling force in the different processing directions,and it could promote the development of force control in orthopedic surgery.