Cutting forces modeling for micro flat end milling by considering tool run-out and bottom edge cutting effect

Abstract

In this article, a cutting forces model for micro flat end milling is developed by regarding tool run-out or eccentric and tilt deviation of tool path as well as the effect of bottom edge cutting. Since the chip thickness is comparable to the edge radius, the size effect, which means the chip is only removed when it is higher than a certain value, is also taken into account. Therefore, cutting forces of the proposed model are calculated by flank shearing, flank ploughing and bottom edge cutting mechanisms in the shearing-domain and ploughing-domain regimes. The coefficients of cutting forces and tool run-out parameters can be calibrated by the experimental cutting forces. The predicted cutting forces with different feed rates and axial depths of cut based on the proposed model have been investigated and compared with experimental results for Al6061. The predicted and measured cutting forces are in good agreement.

An experimental analysis of minimum chip thickness in micro-milling of two different titanium alloys

“…h/R e < 1), the SCF shows a nonlinear increase, due to plowing. 5 The SCF is obtained by dividing the average cutting force by the chip section. In this study, SCF was calculated by considering the resultant force of Fx and Fy.…”

“…In order to determine the minimum chip thickness, the surface roughness and force change are generally considered. 4,5 In areas where plowing occurs, the quality of the machined surface also deteriorates. This usually occurs at locations where the cutting edge starts cutting and finishes cutting.…”

A methodology for precision manufacture of a nozzle using hybrid laser powder-bed fusion: A case study

“…Hybrid powder-bed additive manufacturing (AM) is a relatively new technology that combines research challenges from two manufacturing processes, laser powder-bed fusion (L-PBF) and micro-milling. The micro-milling process has been researched where the physics and the associated challenges have been addressed in the past, including cutting forces [1,2], tool dynamics and chatter [3,4], tool wear [5,6], thermal loads [7,8] and associated effects of the process parameters on different materials [9]. There is also significant research conducted in L-PBF in the development of process parameters for different materials [10,11], understanding porosity and defects [12], residual stresses and mitigation of distortion [13,14], design optimisation techniques [15], powder behaviour and metallurgical aspects [16,17].…”

Data‐driven framework for the prediction of cutting force in turning

“…Tool wear modelling is very important for replacing the tool before it breaks or produces an inferior quality product. A number of analytical and numerical methods have been developed to predict the surface roughness and cutting forces as a function of process parameters [4, 5]. Attempts have also been made to predict tool wear during machining based on online signals from sensors [6, 7].…”