Cutting forces in micro-end-milling processes

Zhang, Xuewei; Ehmann, Kornel F.; Yu, Tianbiao; Wang, Wanshan

doi:10.1016/j.ijmachtools.2016.04.012

Cited by 152 publications

(55 citation statements)

References 23 publications

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“…In micromachining, the interaction between the cutting edge geometry and the work material significantly affects the outcome of the process [4]. Mechanistic modeling approach is commonly used in modeling the micromachining process [5][6][7][8][9]. Mechanistic modeling requires some experimental work to be performed in order to map the combined influences of work material, friction conditions, tool material, and geometry to some cutting coefficients.…”

Section: Introductionmentioning

confidence: 99%

Investigating the influence of friction conditions on finite element simulation of microscale machining with the presence of built-up edge

Oliaei

2016

Int J Adv Manuf Technol

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In micromachining, the uncut chip thickness is less than the cutting tool edge radius, which results in a large negative effective rake angle. Depending on the material properties, this large negative rake angle promotes built-up edge (BUE) formation. A stable BUE acts like a cutting edge and affects the mechanics of the process. The size of the BUE increases with increasing uncut chip thickness and cutting speed. It also creates a positive rake angle, but it decreases the clearance angle of the tool. A method of including BUE formation in finite element simulations is to use sticking friction conditions at the tip of the tool. However, this approach is shown to be insufficient to simulate BUE formation in microscale machining. Therefore, the cutting edge is modified with the experimental BUE size in the finite element simulations based on experimental measurements. The influence of friction models between BUE and the work material has been investigated, and the study identifies friction coefficients that yield good agreements with experimental results. The finite element model is shown to be capable of simulating process forces and chip shapes for uncut chip thickness values larger than minimum uncut chip thickness.

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Section: Introductionmentioning

confidence: 99%

Investigating the influence of friction conditions on finite element simulation of microscale machining with the presence of built-up edge

Oliaei

2016

Int J Adv Manuf Technol

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“…Tool run-out is directly related to the microtool, the tool holder, and the high-speed spindle. The tool run-out model of Zhang et al [6] has been adopted in this study. The uncut chip thickness is also a function of the immersion angle and helix angle of the tool acting on a differential height element (dz) on the tool body.…”

Section: Micromilling Mechanistic Force Modelingmentioning

confidence: 99%

“…Force modeling based on process input parameters is usually considered as the first step in process modeling. Mechanistic process modeling is usually preferred to model process forces in micromilling where the relationship between the work material and the cutting edge is obtained through cutting, edge, and ploughing force coefficients [5][6][7]. These coefficients are often calculated from either experimental measurements of process forces or finite element-based simulation models [8].…”

Section: Introductionmentioning

confidence: 99%

Uncertainty analysis of force coefficients during micromilling of titanium alloy

Gözü

2017

Int J Adv Manuf Technol

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Predicting process forces in micromilling is difficult due to complex interaction between the cutting edge and the work material, size effect, and process dynamics. This study describes the application of Bayesian inference to identify force coefficients in the micromilling process. The Metropolis-Hastings (MH) algorithm Markov chain Monte Carlo (MCMC) approach has been used to identify probability distributions of cutting, edge, and ploughing force coefficients based on experimental measurements and a mechanistic model of micromilling. The Bayesian inference scheme allows for predicting the upper and lower limits of micromilling forces, providing useful information about stability boundary calculations and robust process optimization. In the first part of the paper, micromilling experiments are performed to investigate the influence of micromilling process parameters on machining forces, tool edge condition, and surface texture. Under the experimental conditions used in this study, built-up edge formation is observed to have a significant influence on the process outputs in micromilling of titanium alloy Ti6Al4V. In the second part, Bayesian inference was explained in detail and applied to model micromilling force prediction. The force predictions are validated with the experimental measurements. The paper concludes with a discussion of the effectiveness of employing Bayesian inference in micromilling force modeling considering special machining cases.

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“…because this method is capable of machining complex structures. To predict the overall three-dimensional components of shear force in these processes, a force prediction model has been proposed and tested with experimental measurements (6). In addition, given the great importance of precision in micro milling due to the small tolerances involved, a real-time monitoring system is proposed to predict surface roughness with an estimation error of 9.5%, using the vibration signal emitted during the milling process (7).…”

Section: Introductionmentioning

confidence: 99%

Effects of Depth of Cut on Cylindrical Milling Process in Steel Casting: A Numerical Study

Salcedo¹,

Pealoza²,

Ochoa³

2018

IJCTR

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The complexity of the milling process has led us to study different parameters, among which are the cutting speed, feed speed, chip volume, cutting time and associated costs, which are the focus of this study. For this purpose, a calculation algorithm was designed in which fixed parameters were left and the cutting depth was varied from 2 to 8 mm. This resulted in an increase in process times and costs, which was expected due to the removal of more material and a negative impact on the surface finish of the part.

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Cutting forces in micro-end-milling processes

Cited by 152 publications

References 23 publications

Investigating the influence of friction conditions on finite element simulation of microscale machining with the presence of built-up edge

Investigating the influence of friction conditions on finite element simulation of microscale machining with the presence of built-up edge

Uncertainty analysis of force coefficients during micromilling of titanium alloy

Effects of Depth of Cut on Cylindrical Milling Process in Steel Casting: A Numerical Study

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