On the Modeling and Analysis of Machining Performance in Micro-Endmilling, Part I: Surface Generation

2004 ◽  
Vol 126 (4) ◽  
pp. 685-694 ◽  
Author(s):  
Michael P. Vogler ◽  
Richard E. DeVor ◽  
Shiv G. Kapoor
Keyword(s):  
Surface Roughness ◽  
Ductile Iron ◽  
Single Phase ◽  
Chip Thickness ◽  
Thickness Effect ◽  
Surface Generation ◽  
Generation Model ◽  
Generation Process ◽  
Machining Performance ◽  
Minimum Chip Thickness

This paper examines the surface generation process in the micro-endmilling of both single-phase and multiphase workpiece materials. We used 508 μm dia endmills with edge radii of 2 and 5 μm to machine slots in ferrite, pearlite, and two ductile iron materials at feed rates ranging from 0.25 to 3.0 μm/flute. A surface generation model to predict the surface roughness for the slot floor centerline is then developed based on the minimum chip thickness concept. The minimum chip thickness values were found through finite element simulations for the ferrite and pearlite materials. The model is shown to accurately predict the surface roughness for single-phase materials, viz., ferrite and pearlite. Two phenomena were found to combine to generate an optimal feed rate for the surface generation of single-phase materials: (i) the geometric effect of the tool and process geometry and (ii) the minimum chip thickness effect. The surface roughness measurements for the ductile iron workpieces indicate that the micromilling surface generation process for multiphase workpiece materials is also affected by the interrupted chip-formation process as the cutting edge moves between phases resulting in burrs at the phase boundaries and the associated increases in surface roughness.

On the Modeling and Analysis of Machining Performance in Micro-Endmilling, Part II: Cutting Force Prediction

2004 ◽  
Vol 126 (4) ◽  
pp. 695-705 ◽  
Author(s):  
Michael P. Vogler ◽  
Shiv G. Kapoor ◽  
Richard E. DeVor
Keyword(s):  
Cutting Force ◽  
Ductile Iron ◽  
Chip Thickness ◽  
Thickness Effect ◽  
Force Model ◽  
Machining Performance ◽  
Cutting Force Prediction ◽  
Minimum Chip Thickness ◽  
Modeling And Analysis ◽  
Deformation Force

In Part II of this paper, a cutting force model for the micro-endmilling process is developed. This model incorporates the minimum chip thickness concept in order to predict the effects of the cutter edge radius on the cutting forces. A new chip thickness computation algorithm is developed to include the minimum chip thickness effect. A slip-line plasticity force model is used to predict the force when the chip thickness is greater than the minimum chip thickness, and an elastic deformation force model is employed when the chip thickness is less than the minimum chip thickness. Orthogonal, microstructure-level finite element simulations are used to calibrate the parameters of the force models for the primary metallurgical phases, ferrite and pearlite, of multiphase ductile iron workpieces. The model is able to predict the magnitudes of the forces for both the ferrite and pearlite workpieces as well as for the ductile iron workpieces within 20%.

Model-Based Analysis of the Surface Generation in Microendmilling—Part I: Model Development

2006 ◽  
Vol 129 (3) ◽  
pp. 453-460 ◽  
Author(s):  
Xinyu Liu ◽  
Richard E. DeVor ◽  
Shiv G. Kapoor
Keyword(s):  
Stochastic Model ◽  
Surface Topography ◽  
Deterministic Model ◽  
Elastic Recovery ◽  
Chip Thickness ◽  
Surface Generation ◽  
Generation Model ◽  
Generation Process ◽  
Floor Surface ◽  
Tool Edge

This paper presents the development of models that describe the surface-generation process for microendmilling. The surface-generation models for the sidewall and floor surfaces consist of deterministic and stochastic models. In the sidewall surface-generation model, the deterministic model characterizes the surface topography generated from the relative motion between the major cutting edge and the workpiece material. The model includes the effects of the process kinematics, dynamics, tool edge serration, and process faults (e.g., tool tip runout). The stochastic model predicts the increased surface roughness generated from ploughing due to the significant tool edge radius effect. In the floor surface-generation model, the deterministic model characterizes the three-dimensional surface topography over the entire floor surface and considers the effects of the minimum chip thickness, the elastic recovery, and the transverse vibration. The variation of the ploughing amount across the swept arc of the cutter due to the varying chip load conditions is considered in the stochastic model.

A Micromilling Experimental Study on AISI 4340 Steel

2009 ◽  
Vol 407-408 ◽  
pp. 335-338 ◽  
Author(s):  
Jin Sheng Wang ◽  
Da Jian Zhao ◽  
Ya Dong Gong
Keyword(s):  
Experimental Study ◽  
Surface Roughness ◽  
Cutting Force ◽  
Spectrum Analysis ◽  
Chip Thickness ◽  
Experimental Results ◽  
Minimum Chip Thickness ◽  
Aisi 4340 Steel ◽  
4340 Steel ◽  
Aisi 4340

A micromilling experimental study on AISI 4340 steel is conducted to understand the micromilling principle deeply. The experimental results, especially on the surface roughness and cutting force, are discussed in detail. It has been found the minimum chip thickness influences the surface roughness and cutting force greatly. Meanwhile, the material elastic recover induces the increase of the axial micromilling force. The average cutting force and its spectrum analysis validate the minimum chip thickness approximation of AISI 4340 is about 0.35μm.

An Analytical Model for the Prediction of Minimum Chip Thickness in Micromachining

2005 ◽  
Vol 128 (2) ◽  
pp. 474-481 ◽  
Author(s):  
X. Liu ◽  
R. E. DeVor ◽  
S. G. Kapoor
Keyword(s):  
Analytical Model ◽  
Chip Thickness ◽  
Machining Process ◽  
Thickness Effect ◽  
Uncut Chip Thickness ◽  
Minimum Chip Thickness ◽  
Tool Edge Radius ◽  
Edge Radius ◽  
Tool Edge ◽  
Cutting Velocity

In micromachining, the uncut chip thickness is comparable or even less than the tool edge radius and as a result a chip will not be generated if the uncut chip thickness is less than a critical value, viz., the minimum chip thickness. The minimum chip thickness effect significantly affects machining process performance in terms of cutting forces, tool wear, surface integrity, process stability, etc. In this paper, an analytical model has been developed to predict the minimum chip thickness values, which are critical for the process model development and process planning and optimization. The model accounts for the effects of thermal softening and strain hardening on the minimum chip thickness. The influence of cutting velocity and tool edge radius on the minimum chip thickness has been taken into account. The model has been experimentally validated with 1040 steel and Al6082-T6 over a range of cutting velocities and tool edge radii. The developed model has then been applied to investigate the effects of cutting velocity and edge radius on the normalized minimum chip thickness for various carbon steels with different carbon contents and Al6082-T6.

Modeling the Material Microstructure Effects on the Surface Generation Process in Microendmilling of Dual-Phase Materials

2012 ◽  
Vol 134 (4) ◽  
Author(s):  
A. M. Abdelrahman Elkaseer ◽  
S. S. Dimov ◽  
K. B. Popov ◽  
M. Negm ◽  
R. Minev
Keyword(s):  
Chip Thickness ◽  
Machining Process ◽  
Surface Generation ◽  
Dual Phase ◽  
Generation Process ◽  
Phase Boundaries ◽  
Material Microstructure ◽  
Workpiece Material ◽  
Multiphase Materials ◽  
Proposed Model

The anisotropic behavior of the material microstructure when processing multiphase materials at microscale becomes an important factor that has to be considered throughout the machining process. This is especially the case when chip-loads and machined features are comparable in size to the cutting edge radius of the tool, and also similar in scale to the grain sizes of the phases present within the material microstructure. Therefore, there is a real need for reliable models, which can be used to simulate the surface generation process during microendmilling of multiphase materials.This paper presents a model to simulate the surface generation process during microendmilling of multiphase materials. The proposed model considers the effects of the following factors: the geometry of the cutting tool, the feed rate, and the workpiece material microstructure. Especially, variations of the minimum chip thickness at phase boundaries are considered by feeding maps of the material microstructure into the model. Thus, the model takes into account these variations that alter the machining mechanism from a proper cutting to ploughing and vice versa, and are the main cause of microburr formation. By applying the proposed model, it is possible to estimate more accurately the resulting roughness because the microburr formation dominates the surface generation process during microendmilling of multiphase materials. The proposed model was experimentally validated by machining two different samples of dual-phase steel under a range of chip-loads. The roughness of the resulting surfaces was measured and compared to the predictions of the proposed model under the same cutting conditions. The results show that the proposed model accurately predicts the roughness of the machined surfaces by taking into account the effects of material multiphase microstructure. Also, the developed model successfully elucidates the mechanism of microburr formation at the phase boundaries, and quantitatively describes its contributions to the resulting surface roughness after microendmilling.

scholarly journals Influence of the Minimum Chip Thickness on the Obtained Surface Roughness During Turning Operations

Procedia CIRP ◽  
2014 ◽  
Vol 13 ◽  
pp. 67-71 ◽  
Author(s):  
Fredrik Schultheiss ◽  
Sören Hägglund ◽  
Volodymyr Bushlya ◽  
Jinming Zhou ◽  
Jan-Eric Ståhl
Keyword(s):  
Surface Roughness ◽  
Chip Thickness ◽  
Turning Operations ◽  
Minimum Chip Thickness

Investigation of the Dynamics of Microend Milling—Part II: Model Validation and Interpretation

2006 ◽  
Vol 128 (4) ◽  
pp. 901-912 ◽  
Author(s):  
Martin B. G. Jun ◽  
Richard E. DeVor ◽  
Shiv G. Kapoor
Keyword(s):  
Dynamic Model ◽  
End Milling ◽  
Elastic Recovery ◽  
Chip Thickness ◽  
Thickness Effect ◽  
Depth Of Cut ◽  
Minimum Chip Thickness ◽  
Microend Milling ◽  
The Stability ◽  
Cutting Mechanisms

In Part II of this paper, experimental and analytical methods have been developed to estimate the values of the process faults defined in Part I of this paper. The additional faults introduced by the microend mill design are shown to have a significant influence on the total net runout of the microend mill. The dynamic model has been validated through microend milling experiments. Using the dynamic model, the effects of minimum chip thickness and elastic recovery on microend milling stability have been studied over a range of feed rates for which the cutting mechanisms vary from ploughing-dominated to shearing-dominated. The minimum chip thickness effect is found to cause feed rate dependent instability at low feed rates, and the range of unstable feed rates depends on the axial depth of cut. The effects of process faults on microend mill vibrations have also been studied and the influence of the unbalance from the faults is found to be significant as spindle speed is increased. The stability characteristics due to the regenerative effect have been studied. The results show that the stability lobes from the second mode of the microend mill, which are generally neglected in macroscale end milling, affect the microend mill stability significantly.

scholarly journals Material microstructure effects in micro-endmilling of Cu99.9E

2016 ◽  
Vol 232 (7) ◽  
pp. 1143-1155 ◽  
Author(s):  
AM Elkaseer ◽  
SS Dimov ◽  
DT Pham ◽  
KP Popov ◽  
L Olejnik ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Grain Size ◽  
Chip Thickness ◽  
Micro Milling ◽  
Coarse Grained ◽  
Material Microstructure ◽  
Micro Cutting ◽  
Minimum Chip Thickness ◽  
Average Grain Size ◽  
Material Homogeneity

This article presents an investigation of the machining response of metallurgically and mechanically modified materials at the micro-scale. Tests were conducted that involved micro-milling slots in coarse-grained Cu99.9E with an average grain size of 30 µm and ultrafine-grained Cu99.9E with an average grain size of 200 nm, produced by equal channel angular pressing. A new method based on atomic force microscope measurements is proposed for assessing the effects of material homogeneity changes on the minimum chip thickness required for a robust micro-cutting process with a minimum surface roughness. The investigation has shown that by refining the material microstructure the minimum chip thickness can be reduced and a high surface finish can be obtained. Also, it was concluded that material homogeneity improvements lead to a reduction in surface roughness and surface defects in micro-cutting.

scholarly journals Development of Surface Roughness Generation Model for CFRTP Manufactured by LFT-D

2020 ◽  
Vol 14 (2) ◽  
pp. 208-216
Author(s):  
Motoyuki Murashima ◽  
Takaharu Murooka ◽  
Noritsugu Umehara ◽  
Takayuki Tokoroyama ◽  
◽  
...  
Keyword(s):  
Surface Roughness ◽  
Standard Deviation ◽  
Carbon Fiber ◽  
Volume Fraction ◽  
Regression Line ◽  
Surface Generation ◽  
Thermal Shrinkage ◽  
Generation Model ◽  
Cross Sectional ◽  
Estimation Formula

In this study, we propose a new surface generation model for carbon fiber reinforced thermoplastics (CFRTP) manufactured by the long fiber thermoplastic-direct (LFT-D) method. CFRTP are considered to be a next-generation structural material because of their high productivity as well as high mechanical strength and lightness. Conversely, CFRTP have a rough surface, which does not meet the automotive outer panel standard of a “class A surface.” In the present study, we establish a surface roughness generation model based on a thermal shrinkage mismatch of thermoplastic resin to carbon fiber and non-uniform carbon fiber distribution. Furthermore, we construct a surface roughness estimation formula based on the model. In the calculation, a cross-sectional image of CFRTP is divided into many vertical segments. Subsequently, the thermal shrinkage of each segment is calculated with a standard deviation, an average, and a probability density of the amount of carbon fiber in each segment. The surface roughness of the manufactured CFRTP was measured using a surface profilometer. The result showed that the arithmetic surface roughness increased with the volume fraction of carbon fiber. We applied the surface roughness calculation to cross-sectional images of the specimens. Consequently, the estimated surface roughness showed the same tendency, in which the surface roughness increased with the volume fraction of carbon fiber. The slope of a regression line of the estimated surface roughness with respect to the volume fraction was 0.010, which was almost the same (0.011) as the slope of a regression line of the measured surface roughness. Furthermore, the estimation formula using a thermal shrinkage effective depth of 395 μm was able to estimate the surface roughness within a 3% average error. Using the estimation formula, it was predicted that the surface roughness increased with the standard deviation of the amount of carbon fiber in a segment. To confirm the reliability of the model and the formula, we measured the standard deviation of the amount of carbon fiber in CFRTP specimens, showing that the trend for CFRTP specimens matched the estimated values.

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