A New Mechanistic Approach for Micro End Milling Force Modeling

2010 ◽  
Author(s):  
Martin B. G. Jun ◽  
Chanseo Goo ◽  
Mohammad Malekian ◽  
Simon S. Park
Keyword(s):  
End Milling ◽  
Elastic Recovery ◽  
Rake Angle ◽  
Mechanistic Modeling ◽  
Force Modeling ◽  
Edge Radius ◽  
Effective Rake Angle ◽  
Wide Range ◽  
Micro End Milling ◽  
Milling Forces

This paper investigates the mechanistic modeling of micro end milling forces, with consideration of the effects of plowing, elastic recovery, effective rake angle, and flank face rubbing. Two different mechanistic models are developed for shearing- and plowing-dominant regimes. Micro end milling experiments are conducted to validate the model for Aluminum 6061; and, the model appropriately predicts force profiles for a wide range of feed rates, and prediction of the root mean square (RMS) values of the resultant forces is, on average, within a 12% error. The study of the model shows that plowing and rubbing force contributions are significant, especially at low feed rates. The edge radius is found to have a significant effect on plowing and rubbing force components and the effective rake angle, which indicates that it is important to maintain a low edge radius to reduce micro end milling forces.

A New Mechanistic Approach for Micro End Milling Force Modeling

2012 ◽  
Vol 134 (1) ◽  
Author(s):  
Martin B. G. Jun ◽  
Chanseo Goo ◽  
Mohammad Malekian ◽  
Simon Park
Keyword(s):  
End Milling ◽  
Elastic Recovery ◽  
Rake Angle ◽  
Mechanistic Modeling ◽  
Force Modeling ◽  
Edge Radius ◽  
Effective Rake Angle ◽  
Wide Range ◽  
Micro End Milling ◽  
Milling Forces

This paper investigates the mechanistic modeling of micro end milling forces, with consideration of the effects of plowing, elastic recovery, effective rake angle, and flank face rubbing. Two different mechanistic models are developed for shearing- and plowing-dominant regimes. Micro end milling experiments are conducted to validate the model for Aluminum 6061; and, the model appropriately predicts force profiles for a wide range of feed rates, and prediction of the root mean square (RMS) values of the resultant forces is, on average, within a 12% error. The study of the model shows that plowing and rubbing force contributions are significant, especially at low feed rates. The edge radius is found to have a significant effect on plowing and rubbing force components and the effective rake angle, which indicates that it is important to maintain a low edge radius to reduce micro end milling forces.

Micro Flat End Milling Simulation Model With Instantaneous Plowing Area Prediction

2016 ◽  
Vol 4 (2) ◽  
Author(s):  
Abdolreza Bayesteh ◽  
Junghyuk Ko ◽  
Martin Byung-Guk Jun
Keyword(s):  
Feed Rate ◽  
Tool Path ◽  
End Milling ◽  
Chip Thickness ◽  
Depth Of Cut ◽  
Uncut Chip Thickness ◽  
Chip Area ◽  
Edge Radius ◽  
Wide Range ◽  
Radial Depth

There is an increasing demand for product miniaturization and parts with features as low as few microns. Micromilling is one of the promising methods to fabricate miniature parts in a wide range of sectors including biomedical, electronic, and aerospace. Due to the large edge radius relative to uncut chip thickness, plowing is a dominant cutting mechanism in micromilling for low feed rates and has adverse effects on the surface quality, and thus, for a given tool path, it is important to be able to predict the amount of plowing. This paper presents a new method to calculate plowing volume for a given tool path in micromilling. For an incremental feed rate movement of a micro end mill along a given tool path, the uncut chip thickness at a given feed rate is determined, and based on the minimum chip thickness value compared to the uncut chip thickness, the areas of plowing and shearing are calculated. The workpiece is represented by a dual-Dexel model, and the simulation properties are initialized with real cutting parameters. During real-time simulation, the plowed volume is calculated using the algorithm developed. The simulated chip area results are qualitatively compared with measured resultant forces for verification of the model and using the model, effects of cutting conditions such as feed rate, edge radius, and radial depth of cut on the amount of shearing and plowing are investigated.

Force Modeling of Five-Axis Microball-End Milling

2015 ◽  
Vol 3 (3) ◽  
Author(s):  
Chi Xu ◽  
James Zhu ◽  
Shiv G. Kapoor
Keyword(s):  
End Milling ◽  
Elastic Recovery ◽  
Chip Thickness ◽  
Force Model ◽  
End Mill ◽  
Data Simulation ◽  
Force Modeling ◽  
Static Indentation ◽  
Five Axis ◽  
Milling Force Model

This paper presents a five-axis ball-end milling force model that is specifically tailored to microscale machining. A composite cutting force is generated by combining two force contributions from a shearing/ploughing slip-line (SL) field model and a quasi-static indentation (ID) model. To fully capture the features of microscale five-axis machining, a unique chip thickness algorithm based on the velocity kinematics of a ball-end mill is proposed. This formulation captures intricate tool trajectories as well as readily allows the integration of runout and elastic recovery effects. A workpiece updating algorithm has also been developed to identify tool–workpiece engagement. As a dual purpose, historical elastic recovery is stored locally on the meshed workpiece surface in vector form so that the directionality of elastic recovery is preserved for future time increments. The model has been validated through a comparison with five-axis end mill force data. Simulation results show reasonably accurate replication of end milling cutting forces with minimal experimental data fitting.

Experimental Study on Micro End-Milling Process of Ti-6AL-4V Using Nanofluid Minimum Quantity Lubrication (MQL)

2014 ◽  
Author(s):  
Dae Hoon Kim ◽  
Pil-Ho Lee ◽  
Jung Sub Kim ◽  
Hyungpil Moon ◽  
Sang Won Lee
Keyword(s):  
Surface Roughness ◽  
Titanium Alloy ◽  
End Milling ◽  
Minimum Quantity Lubrication ◽  
Milling Process ◽  
Minimum Quantity ◽  
Nanofluid Minimum Quantity Lubrication ◽  
Micro End Milling ◽  
Milling Forces ◽  
End Milling Process

This paper investigates the characteristics of micro end-milling process of titanium alloy (Ti-6AL-4V) using nanofluid minimum quantity lubrication (MQL). A series of micro end-milling experiments are conducted in the meso-scale machine tool system, and milling forces, burr formations, surface roughness, and tool wear are observed and analyzed according to varying feed per tooth and lubrication conditions. The experimental results show that MQL and nanofluid MQL with nanodiamond particles can be effective to reduce milling forces, burrs and surface roughness during micro end-milling of titanium alloy. In particular, it is demonstrated that smaller size of nanodiamond particles — 35 nm — can be more effective to decrease burrs and surface roughness in the case of nanofluid MQL micro end-milling.

Characterization and Micromilling of Flow Induced Aligned Carbon Nanotube Nanocomposites

2013 ◽  
Vol 1 (1) ◽  
Author(s):  
Mehdi Mahmoodi ◽  
M. G. Mostofa ◽  
Martin Jun ◽  
Simon S. Park
Keyword(s):  
Thermal Conductivity ◽  
Carbon Nanotube ◽  
Cutting Forces ◽  
End Milling ◽  
Flow Direction ◽  
High Strength ◽  
Force Model ◽  
Micro End Milling ◽  
Different Characteristics ◽  
Milling Forces

Carbon nanotube (CNT) based polymeric composites exhibit high strength and thermal conductivity and can be electrically conductive at a low percolation threshold. CNT nanocomposites with polystyrene (PS) thermoplastic matrix were injection-molded and high shear stress in the flow direction enabled partial alignment of the CNTs. The samples with different CNT concentrations were prepared to study the effect of CNT concentration on the cutting behavior of the samples. Characterizations of CNT polymer composites were studied to relate different characteristics of materials such as thermal conductivity and mechanical properties to micromachining. Micro-end milling was performed to understand the material removal behavior of CNT nanocomposites. It was found that CNT alignment and concentrations influenced the cutting forces. The mechanistic micromilling force model was used to predict the cutting forces. The force model has been verified with the experimental milling forces. The machinability of the CNT nanocomposites was better than that of pure polymer due to the improved thermal conductivity and mechanical characteristics.

Modeling of burr thickness in micro-end milling of Ti6Al4V

2018 ◽  
Vol 233 (4) ◽  
pp. 1087-1102 ◽  
Author(s):  
Vipindas Kizhakken ◽  
Jose Mathew
Keyword(s):  
Mathematical Model ◽  
Prediction Error ◽  
End Milling ◽  
Value Added ◽  
Material Model ◽  
Machining Process ◽  
Micro Machining ◽  
Proposed Model ◽  
Wide Range ◽  
Micro End Milling

Mechanical micro-machining of Ti6Al4V is finding great demand because of its wide range of application in various fields such as communication, optics and biomedical devices. Increasing demands on functioning and performance requires components to be free from burrs after the machining process. Presence of burrs on micro-mechanical parts or features significantly affects quality and proper assembly of the parts. Also in micro-machining, the size of burr is comparable to that of micro-features. Since the formation of burr is inevitable in any machining process, generally the deburring operation is performed to remove burrs. Burr thickness is one of the important parameters which describe the time and method necessary for the deburring operation. Burrs on micro-parts are generally characterized using scanning electron microscope, which is a time-consuming, costly and non-value-added activity. However, a proper mathematical model will help predict burr thickness easily. In this article, a mathematical model to predict burr thickness during micro-end milling of Ti6Al4V is presented. The proposed model was developed based on the principle of continuity of work at the transition from chip formation to burr formation. Ti6Al4V titanium alloy is one of the materials which generates segmented (saw-tooth) chips at low cutting speeds. Hence, initially an appropriate material constitutive model was selected based on better prediction of burr thickness. Then, to reduce the prediction error, machining temperature was evaluated for all experimental conditions and included in the model. From the initial study, it was found that Hyperbolic TANgent material model gives a better prediction compared to Johnson–Cook material model. Later, after including machining temperature into the model it was observed that the prediction error was reduced. The proposed model was validated with the experimental results.

Sign in / Sign up

Export Citation Format

Share Document