Mechanistic Modeling of Five-Axis Machining With a Flat End Mill Considering Bottom Edge Cutting Effect

2016 ◽  
Vol 138 (11) ◽  
Author(s):  
Zhou-Long Li ◽  
Li-Min Zhu
Keyword(s):  
Cutting Forces ◽  
Mechanistic Model ◽  
Mechanistic Modeling ◽  
End Mill ◽  
Bottom Edge ◽  
Radial Line ◽  
Bottom Part ◽  
Lead Angle ◽  
Cutting Effect ◽  
Five Axis

In five-axis milling, the bottom edge of a flat end mill is probably involved in cutting when the lead angle of tool axis changes to negative. The mechanistic model will lose accuracy if the bottom edge cutting effect is neglected. In this paper, an improved mechanistic model of five-axis machining with a flat end mill is presented to accurately predict cutting forces by combining the cutting effects of both side and bottom edges. Based on the kinematic analysis of the radial line located at the tool bottom part, the feasible contact radial line (FCRL) is analytically extracted. Then, boundaries of the bottom cutter-workpiece engagements (CWEs) are obtained by intersecting the FCRL with workpiece surfaces and identifying the inclusion relation of its endpoints with the workpiece volume. Next, an analytical method is proposed to calculate the cutting width and the chip area by considering five-axis motions of the tool. Finally, the method of calibrating bottom-cutting force coefficients by conducting a series of plunge milling tests at various feedrates is proposed, and the improved mechanistic model is then applied to predict cutting forces. The five-axis milling with a negative lead angle and the rough machining of an aircraft engine blisk are carried out to test the effectiveness and practicability of the proposed model. The results indicate that it is essential to take into account the bottom edge cutting effect for accurate prediction of cutting forces at tool path zones where the tool bottom part engages with the workpiece.

scholarly journals Mechanistic modeling of cutting forces in high-speed microturning of titanium alloy with consideration of nose radius

2021 ◽  
Author(s):  
Kubilay Aslantas ◽  
Şükrü Ülker ◽  
Ömer Şahan ◽  
Danil Yu Pimenov ◽  
Khaled Giasin
Keyword(s):  
Cutting Forces ◽  
High Speed ◽  
Mechanistic Model ◽  
Cutting Speed ◽  
Mechanistic Modeling ◽  
Machining Process ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Multilinear Regression Analysis ◽  
Edge Radius

AbstractMicroturning is a micromechanical machining process used to produce microcylindrical or axially symmetrical parts. Microcylindrical parts are mainly used in microfluidic systems, intravenous micromotors, microsurgical applications, optical lens applications, and microinjection systems. The workpiece diameter is very small in microturning and therefore is greatly affected by the cutting forces. For this reason, it is important to predict the cutting forces when machining miniature parts. In this study, an analytical mechanistic model of microturning is used to predict the cutting forces considering the tool nose radius. In the semi-empirically developed mechanistic model, the tool radius was considered. A series of semi-orthogonal microturning cutting tests were carried out to determine the cutting and edge force coefficients. The mechanistic model was generalized depending on the cutting speed and depth of cut by performing multilinear regression analysis. In the study, the depth of cut (ap = 30–90 µm) and feed values (f = 0.5–20 µm/rev) were selected considering the nose radius and edge radius of the cutting tool. The experiments were carried out under high-cutting speeds (Vc = 150–500 m/min) and microcutting conditions. Ti6Al4V alloy was used as the workpiece material and the tests were carried out under dry cutting conditions. Validation tests for different cutting parameters were carried out to validate the accuracy of the developed mechanistic model. The results showed that the difference between the mechanistic model and the experimental data was a minimum of 3% and a maximum of 24%. The maximum difference between the experimental and the model usually occurs in forces in the tangential direction. It has been observed that the developed model gives accurate results even at a depth of cut smaller than the nose radius and at feed values smaller than the edge radius.

Interference-Free Multi-Axis NC Machining of Cylindrical Cam Using Enveloping Element

2009 ◽  
Vol 419-420 ◽  
pp. 333-336
Author(s):  
Jeng Nan Lee ◽  
Chih Wen Luo ◽  
Hung Shyong Chen
Keyword(s):  
Cutting Tool ◽  
Nc Machining ◽  
Model Material ◽  
Solid Model ◽  
End Mill ◽  
Generating Method ◽  
Collision Problem ◽  
Five Axis ◽  
Cutting Path ◽  
Cutting Simulations

To obtain the flexibility of choice of cutting tool and to compensate the wear of the cutting tool, this paper presents an interference-free toolpath generating method for multi-axis machining of a cylindrical cam. The notion of the proposed method is that the cutting tool is confined within the meshing element and the motion of the cutting tool follows the meshing element so that collision problem can be avoided. Based on the envelope theory, homogeneous coordinate transformation and differential geometry, the cutter location for multi-axis NC machining using cylindrical-end mill is derived and the cutting path sequences with the minimum lead in and lead out are planned. The cutting simulations with solid model are performed to verify the proposed toolpath generation method. It is also verified through the trial cut with model material on a five-axis machine tool.

Tool Path Generation for Five-Axis Controlled Machining of Free-Form Surface Using Barrel Tool: Control of Contact Point on Cutting Edge

2020 ◽  
Author(s):  
Tomonobu Suzuki ◽  
Koichi Morishige
Keyword(s):  
Tool Path ◽  
Contact Point ◽  
Cutting Edge ◽  
Free Form ◽  
End Mill ◽  
Ball End Mill ◽  
Surface Machining ◽  
Free Form Surface ◽  
The Cost ◽  
Five Axis

Abstract This study aimed to improve the efficiency of free-form surface machining by using a five-axis controlled machine tool and a barrel tool. The barrel tool has cutting edges, with curvature smaller than the radius, increasing the pick feed width compared with a conventional ball end mill of the same tool radius. As a result, the machining efficiency can be improved; however, the cost of the barrel tool is high and difficult to reground. In this study, a method to obtain the cutting points that make the cusp height below the target value is proposed. Moreover, a method to improve the tool life by continuously and uniformly changing the contact point on the cutting edge is proposed. The usefulness of the developed method is confirmed through machining simulations.

A Mechanistic Force Model of the 5-Axis Milling Process

2000 ◽  
Author(s):  
Paul A. Clayton ◽  
Mohamed A. Elbestawi ◽  
Tahany El-Wardany ◽  
Dan Viens
Keyword(s):  
High Speed ◽  
Mechanistic Model ◽  
Back Propagation ◽  
High Speed Steel ◽  
Cutting Edge ◽  
Analytic Description ◽  
Force Model ◽  
Force Output ◽  
Five Axis ◽  
Milling Force Model

Abstract This paper presents a five-axis milling force model that can incorporate a variety of cutters and workpiece materials. The mechanistic model uses a discretized cutting edge to calculate an area of intersection which is multiplied by the specific cutting pressure to produce a force output along the primary cartesian coordinate system. By using an analytic description of the cutting edge with a non-specific cutter and workpiece intersection routine, a model was created that can describe a variety of cutting situations. Furthermore, a back propagation neural network is used to calibrate the model, providing robustness and scalability to the calibration process. Testing was performed on 1020 steel using various cutting parameters with a high speed steel two flute cutter and a tungsten carbide insert cutter. Furthermore, both linear cuts and a test die surface yielded good agreement between predicted and measured results.

scholarly journals Inverse mechanistic modeling of transdermal drug delivery for fast identification of optimal model parameters

2020 ◽  
Author(s):  
Thijs Defraeye ◽  
Flora Bahrami ◽  
Rene M Rossi
Keyword(s):  
Drug Delivery ◽  
Inverse Modeling ◽  
Transdermal Drug Delivery ◽  
Drug Transport ◽  
Mechanistic Model ◽  
Mechanistic Modeling ◽  
Drug Uptake ◽  
Added Value ◽  
Model Parameters ◽  
Transdermal Drug Delivery Systems

Transdermal drug delivery systems are a key technology to administer drugs with a high first-pass effect in a non-invasive and controlled way. Physics-based modeling and simulation are on their way to become a cornerstone in the engineering of these healthcare devices since it provides a unique complementarity to experimental data and insights. Simulations enable to virtually probe the drug transport inside the skin at each point in time and space. However, the tedious experimental or numerical determination of material properties currently forms a bottleneck in the modeling workflow. We show that multiparameter inverse modeling to determine the drug diffusion and partition coefficients is a fast and reliable alternative. We demonstrate this strategy for transdermal delivery of fentanyl. We found that inverse modeling reduced the normalized root mean square deviation of the measured drug uptake flux from 26 to 9%, when compared to the experimental measurement of all skin properties. We found that this improved agreement with experiments was only possible if the diffusion in the reservoir holding the drug was smaller than the experimentally-measured diffusion coefficients suggested. For indirect inverse modeling, which systematically explores the entire parametric space, 30 000 simulations were required. By relying on direct inverse modeling, we reduced the number of simulations to be performed to only 300, so a factor 100 difference. The modeling approach's added value is that it can be calibrated once in-silico for all model parameters simultaneously by solely relying on a single measurement of the drug uptake flux evolution over time. We showed that this calibrated model could accurately be used to simulate transdermal patches with other drug doses. We showed that inverse modeling is a fast way to build up an accurate mechanistic model for drug delivery. This strategy opens the door to clinically-ready therapy that is tailored to patients.

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