scholarly journals Simulating the effect of depth of cut and feed rate on the force components in face milling

2019 ◽  
Vol 9 (1) ◽  
pp. 65-72
Author(s):  
Mohammad Zaher Akkad ◽  
Felhő Csaba
Keyword(s):  
Feed Rate ◽  
Face Milling ◽  
Depth Of Cut ◽  
Third Wave ◽  
Cutting Depth ◽  
Milling Operation ◽  
The Face ◽  
Force Components ◽  
Cutting Processes ◽  
The Impact

This paper presents a study about the workpiece force components (Fx, Fy, Fz) changes in face milling, which results from changing the depth of cut and the feed rate values. The values of the three force components in the face milling operation were found through the FEA-software AdvantEdge by Third Wave Systems. This program is uniquely intended for modelling of cutting processes. Simulations were carried out within five different cutting depth of cut and feed rate, to compare the obtained values and find out the results of the impact of changes on the three force components.

scholarly journals Finite element modelling of cutting force components in face milling

2020 ◽  
Vol 10 (1) ◽  
pp. 119-128
Author(s):  
Csaba Felhő
Keyword(s):  
Finite Element ◽  
Cutting Force ◽  
Finite Element Modelling ◽  
Measurement Data ◽  
Face Milling ◽  
Third Wave ◽  
Element Modelling ◽  
Cutting Force Components ◽  
Force Components ◽  
Cutting Processes

This paper presents a study about the Finite Element Modelling of cutting force components acting on the workpiece (Fx, Fy, Fz) in face milling. The values of the three force components were simulated by the FEM software AdvantEdge by Third Wave Systems. This program is uniquely intended for modelling of cutting processes. The simulated cutting force values were compared with real measurement data, and a good correlation was between them.

Nature instigated Grey wolf algorithm for parametric optimization during machining (Milling) of polymer nanocomposites

2021 ◽  
pp. 089270572199320
Author(s):  
Prakhar Kumar Kharwar ◽  
Rajesh Kumar Verma
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Polymer Nanocomposites ◽  
Feed Rate ◽  
Fitness Function ◽  
Depth Of Cut ◽  
Multiwall Carbon Nanotube ◽  
Grey Wolf ◽  
Milling Characteristics ◽  
The Impact

The new era of engineering society focuses on the utilization of the potential advantage of carbon nanomaterials. The machinability facets of nanocarbon materials are passing through an initial stage. This article emphasizes the machinability evaluation and optimization of Milling performances, namely Surface roughness (Ra), Cutting force (Fc), and Material removal rate (MRR) using a recently developed Grey wolf optimization algorithm (GWOA). The Taguchi theory-based L27 orthogonal array (OA) was employed for the Machining (Milling) of polymer nanocomposites reinforced by Multiwall carbon nanotube (MWCNT). The second-order polynomial equation was intended for the analysis of the model. These mathematical models were used as a fitness function in the GWOA to predict machining performances. The ANOVA outcomes efficiently explore the impact of machine parameters on Milling characteristics. The optimal combination for lower surface roughness value is 1.5 MWCNT wt.%, 1500 rpm of spindle speed, 50 mm/min of feed rate, and 3 mm depth of cut. For lower cutting force, 1.0 wt.%, 1500 rpm, 90 mm/min feed rate and 1 mm depth of cut and the maximize MRR was acquired at 0.5 wt.%, 500 rpm, 150 mm/min feed rate and 3 mm depth of cut. The deviation of the predicted value from the experimental value of Ra, Fc, and MRR are found as 2.5, 6.5 and 5.9%, respectively. The convergence plot of all Milling characteristics suggests the application potential of the GWO algorithm for quality improvement in a manufacturing environment.

scholarly journals The cutting behavior of cortical bone in different bone osten cutting angles and depths of cut

2021 ◽  
Author(s):  
Yuanqiang Luo ◽  
Yinghui Ren ◽  
Yang Shu ◽  
Cong Mao ◽  
Zhixiong Zhou ◽  
...  
Keyword(s):  
Fracture Toughness ◽  
Cutting Force ◽  
Cortical Bone ◽  
Depth Of Cut ◽  
Cutting Angle ◽  
Small Depth ◽  
Proposed Model ◽  
Cutting Processes ◽  
The Impact ◽  
Cutting Path

Abstract Cortical bones are semi-brittle and anisotropic, this brings the challenge to suppress vibration and avoid undesired fracture in precise cutting processes in surgeries. In this paper, we proposed a novel analytical model to represent cutting processes of cortical bones, and we used to evaluate cutting forces and fracture toughness, and investigate the formations of chips and cracks under varying bone osteon cutting angles and depths. To validate the proposed model, the experiments are conducted on orthogonal cuttings over cortical bones to investigate the impact of bone osteon cutting angle and depth on cutting force, crack initialization and growth, and fracture toughness of cortical bone microstructure. The experimental results highly agreed with the prediction by the proposed model in sense that (1) curly, serrated, grainy and powdery chips were formed when the cutting angle was set as 0°, 60°, 90°, and 120°, respectively. (2) Bone materials were removed dominantly by shearing at a small depth of cut from 10 to 50 µm, and by a mixture of pealing, shearing, and bending at a large depth of cut over 100 µm at different cutting orientations. Moreover, it was found that a cutting path along the direction of crack initialization and propagation benefited to suppress the fluctuation of cutting force thus reduce the vibration. The presented model has theoretical and practical significance in optimizing cutting tools and operational parameters in surgeries.

Predictive Modeling and Optimization of Cutting Forces Through RSM and Taguchi Techniques in the Turning of ASTM B574 (Hastelloy C-22)

2018 ◽  
pp. 398-417
Author(s):  
İsmail Kırbaş ◽  
Musa Peker ◽  
Gültekin Basmacı ◽  
Mustafa Ay
Keyword(s):  
Feed Rate ◽  
Cutting Forces ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Rake Angle ◽  
Orthogonal Experimental Design ◽  
Depth Of Cut ◽  
Effective Parameters ◽  
Factors Affecting ◽  
The Impact

In this chapter, the impact of cutting parameters (depth of cut, cutting speed, feed, flow, rake angle, lead angle) on cutting forces in the turning process with regard to ASTM B574 (Hastelloy C-22) material has been investigated. Variance analysis has been applied in order to determine the factors affecting the cutting forces. The optimization of the parameters affecting the surface roughness has been obtained using response surface methodology (RSM) based on the Taguchi orthogonal experimental design. The accuracy of the developed models required for the estimation of the force values (Fx, Fy, Fz) is quite successful. In this study, where the R2 value has been used as the criterion/measure, accuracy values of 93.35%, 95.03%, and 95.09% have been achieved for Fx, Fy, and Fz, respectively. As a result of the ANOVA analysis, the most effective parameters for Fx at a 95% confidence interval are depth of cut, feed rate, flow, and rake angle. The most effective parameter for Fy is depth of cut, while the most effective parameters for Fz are depth of cut, feed rate, and flow, respectively.

scholarly journals Research and Optimization of Surface Roughness in Milling of SLM Semi-Finished Parts Manufactured by Using the Different Laser Scanning Speed

Materials ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 9 ◽  
Author(s):  
Andrzej Matras
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Laser Scanning ◽  
Cutting Tool ◽  
Scanning Speed ◽  
Milling Process ◽  
Face Milling ◽  
Machining Parameters ◽  
The Face ◽  
Laser Scanning Speed

The paper studies the potential to improve the surface roughness in parts manufactured in the Selective Laser Melting (SLM) process by using additional milling. The studied process was machining of samples made of the AlSi10Mg alloy powder. The simultaneous impacts of the laser scanning speed of the SLM process and the machining parameters of the milling process (such as the feed rate and milling width) on the surface roughness were analyzed. A mathematical model was created as a basis for optimizing the parameters of the studied processes and for selecting the sets of optimum solutions. As a result of the research, surface with low roughness (Ra = 0.14 μm, Rz = 1.1 μm) was obtained after the face milling. The performed milling allowed to reduce more than 20-fold the roughness of the SLM sample surfaces. The feed rate and the cutting width increase resulted in the surface roughness deterioration. Some milled surfaces were damaged by the chip adjoining to the rake face of the cutting tool back tooth.

A Study on Edge Milling Operation of NEMA G11 GFRP Composites Based on Grey-Taguchi Method

2014 ◽  
Vol 592-594 ◽  
pp. 18-22
Author(s):  
Hari Vasudevan ◽  
Ramesh Rajguru ◽  
Naresh Deshpande
Keyword(s):  
Taguchi Method ◽  
Feed Rate ◽  
Spindle Speed ◽  
Performance Characteristics ◽  
Depth Of Cut ◽  
Machining Processes ◽  
Milling Parameters ◽  
Response Table ◽  
Milling Operation ◽  
Grey Relational

Milling is one of the most practical machining processes for removing excess material to produce high quality surfaces. However, milling of composite materials is a rather complex task, owing to its heterogeneity and poor surface finish, which includes fibre pullout, matrix delamination, sub-surface damage and matrix polymer interface failure. In this study, an attempt has been made to optimize milling parameters with multiple performance characteristics in the edge milling operation, based on the Grey Relational Analysis coupled with Taguchi method. Taguchi’s L18 orthogonal array was used for the milling experiment. Milling parameters such as milling strategy, spindle speed, feed rate and depth of cut are optimised along with multiple performance characteristics, such as machining forces and delamination. Response table of grey relational grade for four process parameters is used for the analysis to produce the best output; the optimal combination of the parameters. From the response table of the average GRG, it is found that the largest value of the GRG is for down milling, spindle speed of 1000 rpm, feed rate of 150 mm/min and depth of cut 0.4 mm.

An Investigation of Optimum Cutting Conditions in Face Milling Mold Steel Affect the Surface Roughness and Tool Wear

2014 ◽  
Vol 931-932 ◽  
pp. 354-359 ◽  
Author(s):  
Surasit Rawangwong ◽  
Worapong Boonchouytan ◽  
Jaknarin Chatthong ◽  
Romadorn Burapa
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Tool ◽  
Fatigue Cracking ◽  
Face Milling ◽  
Percentage Error ◽  
Depth Of Cut ◽  
Carbide Tool ◽  
Margin Of Error ◽  
Percent Accuracy

The purpose of this research was to investigate the effect of the main factors on the surface roughness in mold steels face milling by carbide tool for results obtained from the analysis used in the manufacture of molds and other parts of the industry. The etching experiment using semi-automated milling machine Obraeci Strojie brand FGV 32 model. Concerning the material was steel grade AISI P20 mold with a hardness between 280-325 HB which used to insert carbide tool. The factors of a speed, feed rate and depth of cut were study. Preliminary experiments showed that the depth does not affect the surface roughness fix depth of cut at 0.5 mm. The experimental revealed that the factor affecting surface roughness was feed rate and speed. The roughness value trenced to reduce at lower feed rate and greater speed. It was possible determine a facing condition by means of the equation Ra = 1.29 - 0.000654Speed + 0.00305Feed rate leading this equation goes to use is in limitation speed 500-1,000 rpm. at feed rate 160-315 mm/min. From the experiment was confirming the result of a comparison between the equation and the percent accuracy with the margin of error. The result from the experiment of mean absolute percentage error (MAPE) of the equation of surface roughness was 3.27% which was less than the margin of error and was acceptable. The pattern of wear was similar to mechanical fatigue cracking. It may be due to the verious tip of the cutting tool or an impact and flank wear as cutting tool materials resistant to wear less.

scholarly journals Investigate the Effect of Cutting Parameters on Surface Roughness When Milling X12m Steel

2021 ◽  
pp. 258-263
Author(s):  
Do Thi Kim Lien ◽  
Nguyen Dinh Man ◽  
Phung Tran Dinh
Keyword(s):  
Experimental Study ◽  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Tool ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Face Milling ◽  
Negligible Effect ◽  
Depth Of Cut ◽  
The Relationship

In this paper, an experimental study on the effect of cutting parameters on surface roughness was conducted when milling X12M steel. The cutting tool used in this study is a face milling cutter. The material that is used to make the insert is the hard alloy T15K6. The cutting parameters covered in this study include the cutting speed, the feed rate and depth of cut. The experiments are performed in the form of a rotating center composite design. The analysis shows that for both Ra and Rz: (1) the feed rate has the greatest influence on the surface roughness while the depth of cut, the cutting speed has a negligible effect on the surface roughness. (2) only the interaction between the feed rate and the depth of the cut has a significant effect on both Ra and Rz while the interaction between the cutting speed and the feed rate, the interaction between the cutting speed and the depth of cut have a negligible effect on surface roughness. A regression equation showing the relationship between Ra, Rz, and cutting parameters has also been built in this study.

scholarly journals Analysis of tool wear and surface roughness in high-speed milling process of aluminum alloy Al6061

2021 ◽  
pp. 71-84
Author(s):  
Nhu-Tung Nguyen ◽  
Dung Hoang Tien ◽  
Nguyen Tien Tung ◽  
Nguyen Duc Luan
Keyword(s):  
Surface Roughness ◽  
Aluminum Alloy ◽  
Tool Wear ◽  
Feed Rate ◽  
High Speed ◽  
Cutting Speed ◽  
Milling Process ◽  
Face Milling ◽  
Depth Of Cut ◽  
High Speed Milling

In this study, the influence of cutting parameters and machining time on the tool wear and surface roughness was investigated in high-speed milling process of Al6061 using face carbide inserts. Taguchi experimental matrix (L9) was chosen to design and conduct the experimental research with three input parameters (feed rate, cutting speed, and axial depth of cut). Tool wear (VB) and surface roughness (Ra) after different machining strokes (after 10, 30, and 50 machining strokes) were selected as the output parameters. In almost cases of high-speed face milling process, the most significant factor that influenced on the tool wear was cutting speed (84.94 % after 10 machining strokes, 52.13 % after 30 machining strokes, and 68.58 % after 50 machining strokes), and the most significant factors that influenced on the surface roughness were depth of cut and feed rate (70.54 % after 10 machining strokes, 43.28 % after 30 machining strokes, and 30.97 % after 50 machining strokes for depth of cut. And 22.01 % after 10 machining strokes, 44.39 % after 30 machining strokes, and 66.58 % after 50 machining strokes for feed rate). Linear regression was the most suitable regression of VB and Ra with the determination coefficients (R2) from 88.00 % to 91.99 % for VB, and from 90.24 % to 96.84 % for Ra. These regression models were successfully verified by comparison between predicted and measured results of VB and Ra. Besides, the relationship of VB, Ra, and different machining strokes was also investigated and evaluated. Tool wear, surface roughness models, and their relationship that were found in this study can be used to improve the surface quality and reduce the tool wear in the high-speed face milling of aluminum alloy Al6061

scholarly journals Multi-Objective Process Parameter Optimization for Surface Roughness and Material Removal Rate in Face Milling of Al 6061 T6 Alloy

2019 ◽  
Vol 9 (2) ◽  
pp. 137-142
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Face Milling ◽  
Machining Process ◽  
Depth Of Cut ◽  
Al 6061

This study uses Taguchi methodology and Gray Relational Analysis approach to explore the optimization of face milling process parameters for Al 6061 T6 alloy.Surface Roughness (Ra), Material Removal Rate (MRR) has been identified as the objective of performance and productivity.The tests were performed by selecting cutting speed (mm / min), feed rate (mm / rev) and cutting depth (mm) at three settings on the basis of Taguchi's L9 orthogonal series.The grey relational approach was being used to establish a multiobjective relationship between both the parameters of machining and the characteristics of results. To find the optimum values of parameters in the milling operation, the response list and plots are used and found to be Vc2-f1-d3. To order to justify the optimum results, the confirmation tests are performed.The machining process parameters for milling were thus optimized in this research to achieve the combined goals such as low surface roughness and high material removal rate on Aluminum 6061 t6.It was concluded that depth of cut is the most influencing parameter followed by feed rate and cutting velocity.

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