scholarly journals Effect of Cutting Speed on Surface Roughness: Face Milling of Steel with a Parallelogram Insert

2019 ◽  
Author(s):  
Antal Nagy ◽  
Janos Kundrak
Keyword(s):  
Surface Roughness ◽  
Cutting Speed ◽  
Face Milling

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

Experimental Study on the Relationship between Surface Roughness and Cutting Parameters when Face Milling High Strength Steel

2010 ◽  
Vol 139-141 ◽  
pp. 782-787
Author(s):  
Yue Ding ◽  
Wei Liu ◽  
Xi Bin Wang ◽  
Li Jing Xie ◽  
Jun Han
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
High Strength Steel ◽  
Cutting Speed ◽  
High Strength ◽  
Face Milling ◽  
Depth Of Cut ◽  
Radial Depth ◽  
The Relationship ◽  
Axial Depth

In this study, surface roughness generated by face milling of 38CrSi high-strength steel is discussed. Experiments based on 24 factorial design and Box-Behnken design method are conducted to investigate the effects of milling parameters (cutting speed, axial depth of cut and radial depth of cut and feed rate) on surface roughness, and a second-order model of surface roughness is established by using surface response methodology (RSM); Significance tests of the model are carried out by the analysis of variance (ANOVA). The results show that the most important cutting parameter is feed rate, followed by radial depth of cut, cutting speed and axial depth of cut. Moreover, it is verified that the predictive model possesses highly significance by the variance examination at a level of confidence of 99%. And the relationship between surface roughness and the important interaction terms is nonlinear.

Effects of Technological Parameters on Surface Characteristics in Face Milling

2017 ◽  
Vol 261 ◽  
pp. 285-292 ◽  
Author(s):  
Gyula Varga ◽  
János Kundrák
Keyword(s):  
Surface Roughness ◽  
Cutting Speed ◽  
Surface Characteristics ◽  
Face Milling ◽  
Roughness Parameters ◽  
Technological Parameters ◽  
3D Surface Roughness ◽  
High Level ◽  
2D And 3D ◽  
Further Development

The experimental and theoretic examination of conventional manufacturing procedures continue to be a topic of modern research. It is assisted, to a great extent, by the spread and the possibility of the application of high level software and more accurate measuring equipment. The research results obtained by the use of new equipment can open new ways for further development of conventional manufacturing procedures and their more intensive, more productive application. In this paper, an experimental method is used for examination of the surface features (e.g. flatness, 2D and 3D surface roughness parameters) of face milled aluminium parts. The aim of experiments was to determine the effect of change of the technological parameters (feed rate and cutting speed) on flatness and surface roughness features in of face milling of aluminium parts.

scholarly journals PENENTUAN KECEPATAN PEMOTONGAN EFEKTIF BERDASARKAN NILAI KEKASARAN PERMUKAAN MATERIAL AA-7075 PADA PROSES FACE MILLING

POROS ◽  
2021 ◽  
Vol 17 (1) ◽  
pp. 51
Author(s):  
Sobron Y. Lubis ◽  
Rosehan Rosehan ◽  
Musa Law
Keyword(s):  
Surface Roughness ◽  
Surface Quality ◽  
Feed Rate ◽  
Tooth Development ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Face Milling ◽  
Machining Parameters ◽  
Aa 7075 ◽  
Aluminum Alloy 7075

During face milling machining, several machining parameters such as feed rate and cuttingspeed determine the surface quality of the workpiece produced by the process. The selection of the rightparameters will lead to the surface quality as planned. Therefore, to improve machining effectiveness, amethod is needed to determine the appropriate machining parameters to produce the desired surfacequality. This research was conducted using a milling machine, five variations of cutting speed and fivevariations of feed rate were used to cut the workpiece aluminum alloy 7075. After machining, the surfaceroughness was measured using a surface test. The surface roughness value is then substituted into thefeed rate equation and effective cutting speed. By finding effective cutting parameters, the machiningprocess will be more efficient and effective without using unnecessary resources. From the results of thestudy note that the development equation to determine the feed rate based on the value of surfaceroughness is ???? = 0,6????√???? ????????0.443mm/tooth. Development equation to determine the effective cutting speedbased on Surface roughness value is ???????? = 3.0686????????0.124 mm/min

Experimental study on the chip morphology, tool–chip contact length, workpiece vibration, and surface roughness during high-speed face milling of A6061 aluminum alloy

2019 ◽  
Vol 234 (3) ◽  
pp. 610-620 ◽  
Author(s):  
Thi-Hoa Pham ◽  
Duc-Toan Nguyen ◽  
Tien-Long Banh ◽  
Van-Canh Tong
Keyword(s):  
Surface Roughness ◽  
Aluminum Alloy ◽  
Feed Rate ◽  
High Speed ◽  
Cutting Speed ◽  
Chip Morphology ◽  
Contact Length ◽  
Face Milling ◽  
Cutting Conditions ◽  
Workpiece Vibration

In this study, experiments of high-speed face milling of A6061 aluminum alloy with a carbide insert milling cutter under dry cutting conditions were conducted. The contact length between tool and chip, the workpiece vibration amplitude, and the arithmetic average surface roughness were measured under varying cutting conditions (cutting speed, feed rate, and depth of cut). The characteristics of chip morphology were observed using scanning electron microscope. Experimental results showed that the increasing cutting speed reduced the tool–chip contact length, the workpiece vibration, and the surface roughness. The tool–chip contact length, the workpiece vibration, and the surface roughness were all increased with increasing cutting depth and feed rate. The results of chip morphology showed that the chips with serrated form were generated under high-speed cutting conditions. Moreover, scratch lines, plastic deformation cavities, and local molten chip material were observed on the slide chip surface.

Experimental Study on Face Milling Austenitic Stainless Steel

2012 ◽  
Vol 723 ◽  
pp. 35-40 ◽  
Author(s):  
Han Lian Liu ◽  
Qing Ge Zhang ◽  
Chuan Zhen Huang ◽  
Bin Zou ◽  
Hong Tao Zhu
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Austenitic Stainless Steel ◽  
Removal Rate ◽  
Cutting Speed ◽  
Main Tool ◽  
Face Milling ◽  
Machining Parameters ◽  
Milling Force ◽  
Four Levels

Based on the characteristics of austenitic stainless steel 1Cr18Ni9Ti, aiming to decrease surface roughness and milling force orthogonal face milling experiment with four factors and four levels was designed to optimize machining parameters with consideration of material removal rate. Three relatively excellent machining parameters were taken to further figure out the influences of cutting speed on tool life, and the tool wear mechanism was also analyzed. The results indicated that both surface roughness and milling force were greatly influenced by cutting speed and feed. The best machining parameters obtained in the experiments were v: 200m/min, fz: 0.1mm/z, ap: 0.9mm, ae: 35mm. The main tool failure mode under this circumstance was tool chipping at the flank between main cutting edge and surface to be processed, besides, the wear of rake face was relatively slight.

The Study of Proper Conditions in Face Milling Palmyra Palm Wood and Coconut Wood Using Design of Experiment

2012 ◽  
Vol 488-489 ◽  
pp. 847-855
Author(s):  
S. Rawangwong ◽  
J. Chatthong ◽  
J. Rodjananugoon ◽  
W. Boonchouytan ◽  
R. Burapa
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Speed ◽  
Face Milling ◽  
Mean Absolute Percentage Error ◽  
Percentage Error ◽  
Depth Of Cut ◽  
Absolute Percentage Error ◽  
Margin Of Error ◽  
Main Factors

The purpose of this research was to investigate the effects of main factors on the surface roughness in face milling process palmyra palm wood and coconut wood by computer numerical controlled milling machine and using shell end mill cutting tools 6 edges. The main factors including speed, feed rate, depth of cut and angle of cut were investigated for the optimum surface roughness. The result of preliminary trial showed that the depth of cut and the angle of the cut had no effect on surface roughness. It was found from the experiment that the factors affecting surface roughness were feed and speed, with tendency for reduction of roughness value at a lower feed rate and greater cutting speed. Therefore, in the facing process for palmyra palm wood it was possible to determine a face milling condition by means of the equation Ra = 0.954 + 20.4 Feed + 0.00126 Speed. This equation was employed at a limited speed of 800-1200 rpm, and the feed rate of 0.03-0.05 mm/tooth. The result from the experiment of the mean absolute percentage error of the equation of surface roughness is 6.10% which is less than the margin of error, and is acceptable. For coconut wood it was found from the experiment that the factor affecting surface roughness was feed rate and cutting speed, with tendency for reduction of roughness value at lower feed rate and greater cutting speed. Therefore, in the face milling coconut wood it was possible determine a facing condition by means of the equation Ra = 4.72 - 0.000864 Speed + 0.00443 Feed. Leading this equation goes to use is in limitation cutting speed 1000-2000 rpm at feed rate 100-300 mm/min. The result from the experiment of mean absolute percentage error of the equation of surface roughness is 4.64% which is less than the margin of error, and is acceptable. As a result, the selection of optimal machining parameters can be greatly benefited to the Coconut wood furniture manufacturing industry in terms of productivity improvement.

Effects of Process Parameters on Surface Roughness and MRR in the hard turning of EN 36 steel

2018 ◽  
pp. 102-110
Author(s):  
Amritpal Singh ◽  
Rakesh Kumar
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
Hard Turning ◽  
Control Parameter ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Dry Cutting

In the present study, Experimental investigation of the effects of various cutting parameters on the response parameters in the hard turning of EN36 steel under the dry cutting condition is done. The input control parameters selected for the present work was the cutting speed, feed and depth of cut. The objective of the present work is to minimize the surface roughness to obtain better surface finish and maximization of material removal rate for better productivity. The design of experiments was done with the help of Taguchi L9 orthogonal array. Analysis of variance (ANOVA) was used to find out the significance of the input parameters on the response parameters. Percentage contribution for each control parameter was calculated using ANOVA with 95 % confidence value. From results, it was observed that feed is the most significant factor for surface roughness and the depth of cut is the most significant control parameter for Material removal rate.

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