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.

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.

scholarly journals Prediction of cutting tool vibration and surface roughness in hard turning of AISI52100 steel

2018 ◽  
Vol 211 ◽  
pp. 03011
Author(s):  
Nitin Ambhore ◽  
Dinesh Kamble ◽  
Satish Chinchanikar
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Vibration Amplitude ◽  
Cutting Tool ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Vibration Signals ◽  
Cutting Parameter ◽  
Acceleration Amplitude

The changing behavior of vibration signals with varying cutting parameters (cutting speed, feed rate and depth of cut) for turning hardened AISI52100 steel has been studied and reported. The vibration response of cutting tool in all three mutually perpendicular directions, namely, in feed Vx, radial Vy and, tangential Vz directions have been captured by mounting piezoelectric tri-axial accelerometer close to the cutting tool. Experiments are planned and conducted as per Central composite rotatable design of Surface response methodology. The second order multiple regression models are developed to correlate cutting parameters with vibration acceleration and surface roughness. The coefficient of regression R2 for all models is found close to 0.92 which shows that the developed models are reliable and provide an excellent explanation between the cutting parameter and the vibration of cutting tool within limits. The analysis of the results revealed that cutting conditions are having prominent and mixed type effect on vibration signals. The acceleration amplitude Vx, Vy and Vz increases with increase in cutting speed, and depth of cut. The vibration amplitude Vx, Vy and Vz initially increases as feed increases and, with further increase in feed, the vibration amplitude decreases. The surface roughness is highly influenced by the feed rate followed by cutting speed whereas the depth of cut was found less significant. The fluctuation in frequency is observed in all directions. However, the band of frequency remains within a certain range. Within selected cutting parameter range, the maximum acceleration amplitude is observed in frequency band of 4 kHz - 16 kHz.

scholarly journals A Survey on the Effects of Cutting Parameters on Surface Roughness When Milling 40Cr Steel Using End Mill Cutter

2020 ◽  
Vol 5 (1) ◽  
pp. 33-36
Author(s):  
Nguyen Hong Son
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Regression Equations ◽  
Face Mill ◽  
Mill Cutter ◽  
The Relationship ◽  
40Cr Steel

In this paper, the empirical research on the effects of cutting parameters on surface roughness when milling 40Cr steel with face mill is conducted. The cutting parameters in this study include the cutting speed, feed rate and depth of cut. The tests are conducted in the form of Central Composite Design. The analysis shows that, for both Ra and Rz: (1) the feed rate has the greatest effect on surface roughness, followed by the degree of influence of the depth of cut, cutting speed with insignificant effects on surface roughness. (2) only the interaction between the feed rate and depth of cut have a significant effect on both Ra and Rz; the interaction between the cutting speed and feed rate, the interaction between the cutting speed and depth of cut have negligible effects on the surface roughness. In addition, the regression equations showing the relationship between Ra, Rz and cutting parameters is developed in this study.

Effects of Insert Nose Radius and Processing Cutting Parameter on the Surface Roughness of Aisi 316 Stainless Steel

2010 ◽  
Vol 447-448 ◽  
pp. 51-54
Author(s):  
Mohd Fazuri Abdullah ◽  
Muhammad Ilman Hakimi Chua Abdullah ◽  
Abu Bakar Sulong ◽  
Jaharah A. Ghani
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Surface Finish ◽  
Feed Rate ◽  
Cutting Speed ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Aisi 316

The effects of different cutting parameters, insert nose radius, cutting speed and feed rates on the surface quality of the stainless steel to be use in medical application. Stainless steel AISI 316 had been machined with three different nose radiuses (0.4 mm 0.8 mm, and 1.2mm), three different cutting speeds (100, 130, 170 m/min) and feed rates (0.1, 0.125, 0.16 mm/rev) while depth of cut keep constant at (0.4 mm). It is seen that the insert nose radius, feed rates, and cutting speed have different effect on the surface roughness. The minimum average surface roughness (0.225µm) has been measured using the nose radius insert (1.2 mm) at lowest feed rate (0.1 mm/rev). The highest surface roughness (1.838µm) has been measured with nose radius insert (0.4 mm) at highest feed rate (0.16 mm/rev). The analysis of ANOVA showed the cutting speed is not dominant in processing for the fine surface finish compared with feed rate and nose radius. Conclusion, surface roughness is decreasing with decreasing of the feed rate. High nose radius produce better surface finish than small nose radius because of the maximum uncut chip thickness decreases with increase of nose radius.

Statistical Study and Multi-Response Optimization of Cutting Parameters for Dry Turning Stainless Steel AISI 316L Using Cermet Tool

2020 ◽  
Vol 36 ◽  
pp. 28-46
Author(s):  
Youssef Touggui ◽  
Salim Belhadi ◽  
Salah Eddine Mechraoui ◽  
Mohamed Athmane Yallese ◽  
Mustapha Temmar
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Aisi 316L ◽  
Cutting Power ◽  
Dry Turning ◽  
Optimization Of Cutting Parameters

Stainless steels have gained much attention to be an alternative solution for many manufacturing industries due to their high mechanical properties and corrosion resistance. However, owing to their high ductility, their low thermal conductivity and high tendency to work hardening, these materials are classed as materials difficult to machine. Therefore, the main aim of the study was to examine the effect of cutting parameters such as cutting speed, feed rate and depth of cut on the response parameters including surface roughness (Ra), tangential cutting force (Fz) and cutting power (Pc) during dry turning of AISI 316L using TiCN-TiN PVD cermet tool. As a methodology, the Taguchi L27 orthogonal array parameter design and response surface methodology (RSM)) have been used. Statistical analysis revealed feed rate affected for surface roughness (79.61%) and depth of cut impacted for tangential cutting force and cutting power (62.12% and 35.68%), respectively. According to optimization analysis based on desirability function (DF), cutting speed of 212.837 m/min, 0.08 mm/rev feed rate and 0.1 mm depth of cut were determined to acquire high machined part quality

scholarly journals Investigations on Surface Roughness and Tool Wear Characteristics in Micro-Turning of Ti-6Al-4V Alloy

Materials ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 2998 ◽  
Author(s):  
Kubilay Aslantas ◽  
Mohd Danish ◽  
Ahmet Hasçelik ◽  
Mozammel Mia ◽  
Munish Gupta ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Removal Rate ◽  
Cutting Speed ◽  
Small Diameter ◽  
Cutting Parameters ◽  
Ti6al4v Alloy ◽  
Depth Of Cut ◽  
Turning Process ◽  
Micro Turning

Micro-turning is a micro-mechanical cutting method used to produce small diameter cylindrical parts. Since the diameter of the part is usually small, it may be a little difficult to improve the surface quality by a second operation, such as grinding. Therefore, it is important to obtain the good surface finish in micro turning process using the ideal cutting parameters. Here, the multi-objective optimization of micro-turning process parameters such as cutting speed, feed rate and depth of cut were performed by response surface method (RSM). Two important machining indices, such as surface roughness and material removal rate, were simultaneously optimized in the micro-turning of a Ti6Al4V alloy. Further, the scanning electron microscope (SEM) analysis was done on the cutting tools. The overall results depict that the feed rate is the prominent factor that significantly affects the responses in micro-turning operation. Moreover, the SEM results confirmed that abrasion and crater wear mechanism were observed during the micro-turning of a Ti6Al4V alloy.

Optimization of Surface Roughness by Using Different Cutting Tools for Aluminum Alloy 6063

2020 ◽  
Vol 17 (2) ◽  
pp. 961-966
Author(s):  
Allina Abdullah ◽  
Afiqah Azman ◽  
B. M. Khirulrizwan
Keyword(s):  
Surface Roughness ◽  
Aluminum Alloy ◽  
Optimum Condition ◽  
Feed Rate ◽  
Optimum Parameter ◽  
Cutting Tool ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Numerical Control ◽  
Depth Of Cut

This research outlines an experimental study to determine the optimum parameter of cutting tool for the best surface roughness (Ra) of Aluminum Alloy (AA) 6063. For the experiment in this research, cutting parameters such as cutting speed, depth of cut and feed rate are used to identify the effect of both cutting tools which are tungsten carbide and cermet towards the surface roughness (Ra) of material AA6063. The machining operation involved to cut the material is turning process by using Computer Numerical Control (CNC) Lathe machine. The experimental design was designed by Full Factorial. The experiment that had been conducted by the researcher is 33 with 2 replications. The total number of the experiments that had been run is 54 runs for each cutting tool. Thus, the total number of experiments for both cutting tools is 108 runs. ANOVA analysis had been analyzed to identify the significant factor that affect the Ra result. The significant factors that affect the Ra result of AA6063 are feed rate and cutting speed. The researcher used main effect plot to determine the factor that most influenced the surface roughness of AA6063, the optimum condition of surface roughness and the optimum parameter of cutting tool. The factor that most influenced the surface roughness of AA6063 is feed rate. The optimum condition of surface roughness is at the feed rate of 0.05 mm/rev, cutting speed of 600 rpm and depth of cut of 0.10 mm. While the optimum parameter of cutting tool is cermet insert with the lowest value of surface roughness (Ra) result which is 0.650 μm.

scholarly journals Experimental Investigation on Surface Roughness and Tool Wear in Dry Machining of TiC Reinforced Aluminium LM6 Composite

2013 ◽  
Vol 773-774 ◽  
pp. 339-347 ◽  
Author(s):  
Muhammad Yusuf ◽  
M.K.A. Ariffin ◽  
N. Ismail ◽  
S. Sulaiman
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Carbide Tool ◽  
Dry Machining ◽  
Workpiece Surface ◽  
High Cutting Speed

With increasing quantities of applications of Metal Matrix Composites (MMCs), the machinablity of these materials has become important for investigation. This paper presents an investigation of surface roughness and tool wear in dry machining of aluminium LM6-TiC composite using uncoated carbide tool. The experiments carried out consisted of different cutting models based on combination of cutting speed, feed rate and depth of cut as the parameters of cutting process. The cutting models designed based on the Design of Experiment Response Surface Methodology. The objective of this research is finding the optimum cutting parameters based on workpiece surface roughness and cutting tool wear. The results indicated that the optimum workpiece surface roughness was found at high cutting speed of 250 m min-1 with various feed rate within range of 0.05 to 0.2 mm rev-1, and depth of cut within range of 0.5 to 1.5 mm. Turning operation at high cutting speed of 250 m min-1 produced faster tool wear as compared to low cutting speed of 175 m min-1 and 100 m min-1. The wear minimum (VB = 42 μm ) was found at cutting speed of 100 m min-1, feet rate of 0.2 mm rev-1, and depth of cut of 1.0 mm until the length of cut reached 4050 mm. Based on the results of the workpiece surface roughness and the tool flank wear, recommended that turning of LM6 aluminium with 2 wt % TiC composite using uncoated carbide tool should be carried out at cutting speed higher than 175 m min-1 but at feed rate of less than 0.05 mm rev-1 and depth of cut less than 1.0 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 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

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