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.

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.

The Influence of Cutting Parameters of Turning Process on the Oil Palm Wood Using Carbide Tool

2013 ◽  
Vol 415 ◽  
pp. 666-671
Author(s):  
Surasit Rawangwong ◽  
Jaknarin Chatthong ◽  
Worapong Boonchouytan
Keyword(s):  
Surface Roughness ◽  
Oil Palm ◽  
Feed Rate ◽  
Cutting Speed ◽  
Experimental Result ◽  
Percentage Error ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Turning Process ◽  
Main Factors

This research study aimed to investigate the effect of main factors on the surface roughness in oil palm wood turning process for manufacturing furniture parts using carbide tools. The main factors, namely, cutting speed, feed rate and depth of cut were investigated for the optimum surface roughness in furniture manufacturing process. The result of preliminary trial shown that the depth of cut had no effect on surface roughness. Moreover, the experiment was found that the factors affecting a surface roughness were cutting speed and feed rate, with having tendency for reduction of roughness value at lower feed rate and greater cutting speed, Therefore in the turning process of oil palm wood, it was possible to determine a cutting condition by means of the equation Ra = 19.8-0.00742 Cutting Speed+3.98 Feed rate, This equation can be best used with limitation of cutting speed at 122-450 m/min, feed rate at 0.1-0.5 mm/rev and depth of cut does not over 1 mm,. To confirm the experiment result, a comparison between the equation value and an actual value by estimating a prediction error value was calculate with the surface roughness and margin of error does not over 10%. The experimental result reveals the mean absolute percentage error (MAPE) of the equation of surface roughness is 3.24%, which is less than the predicted error value and it is acceptable.

An Investigation of Optimum Cutting Conditions in Face Milling Semi-Solid Cast 6061 Aluminum Alloy Using Carbide Tool

2013 ◽  
Vol 747 ◽  
pp. 777-780 ◽  
Author(s):  
S. Rawangwong ◽  
Worapong Boonchouytan ◽  
J. Chatthong ◽  
R. Burapa
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Face Milling ◽  
Percentage Error ◽  
Depth Of Cut ◽  
Milling Machine ◽  
Optimum Cutting ◽  
The Mean ◽  
Main Factors ◽  
Semi Solid

The purpose of this research was to investigate the effect of the main factors of the surface roughness in semi-solid 6061 aluminum face milling. This study was conducted by using computer numerical controlled milling machine. The controlled factors were the speed, the feed rate and the depth of cut which the depth of cut was not over 1 mm. For this experiment, we used factorial designs and the result showed that the factors effected of surface roughness was the feed rate and the speed while the depth of cut did not effect with the surface roughness. Furthermore, the surface roughness was likely to reduce when the speed was 4,200 rpm and the feed rates was 1,300 mm/min. The result of the research led to the linear equation measurement value which was Ra = 0.186 - 0.000034 Speed + 0.000047 Feed rate. The equation formula should be used with the speed in the range of 3,200-4,200 rpm, feed rate in the range of 1,300-1,800 mm/min and the depth of cut not over 1 mm. The equation was used to confirm the research results, it was found that the mean absolute percentage error of the surface roughness obtained from the predictive comparing to the value of the experiment was 4.12%, which was less than the specified error and it was acceptable.

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 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

Characterisation, Performance and Optimisation of Nanocellulose Metalworking Fluid (MWF) for Green Machining Process

2021 ◽  
Vol 18 (4) ◽  
pp. 9188-9207
Author(s):  
Mahendran Samykano ◽  
J. Kananathan ◽  
K. Kadirgama ◽  
A. K. Amirruddin ◽  
D. Ramasamy ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Surface Roughness ◽  
Tool Wear ◽  
Feed Rate ◽  
Cutting Speed ◽  
Machining Process ◽  
Alumina Nanoparticles ◽  
Working Fluid ◽  
Depth Of Cut ◽  
Nanoparticle Concentration

The present research attempts to develop a hybrid coolant by mixing alumina nanoparticles with cellulose nanocrystal (CNC) into ethylene glycol-water (60:40) and investigate the viability of formulated hybrid nanocoolant (CNC-Al2O3-EG-Water) towards enhancing the machining behavior. The two-step method has been adapted to develop the hybrid nanocoolant at various volume concentrations (0.1, 0.5, and 0.9%). Results indicated a significant enhancement in thermal properties and tribological behaviour of the developed hybrid coolant. The thermal conductivity improved by 20-25% compared to the metal working fluid (MWF) with thermal conductivity of 0.55 W/m℃. Besides, a reduction in wear and friction coefficient was observed with the escalation in the nanoparticle concentration. The machining performance of the developed hybrid coolant was evaluated using Minimum Quantity Lubrication (MQL) in the turning of mild steel. A regression model was developed to assess the deviations in the tool flank wear and surface roughness in terms of feed, cutting speed, depth of the cut, and nanoparticle concentration using Response Surface Methodology (RSM). The mathematical modeling shows that cutting speed has the most significant impact on surface roughness and tool wear, followed by feed rate. The depth of cut does not affect surface roughness or tool wear. Surface roughness achieved 24% reduction, 39% enhancement in tool length of cut, and 33.33% improvement in tool life span. From this, the surface roughness was primarily affected by spindle cutting speed, feed rate, and then cutting depth while utilising either conventional water or composite nanofluid as a coolant. The developed hybrid coolant manifestly improved the machining behaviour.

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.

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