Investigation on Drilling Performance of Titanium Alloy Ti6Al4V Based on Response Surface Method

2017 ◽  
Author(s):  
Zhaoju Zhu ◽  
Shaochun Sui ◽  
Jie Sun ◽  
Jianfeng Li ◽  
Kai Liu
Keyword(s):  
Surface Roughness ◽  
Response Surface ◽  
Response Surface Method ◽  
Feed Rate ◽  
Thrust Force ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Drilling Performance ◽  
Surface Method ◽  
Low Efficiency

In order to break the bottleneck of low efficiency, bad quality following drilling alloy Ti6Al4V, the effect of cutting parameters on thrust force, drilling vibration, burr height and surface roughness was studied based on response surface method. The optimized parameters were obtained. Results showed that feed rate had significant effect on thrust force and little on drilling vibration, while cutting speed had significant effect on vibration and little on thrust force. It is also observed that surface roughness decreased with cutting speed increasing, as well as increased with feed rate increasing. In addition, microstructure on the drilled hole surface showed mobility along feeding direction. Grain refinement on the drilling hole surface became serious with the increase of cutting speed and feed rate.

Prediction Modelling of Surface Roughness for Laser Beam Cutting on Acrylic Sheets

2009 ◽  
Vol 83-86 ◽  
pp. 793-800 ◽  
Author(s):  
M.M. Noor ◽  
K. Kadirgama ◽  
M.M. Rahman ◽  
N.M. Zuki N.M. ◽  
Mohd Ruzaimi Mat Rejab ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Laser Beam ◽  
Response Surface ◽  
Response Surface Method ◽  
Laser Cutting ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Power Requirement ◽  
Box Behnken Design ◽  
Surface Method

This paper develops the predicting model on surface roughness of laser beam cutting (LBC) for acrylic sheets. Box-Behnken design based on Response surface method was used to predict the effect of laser cutting parameters including the power requirement, cutting speed and tip distance on surface roughness during the machining. Response surface method (RSM) was used to minimize the number of experiments. It can be seen that from the experimental results, the effects of the laser cutting parameters with the surface roughness were investigated. It was found that the surface roughness is significantly affected by the tip distance followed by the power requirement and cutting speed. Some defects were found in microstructure such as burning, melting and wavy surface. This simulation gain more understanding of the surface roughness distribution in laser cutting. The developed model is suitable to be used in the range of (power 90 to 95, cutting speed 700 to 1100 and tip distance 3 to 9) to predict surface roughness.

scholarly journals Surface Roughness Optimization in Drilling Process Using Response Surface Method (RSM)

2014 ◽  
Vol 66 (3) ◽  
Author(s):  
Mohd Amran ◽  
Siti Salmah ◽  
Mohd Sanusi ◽  
Mohd Yuhazri ◽  
Noraiham Mohamad ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Surface Roughness ◽  
Response Surface ◽  
Response Surface Method ◽  
Feed Rate ◽  
Spindle Speed ◽  
Drilling Process ◽  
Surface Method ◽  
Drilling Parameters ◽  
Drill Diameter

This paper presents the effect of drilling parameters on surface roughness and surface appearance by applying response surface method (RSM). The mathematical model for correlating the interactions of drilling parameters such as spindle speed, feed rate and drill diameter on surface roughness was developed. RSM methodology was used as it is a technique that most practical and effective way to develop a mathematical model. In addition, this method also can reduce trial and error in experiment. Since the number of factors are three; spindle speed, feed rate and drill diameter, by applying RSM the total numbers of experiment involved are 20 experimental observations. From the experimental result, it is found that the minimum surface roughness on the hole was 1.06 mm from combination of 2000 rpm spindle speed, 78 mm/min feed rate and 2.5 mm drill diameter. While the maximum surface roughness 2.59 mm was the combination of 250 rpm spindle speed, 153 mm/min feed rate and 3.5 mm drill diameter. A mathematical equation was developed with percentage of error are 0% to 29%. Thus, from the result we understand that to find the smooth surface in drilling process, it needs higher spindle speed with lower feed rate and smaller diameter.

scholarly journals Prediction of Surface Roughness and Optimization of Cutting Parameters of Stainless Steel Turning Based on RSM

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Maohua Xiao ◽  
Xiaojie Shen ◽  
You Ma ◽  
Fei Yang ◽  
Nong Gao ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Response Surface ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Cutting Depth ◽  
Surface Design ◽  
Composite Surface ◽  
Optimization Of Cutting Parameters

The turning test of stainless steel was carried out by using the central composite surface design of response surface method (RSM) and Taguchi design method of central combination design. The influence of cutting parameters (cutting speed, feed rate, and cutting depth) on the surface roughness was analyzed. The surface roughness prediction model was established based on the second-order RSM. According to the test results, the regression coefficient was estimated by the least square method, and the regression equation was curve fitted. Meanwhile, the significance analysis was conducted to test the fitting degree and response surface design and analysis, in addition to establishing a response surface map and three-dimensional surface map. The life of the machining tool was analyzed based on the optimized parameters. The results show that the influence of feed rate on the surface roughness is very significant. Cutting depth is the second, and the influence of cutting speed is the least. Therefore, the cutting parameters are optimized and tool life is analyzed to realize the efficient and economical cutting of difficult-to-process materials under the premise of ensuring the processing quality.

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.

Optimization and Prediction of Machining Responses Using Response Surface Methodology and Adaptive Neural Network by Wire Electric Discharge Machining of Alloy-X

2021 ◽  
Vol 1026 ◽  
pp. 28-38
Author(s):  
I. Vishal Manoj ◽  
S. Narendranath ◽  
Alokesh Pramanik
Keyword(s):  
Neural Network ◽  
Surface Roughness ◽  
Artificial Neural Network ◽  
Response Surface ◽  
Electric Discharge ◽  
Cutting Speed ◽  
Electric Discharge Machining ◽  
Surface Method ◽  
Wire Electric Discharge Machining ◽  
Pulse On Time

Wire electric discharge machining non-contact machining process based on spark erosion technique. It can machine difficult-to-cut materials with excellent precision. In this paper Alloy-X, a nickel-based superalloy was machined at different machining parameters. Input parameters like pulse on time, pulse off time, servo voltage and wire feed were employed for the machining. Response parameters like cutting speed and surface roughness were analyzed from the L25 orthogonal experiments. It was noted that the pulse on time and servo voltage were the most influential parameters. Both cutting speed and surface roughness increased on increase in pulse on time and decrease in servo voltage. Grey relation analysis was performed to get the optimal parametric setting. Response surface method and artificial neural network predictors were used in the prediction of cutting speed and surface roughness. It was found that among the two predictors artificial neural network was accurate than response surface method.

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 Influence of process parameters on surface roughness and forming time of Al-1100 sheet in incremental sheet metal forming

2019 ◽  
Vol 13 (2) ◽  
pp. 4911-4927
Author(s):  
Swagatika Mohanty ◽  
Srinivasa Prakash Regalla ◽  
Yendluri Venkata Daseswara Rao
Keyword(s):  
Surface Roughness ◽  
Response Surface ◽  
Sheet Metal ◽  
Process Parameters ◽  
Sheet Metal Forming ◽  
Feed Rate ◽  
Metal Forming ◽  
Wall Angle ◽  
Surface Method ◽  
Incremental Sheet Metal Forming

Product quality and production time are critical constraints in sheet metal forming. These are normally measured in terms of surface roughness and forming time, respectively. Incremental sheet metal forming is considered as most suitable for small batch production specifically because it is a die-less manufacturing process and needs only a simple generic fixture. The surface roughness and forming time depend on several process parameters, among which the wall angle, step depth, feed rate, sheet thickness, and spindle speed have a greater impact on forming time and surface roughness. In the present work, the effect of step depth, feed rate and wall angle on the surface roughness and forming time have been investigated for constant 1.2 mm thick Al-1100 sheet and at a constant spindle speed of 1300 rpm. Since the variable effects of these parameters necessitate multi-objective optimization, the Taguchi L9 orthogonal array has been used to plan the experiments and the significance of parameters and their interactions have been determined using analysis of variance (ANOVA) technique. The optimum response has been brought out using response surfaces. Finally, the findings of response surface method have been validated by conducting additional experiments at the intermediate values of the parameters and these results were found to be in agreement with the predictions of Taguchi method and response surface method.

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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