scholarly journals Experimental Analysis on Surface Roughness in Turning Hybrid Metal Matrix (6061Al+SiC+Gr) Composites

2020 ◽  
Vol 22 (1) ◽  
pp. 341-356
Author(s):  
M. Kathirvel ◽  
K. Palani Kumar ◽  
P. M. Diaz
Keyword(s):  
Surface Roughness ◽  
Response Surface ◽  
Surface Finish ◽  
Empirical Model ◽  
Metal Matrix ◽  
Hybrid Composites ◽  
Cutting Parameters ◽  
Surface Method ◽  
Matrix Graphite ◽  
Validation Experiments

AbstractOwing to the distinguished properties Metal Matrix Graphite Hybrid Composites (Al/SiC-MMC-Gr) are used in various applications. This paper deals with the utility of Taguchi and response surface methodologies for the prediction of surface roughness in tuning of these materials with PCD tool. The cutting parameters effect on surface quality is analyzed and an empirical model with respect to turning parameters is established using response surface method. The most important parameter that influences the turning Al/SiC-MMC-Gr is feed. The measured and predicted results are approximately equal, which proves that, model is to be used for predicting surface finish in turning of these composites. Validation experiments have been used to confirm the predicted results.

Optimization of Machining Parameters on Surface Roughness in EDM of Ti-6Al-4V Using Response Surface Method

2011 ◽  
Vol 213 ◽  
pp. 402-408 ◽  
Author(s):  
M.M. Rahman ◽  
Md. Ashikur Rahman Khan ◽  
M.M. Noor ◽  
K. Kadirgama ◽  
Rosli A. Bakar
Keyword(s):  
Surface Roughness ◽  
Response Surface ◽  
Response Surface Method ◽  
Surface Finish ◽  
Machining Parameters ◽  
Surface Method ◽  
Superior Surface ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time

This paper presents the influence of EDM parameters in terms of peak ampere, pulse on time and pulse off time on surface roughness of titanium alloy (Ti-6Al-4V). A mathematical model for surface finish is developed using response surface method (RSM) and optimum machining setting in favor of surface finish are evaluated. Design of experiments (DOE) techniques is implemented. Analysis of variance (ANOVA) has been performed to verify the fit and adequacy of the developed mathematical models. The acquired results yield that the increasing pulse on time causes fine surface till a certain value and then deteriorates the surface finish. It is investigated that about 200 µs pulse off time produce superior surface finish. These results lead to desirable surface roughness and economical industrial machining by optimizing the input parameters.

scholarly journals Research and Modelling of Surface Roughness, Cutting Forces and I-kaz Coefficients for S42C in Turning using Response Surface Methodology

2019 ◽  
Vol 8 (12S2) ◽  
pp. 608-620
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Statistical Analysis ◽  
Response Surface ◽  
Cutting Parameters ◽  
Machining Process ◽  
Regression Equations ◽  
Turning Process ◽  
Machining Processes ◽  
Surface Method

This paper presents the optimization in machining processes on the cutting parameters for the S45C in turning process using the response surface method (RSM). The experimental work conducted investigates the influence of cutting parameters on statistical analysis of signals and surface quality. The paper also presents a statistical analysis of signal processing. The cutting force was measured during machining using the Kistler 9129AA dynamometer to monitor the force signals and the data was analyzed using the I-kazTM method of statistical analysis. This statistical analysis was used to assess the effect of force signals during the machining process. The RSM models for Ra and Rz, and Ideveloped with ANOVA and multiple regression equations. The models also were compared and validated with the predicted and measured of Ra and Rz values, and I-kaz coefficients. The optimal configuration of cutting parameters was observed at 200 m/min, 0.1 mm/rev and 0.521 mm with desirability of 95.9%. It is observed that the models developed are suggested to be utilized for predicting surface roughness values and I-kaz coefficients for the machining of S45C steel.

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.

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.

scholarly journals Effect of Turning Parameters and Reinforcement on the Surface Roughness of Hybrid Aluminium Metal Matrix Composite

2019 ◽  
Vol 9 (1) ◽  
Keyword(s):  
Surface Roughness ◽  
Surface Finish ◽  
Feed Rate ◽  
Metal Matrix ◽  
Matrix Material ◽  
Cutting Parameters ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Pure Aluminium ◽  
Machining Time

Since last two decades, technology has changed rapidly in each industry from consumer goods to aerospace. To quench the thrust of technology advancement of industries, the research community has to develop the novel materials. As a part of the ongoing process of material development and machinability study, present work was carried out to find out the effect of various cutting parameters on surface roughness and machining time of aluminium Hybrid Metal Matrix Composites (AHMMCs). In this study, pure aluminium was used as a matrix material while; B4C, Mg, Ti and Graphite were used as reinforcement. It was observed that 2202 RPM spindle speed, 0.18 mm/rev feed rate and 1.1 mm depth of cut are the optimum turning parameters with PCD insert. While machining of same composites using carbide insert, optimum spindle speed, feed rate and depth of cut are 2091 RPM, 0.19 mm/rev and 1.1 mm respectively. Moreover, PCD insert provides better surface finish compared to carbide coated insert for same cutting conditions. Moreover, the effect of reinforcement particles presence on the surface finish was also investigated and it was concluded that reinforcement presence reduces the surface roughness considerably. Particularly presence of Mg and graphite reduces surface finish significantly.

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.

Studies of kerf width and surface roughness using the response surface methodology in AA 4032–TiC composites

2021 ◽  
pp. 095440892110414
Author(s):  
TS Senthilkumar ◽  
R Muralikannan ◽  
T Ramkumar ◽  
S Senthil Kumar
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Metal Matrix ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Kerf Width ◽  
Wire Electrical Discharge Machining ◽  
Box Behnken Design ◽  
Pulse On Time

A substantially developed machining process, namely wire electrical discharge machining (WEDM), is used to machine complex shapes with high accuracy. This existent work investigates the optimization of the process parameters of wire electrical discharge machining, such as pulse on time ( Ton), peak current ( I), and gap voltage ( V), to analyze the output performance, such as kerf width and surface roughness, of AA 4032–TiC metal matrix composite using response surface methodology. The metal matrix composite was developed by handling the stir casting system. Response surface methodology is implemented through the Box–Behnken design to reduce experiments and design a mathematical model for the responses. The Box–Behnken design was conducted at a confident level of 99.5%, and a mathematical model was established for the responses, especially kerf width and surface roughness. Analysis of variance table was demarcated to check the cogency of the established model and determine the significant process. Surface roughness attains a maximum value at a high peak current value because high thermal energy was released, leading to poor surface finish. A validation test was directed between the predicted value and the actual value; however, the deviation is insignificant. Moreover, a confirmation test was handled for predicted and experimental values, and a minimal error was 2.3% and 2.12% for kerf width and surface roughness, respectively. Furthermore, the size of the crater, globules, microvoids, and microcracks were increased by amplifying the pulse on time.

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.

OPTIMISING CUTTING PARAMETERS FOR HOT TURNING ON EN31 MATERIAL

2021 ◽  
Vol 5 (10) ◽  
Author(s):  
Prof. Hemant k. Baitule ◽  
Satish Rahangdale ◽  
Vaibhav Kamane ◽  
Saurabh Yende
Keyword(s):  
Surface Roughness ◽  
Surface Finish ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Machining Process ◽  
Depth Of Cut ◽  
Multiple Time ◽  
Turning Process ◽  
Workpiece Material ◽  
Hot Turning

In any type of machining process the surface roughness plays an important role. In these the product is judge on the basis of their (surface roughness) surface finish. In machining process there are four main cutting parameter i.e. cutting speed, feed rate, depth of cut, spindle speed. For obtaining good surface finish, we can use the hot turning process. In hot turning process we heat the workpiece material and perform turning process multiple time and obtain the reading. The taguchi method is design to perform an experiment and L18 experiment were performed. The result is analyzed by using the analysis of variance (ANOVA) method. The result Obtain by this method may be useful for many other researchers.

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