Optimization of machining parameters on temperature rise in end milling of Al 6063 using response surface methodology and genetic algorithm

2012 ◽  
Vol 67 (9-12) ◽  
pp. 2313-2323 ◽  
Author(s):  
P. S. Sivasakthivel ◽  
R. Sudhakaran
Keyword(s):  
Genetic Algorithm ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Temperature Rise ◽  
End Milling ◽  
Machining Parameters

Study on Wire Electric Discharge Machining Based on Response Surface Methodology and Genetic Algorithm

2012 ◽  
Vol 622-623 ◽  
pp. 1280-1284 ◽  
Author(s):  
Pragya Shandilya ◽  
P.K. Jain ◽  
N.K. Jain
Keyword(s):  
Genetic Algorithm ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Electric Discharge ◽  
Metal Matrix ◽  
Machining Parameters ◽  
Electric Discharge Machining ◽  
Response Parameter ◽  
Wire Electric Discharge Machining

Wire electric discharge machining (WEDM) is one of the most popular non-conventional machining processes for machining metal matrix composites (MMCs). The present research work deals the parametric optimization of the input process parameters for response parameter during WEDM of SiCp/6061 Al metal matrix composite (MMC). Response surface methodology (RSM) and genetic algorithm (GA) integrated with each other to optimize the process parameters. RSM has been used to plan and analyze the experiments. Four WEDM parameters namely servo voltage, pulse-on time, pulse-off time and wire feed rate were varied to study their effect on the quality of cut in SiCp/6061 Al MMC using cutting width (kerf) as response parameter. The relationship between kerf and machining parameters has been developed by using RSM. The mathematical model thus than developed was then employed on GA to optimized the process parameters.

scholarly journals Multi-response Optimization of End Milling Parameters for Al-Zn-Mg/SiC Co-continuous Composite Using Response Surface Methodology

2019 ◽  
Vol 25 (4) ◽  
pp. 471-477
Author(s):  
Prasanth ACHUTHAMENON SYLAJAKUMARI ◽  
Ramesh RAMAKRISHNASAMY ◽  
Gopalakrishnan PALANIAPPAN ◽  
Ramu MURUGAN
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Regression Models ◽  
Ceramic Composite ◽  
End Milling ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Linear Regression Models ◽  
Desirability Analysis ◽  
Response Optimization

A co-continuous ceramic composite (C4) was manufactured by gravity infiltration. The effect of varying machining parameters namely, speed, feed and depth of cut during end milling of C4, on the multi-responses of surface roughness, tool wear and depth of cut was investigated using response surface methodology. Non-linear regression models were generated and optimal machining parameters were determined using desirability analysis. Confirmation experiments performed, validated the models with a ± 5 % error in prediction.

Surface Roughness Prediction in End Milling of Machinable Glass Ceramic and Optimization by Response Surface Methodology

2011 ◽  
Vol 189-193 ◽  
pp. 1376-1381
Author(s):  
Moola Mohan Reddy ◽  
Alexander Gorin ◽  
Khaled A. Abou El Hossein
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Glass Ceramic ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Speed ◽  
Lower Surface ◽  
Depth Of Cut ◽  
Machining Parameters

This paper presents the prediction of a statistically analyzed model for the surface roughness,R_a of end-milled Machinable glass ceramic (MGC). Response Surface Methodology (RSM) is used to construct the models based on 3-factorial Box-Behnken Design (BBD). It is found that cutting speed is the most significant factor contributing to the surface roughness value followed by the depth of cut and feed rate. The surface roughness value decreases for higher cutting speed along with lower feed and depth of cut. Additionally, the process optimization has also been done in terms of material removal rate (MRR) to the model’s response. Ideal combinations of machining parameters are then suggested for common goal to achieve lower surface roughness value and higher MRR.

Surface Roughness Prediction in the End Milling Parameters of Aluminum Nitride Ceramic by Response Surface Methodology

2010 ◽  
Vol 154-155 ◽  
pp. 626-633
Author(s):  
Moola Mohan Reddy ◽  
Alexander Gorin ◽  
Khaled A. Abou-El-Hossein
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
End Milling ◽  
Cubic Boron Nitride ◽  
Cutting Speed ◽  
Machining Parameters ◽  
Roughness Model ◽  
Roughness Prediction ◽  
Grinding Tool

The present experimental study aimed to examine the selected machining parameters on Surface roughness in the machining of alumina nitride ceramic. The influence of cutting speed and feed rate were determined in end milling by using Cubic boron nitride grinding tool. The predictive surface roughness model has been developed by response surface methodology. The response surface contours with respect to input parameters are presented with the help of Design expert software. The adequacy of the model was tested by ANOVA.

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