Optimization of transesterification process parameters of castor oil ethanolysis using response surface methodology-based genetic algorithm

2016 ◽  
Vol 38 (2) ◽  
pp. 300-308 ◽  
Author(s):  
S. Arumugam ◽  
G. Sriram ◽  
T. Rajmohan ◽  
K. Sivakumar
Keyword(s):  
Genetic Algorithm ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Castor Oil

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.

Parametric Optimization of EDM Process of Aluminium Boron Carbide Composite Using Desirability Function Approach and Genetic Algorithm

2014 ◽  
Vol 592-594 ◽  
pp. 684-688 ◽  
Author(s):  
K.R. Thangadurai ◽  
A. Asha
Keyword(s):  
Genetic Algorithm ◽  
Response Surface Methodology ◽  
Boron Carbide ◽  
Response Surface ◽  
Process Parameters ◽  
Electric Discharge ◽  
Machining Process ◽  
Electric Discharge Machining ◽  
Carbide Composite ◽  
Edm Process

Electric discharge machining process is an unconventional machining process primarily used for machining the materials such as difficult to machine in conventional machining process, hardest material and composite materials. In the present work, a study is made to find out the optimum EDM process parameters during machining of AA6061-15% boron carbide composite fabricated through stir casting technique. Three process parameters such as Current, pulse on time and pulse of time are opted as machining parameter variables. Response surface methodology is used to formulate the mathematical model for material removal rate, tool wear rate and surface roughness. Response surface methodology and genetic algorithm are applied to optimize the machining parameters individually by taking combined objective function and compared. Genetic algorithm optimization techniques yields better results than desirability approach. Key words: Electric discharge machining, MRR, TWR, Ra, RSM, Genetic algorithm

Process optimization of rolling for zincked sheet technology using response surface methodology and genetic algorithm

2017 ◽  
Vol 31 (16-19) ◽  
pp. 1744017
Author(s):  
Liang-Bo Ji ◽  
Fang Chen
Keyword(s):  
Genetic Algorithm ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Reduction Rate ◽  
Optimum Process ◽  
Surface Model ◽  
Optimization Of Process Parameters ◽  
Predicted Values ◽  
Shortening Rate

Numerical simulation and intelligent optimization technology were adopted for rolling and extrusion of zincked sheet. By response surface methodology (RSM), genetic algorithm (GA) and data processing technology, an efficient optimization of process parameters for rolling of zincked sheet was investigated. The influence trend of roller gap, rolling speed and friction factor effects on reduction rate and plate shortening rate were analyzed firstly. Then a predictive response surface model for comprehensive quality index of part was created using RSM. Simulated and predicted values were compared. Through genetic algorithm method, the optimal process parameters for the forming of rolling were solved. They were verified and the optimum process parameters of rolling were obtained. It is feasible and effective.

An Integrated RSM-GA Based Approach for Multi Response Optimization of FDM Process Parameters for Pyramidal ABS Primitives

2016 ◽  
Vol 16 (3) ◽  
pp. 201-208 ◽  
Author(s):  
Manu Srivastava ◽  
Sachin Maheshwari ◽  
T.K. Kundra ◽  
Sandeep Rathee
Keyword(s):  
Genetic Algorithm ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Fitness Function ◽  
Research Work ◽  
Fused Deposition Modelling ◽  
Time Model ◽  
Fused Deposition ◽  
Response Optimization

AbstractIn this research work, a statistical model is developed for predicting the optimal process parameters of Fused Deposition Modelling (FDM) process for layout optimization. Multi response optimization of process parameters was achieved using Response Surface Methodology technique integrated with Genetic Algorithm. Response Surface Methodology (RSM) was utilized to design and conduct experiments. 86 experiments were conducted according to central composite design considering six process parameters namely raster width, raster angle, contour width, air gap, slice height and orientation to achieve four responses namely build time, model material volume, support structure volume and production cost. RSM-genetic algorithms (GA) integrated optimization is introduced in which GA is constructed including the development of coding strategy, evaluation operator and the fitness function. The constructed GA can meet the requirement of optimization work. The fitness function is defined as the sum of compulsive constraints or responses. All the constraints/responses have assigned same weightage. A Matlab genetic algorithm solver is utilized to predict best fitness values along with the optimal individual parameters in the present work.

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