Pai, Dayananda and Rao, Shrikantha S and D’Souza, Rio (2011) Multi Objective Optimization of Surface Grinding Process by Combination of Response Surface Methodology and Enhanced Non-dominated Sorting Genetic Algorithm. International Journal of Computer Applications, 36 (3). pp. 19-24. ISSN 0975 – 8887
![]() |
PDF
IJCA Multi Objective Optimization of Surface Grinding.pdf - Published Version Restricted to Registered users only Download (432kB) | Request a copy |
Abstract
The present study is focused on the multi-objective optimization of performance parameters such as specific energy (u), metal removal rate (MRR) and surface roughness(Ra) obtained in grinding of Al-SiC35P composites. The enhanced elitist non-dominated sorting genetic algorithm (NSGA -II) is used to solve this multi-objective optimization problem. Al-SiC specimens containing 8 vol. %, 10 vol. % and 12 vol. % of silicon carbide particles of mean diameter 35μm, feed and depth of cut were chosen as process variables. A mathematical predictive model for each of the performance parameters was developed using response surface methodology (RSM). Further, an enhanced NSGA-II algorithm is used to optimize the model developed by RSM. Finally, the experiments were carried out to validate the results obtained from RSM and enhanced NSGA-II. The results obtained were in close agreement, which indicates that the developed model can be effectively used for the prediction.
Item Type: | Article |
---|---|
Uncontrolled Keywords: | Discontinuously reinforced aluminium composites (DRACs), Surface grinding, Central composite design (CCD), Response surface methodology (RSM), enhanced non-dominated Sorting Genetic algorithm (NSGA-II), Multi objective optimization |
Subjects: | Engineering > MIT Manipal > Aeronautical and Automobile |
Depositing User: | MIT Library |
Date Deposited: | 10 Sep 2013 11:41 |
Last Modified: | 10 Sep 2013 11:41 |
URI: | http://eprints.manipal.edu/id/eprint/137068 |
Actions (login required)
![]() |
View Item |