Shin, Teh Muy and Asrul, Adam and Amar Faiz, Zainal Abidin (2019) A comparative study of PSO, GSA and SCA in parameters optimization of surface grinding process. Bulletin of Electrical Engineering and Informatics, 8 (3). pp. 1117-1127. ISSN 2089-3191 (Print); 2302-9285 (Online). (Published)
|
Pdf
A comparative study of PSO, GSA and SCA in parameters.pdf Download (746kB) | Preview |
Abstract
The selection of parameters in grinding process remains as a crucial role to guarantee that the machined product quality is at the minimum production cost and maximum production rate. Therefore, it is required to utilize more advance and effective optimization methods to obtain the optimum parameters and resulting an improvement on the grinding performance. In this paper, three optimization algorithms which are particle swarm optimization (PSO), gravitational search, and Sine Cosine algorithms are employed to optimize the grinding process parameters that may either reduce the cost, increase the productivity or obtain the finest surface finish and resulting a higher grinding process performance. The efficiency of the three algorithms are evaluated and comparedwith previous results obtained by other optimization methods on similar studies.The experimental results showed that PSO algorithm achieves better optimization performance in the aspect of convergence rate and accuracy of best solution.Whereas in the comparison of results of previous researchers, the obtained result of PSO proves that it is efficient in solving the complicated mathematical model of surface grinding process with different conditions.
| Item Type: | Article |
|---|---|
| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | Particle swarm optimization; Gravitational search algorithm; Sine Cosine algorithm; Surface grinding process; Production costs |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TS Manufactures |
| Faculty/Division: | Faculty of Manufacturing Engineering Institute of Postgraduate Studies |
| Depositing User: | Mrs Norsaini Abdul Samat |
| Date Deposited: | 09 Nov 2022 07:44 |
| Last Modified: | 09 Nov 2022 07:44 |
| URI: | http://umpir.ump.edu.my/id/eprint/29742 |
| Download Statistic: | View Download Statistics |
Actions (login required)
 |
View Item |