Norfadzlan, Yusup and Azlan, Mohd Zain and Siti Zaiton, Mohd Hashim (2012) Overview of PSO for Optimizing Process Parameters of Machining. Procedia Engineering, 29. pp. 914-923. ISSN 1877-7058
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Abstract
In the current trends of optimizing machining process parameters, various evolutionary or meta-heuristic techniques such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Simulated Annealing (SA), Ant Colony Optimization (ACO) and Artificial Bee Colony algorithm (ABC) have been used. This paper gives an overview of PSO techniques to optimize machining process parameter of both traditional and modern machining from 2007 to 2011. Machining process parameters such as cutting speed, depth of cut and radial rake angle are mostly considered by researchers in order to minimize or maximize machining performances. From the review, the most machining process considered in PSO was multi-pass turning while the most considered machining performance was production costs.
| Item Type: | Article |
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| Additional Information: | Information, Communication and Creative Technology |
| Uncontrolled Keywords: | Machining, Optimization, Process Parameters, PSO, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak |
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology Faculties, Institutes, Centres > Faculty of Computer Science and Information Technology Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology |
| Depositing User: | Karen Kornalius |
| Date Deposited: | 14 Sep 2017 07:04 |
| Last Modified: | 29 Sep 2022 08:27 |
| URI: | http://ir.unimas.my/id/eprint/17591 |
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