Optimization of multi-holes drilling path using particle swarm optimization

In multi-holes drilling process, the tool movement and tool switching consumed on average 70% of the total machining time. Tool path optimization is able to reduce the time taken in machining process. This paper is focus on the modeling and optimization of multi-holes drilling path. The problem is m...

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Main Authors:	Najwa Wahida, Zainal Abidin, M. F. F., Ab Rashid, N. M. Zuki, N. M.
Format:	Book Section
Language:	English English
Published:	Springer Singapore 2018
Subjects:	TJ Mechanical engineering and machinery
Online Access:	http://umpir.ump.edu.my/id/eprint/21657/ http://umpir.ump.edu.my/id/eprint/21657/ http://umpir.ump.edu.my/id/eprint/21657/ http://umpir.ump.edu.my/id/eprint/21657/1/book27%20Optimization%20of%20Multi-holes%20Drilling%20Path%20Using%20Particle%20Swarm%20Optimization.pdf http://umpir.ump.edu.my/id/eprint/21657/2/book27.1%20Optimization%20of%20Multi-holes%20Drilling%20Path%20Using%20Particle%20Swarm%20Optimization.pdf

id	ump-21657
recordtype	eprints
spelling	ump-216572018-08-06T08:27:00Z http://umpir.ump.edu.my/id/eprint/21657/ Optimization of multi-holes drilling path using particle swarm optimization Najwa Wahida, Zainal Abidin M. F. F., Ab Rashid N. M. Zuki, N. M. TJ Mechanical engineering and machinery In multi-holes drilling process, the tool movement and tool switching consumed on average 70% of the total machining time. Tool path optimization is able to reduce the time taken in machining process. This paper is focus on the modeling and optimization of multi-holes drilling path. The problem is modeled as traveling salesman problem (TSP) and optimized using Particle Swarm Optimization (PSO). To test the PSO performance, 15 test problems were created with different range of holes numbers. The optimization results from PSO were compared with other top algorithms such Genetic Algorithm and Ant Colony Optimization algorithm. PSO is also compared with another algorithm like Whale Optimization Algorithm, Ant Lion Optimizer, Dragonfly Algorithm, Grasshopper Optimization Algorithm, Moth-flame Optimization and Sine Cosine Algorithm. The result indicates that PSO algorithm is performed better than comparison algorithms. PSO algorithm gives the minimum value of fitness path and their CPU time compared to other algorithms. Hence, the smaller their value, the algorithm is better and more efficient. In future, researchers should more focus on environmental issues and energy consumption for sustainable manufacturing. Besides, need to explore other potential of new meta-heuristics algorithms to increase the hole drilling operation efficiencies. Springer Singapore 2018-04-28 Book Section PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/21657/1/book27%20Optimization%20of%20Multi-holes%20Drilling%20Path%20Using%20Particle%20Swarm%20Optimization.pdf pdf en http://umpir.ump.edu.my/id/eprint/21657/2/book27.1%20Optimization%20of%20Multi-holes%20Drilling%20Path%20Using%20Particle%20Swarm%20Optimization.pdf Najwa Wahida, Zainal Abidin and M. F. F., Ab Rashid and N. M. Zuki, N. M. (2018) Optimization of multi-holes drilling path using particle swarm optimization. In: Intelligent Manufacturing & Mechatronics: Proceedings of Symposium, 29 January 2018, Pekan, Pahang, Malaysia. Lecture Notes in Mechanical Engineering . Springer Singapore, Singapore, pp. 101-107. ISBN 9789811087875 https://doi.org/10.1007/978-981-10-8788-2_10 DOI: https://doi.org/10.1007/978-981-10-8788-2_10
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English English
topic	TJ Mechanical engineering and machinery
spellingShingle	TJ Mechanical engineering and machinery Najwa Wahida, Zainal Abidin M. F. F., Ab Rashid N. M. Zuki, N. M. Optimization of multi-holes drilling path using particle swarm optimization
description	In multi-holes drilling process, the tool movement and tool switching consumed on average 70% of the total machining time. Tool path optimization is able to reduce the time taken in machining process. This paper is focus on the modeling and optimization of multi-holes drilling path. The problem is modeled as traveling salesman problem (TSP) and optimized using Particle Swarm Optimization (PSO). To test the PSO performance, 15 test problems were created with different range of holes numbers. The optimization results from PSO were compared with other top algorithms such Genetic Algorithm and Ant Colony Optimization algorithm. PSO is also compared with another algorithm like Whale Optimization Algorithm, Ant Lion Optimizer, Dragonfly Algorithm, Grasshopper Optimization Algorithm, Moth-flame Optimization and Sine Cosine Algorithm. The result indicates that PSO algorithm is performed better than comparison algorithms. PSO algorithm gives the minimum value of fitness path and their CPU time compared to other algorithms. Hence, the smaller their value, the algorithm is better and more efficient. In future, researchers should more focus on environmental issues and energy consumption for sustainable manufacturing. Besides, need to explore other potential of new meta-heuristics algorithms to increase the hole drilling operation efficiencies.
format	Book Section
author	Najwa Wahida, Zainal Abidin M. F. F., Ab Rashid N. M. Zuki, N. M.
author_facet	Najwa Wahida, Zainal Abidin M. F. F., Ab Rashid N. M. Zuki, N. M.
author_sort	Najwa Wahida, Zainal Abidin
title	Optimization of multi-holes drilling path using particle swarm optimization
title_short	Optimization of multi-holes drilling path using particle swarm optimization
title_full	Optimization of multi-holes drilling path using particle swarm optimization
title_fullStr	Optimization of multi-holes drilling path using particle swarm optimization
title_full_unstemmed	Optimization of multi-holes drilling path using particle swarm optimization
title_sort	optimization of multi-holes drilling path using particle swarm optimization
publisher	Springer Singapore
publishDate	2018
url	http://umpir.ump.edu.my/id/eprint/21657/ http://umpir.ump.edu.my/id/eprint/21657/ http://umpir.ump.edu.my/id/eprint/21657/ http://umpir.ump.edu.my/id/eprint/21657/1/book27%20Optimization%20of%20Multi-holes%20Drilling%20Path%20Using%20Particle%20Swarm%20Optimization.pdf http://umpir.ump.edu.my/id/eprint/21657/2/book27.1%20Optimization%20of%20Multi-holes%20Drilling%20Path%20Using%20Particle%20Swarm%20Optimization.pdf
first_indexed	2023-09-18T22:31:52Z
last_indexed	2023-09-18T22:31:52Z
_version_	1777416339819855872

Optimization of multi-holes drilling path using particle swarm optimization

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