Modeling and optimization of multi-holes drilling path using Particle Swarm Optimization

In today’s competitive environment, optimization is considered as an important element for maintaining and improving both aspect of manufacturing such as quality and productivity. In multi-holes drilling process, 70% of the machining time involved the tool movement and tool switching. Various resear...

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Bibliographic Details
Main Authors: Ab Rashid, Mohd Fadzil Faisae, Nik Mohamed, Nik Mohd Zuki, Romlay, Fadhlur Rahman Mohd, Razali, Akhtar Razul, Asmizam, Mokhtar
Format: Research Report
Language:English
Published: 2018
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/36366/1/Modeling%20and%20optimization%20of%20multi-holes%20drilling%20path%20using%20particle%20swarm%20optimization.wm.pdf
http://umpir.ump.edu.my/id/eprint/36366/
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Institution: Universiti Malaysia Pahang
Language: English
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Summary:In today’s competitive environment, optimization is considered as an important element for maintaining and improving both aspect of manufacturing such as quality and productivity. In multi-holes drilling process, 70% of the machining time involved the tool movement and tool switching. Various researches had been conducted to reduce the tool movement and switching time. This research aim to reduce the machining time by minimizing the tool path using metaheuristics algorithms. The problem is modelled using travelling salesman problem (TSP) concept. Later the problem is optimized using Particle Swarm Optimization (PSO) and compared with other algorithms including the new metaheuristics algorithms. Then a machining experiment has been conducted to validate the optimization results. The optimization results clearly indicated that the PSO algorithm outperformed all comparison algorithms for the drilling tool path problem. The machining experiment results confirmed that the PSO algorithm provide faster tool path compared with commercial CAD CAM software, with average 5%.