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Optimization of Drilling Process Using Non-Conventional Method

Haslina Abdullah 1, Mohamad Shukri Zakaria 2, Norfazillah Talib 1, Lee Woon Kiow 1, and Aslinda Saleh 1
1. Department of Manufacturing and Industry, Faculty of Mechanical and Manufacturing Industry, University Tun Hussein Onn Malaysia, Johor, Malaysia
2. Faculty of Mechanical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia

Abstract—Reducing time in the machining process is important in order to increase the efficiency of the process. In this present study, a non-conventional method was used to minimise the tool path length in the drilling process in order to decrease machining time. Ant Colony Optimisation (ACO) and Particle Swarm Optimisation (PSO) were applied to optimise the tool path in the drilling process. Then, the optimum tool path length was compared to the Genetic Algorithm and conventional methods. A workpiece with 158 holes was developed in Solidworks software in order to minimise the tool path length based on the drilling process. Then, the model was exported to Mastercam software for the simulation of tool path. The result of ACO and PSO showed that the optimisation process could reduce the tool path length in the drilling process as compared to the tool path length produced by Mastercam. It could be summarised that the simulation of non-conventional method is capable to determine the shortest tool path length, thus reducing machining time for the drilling process

Index Terms—tool path length, Mastercam, particle swarm optimization, ant colony algorithm, drilling

Cite: Haslina Abdullah, Mohamad Shukri Zakaria, Norfazillah Talib, Lee Woon Kiow, and Aslinda Saleh, "Optimization of Drilling Process Using Non-Conventional Method," International Journal of Mechanical Engineering and Robotics Research, Vol. 9, No. 9, pp. 1233-1239, September 2020. DOI: 10.18178/ijmerr.9.9.1233-1239

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.