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Minimization of machining process sequence based on ant colony algorithm and conventional method

Machining airtime or non-productive time or airtime is a process of movement of the tool before shaping the workpiece. One of the methods to decrease the total machining time is by reducing airtime. Thus, in this study, an optimization of the sequence operation in machining was conducted using an Ar...

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Main Authors: Abdullah, Haslina, Law, Boon Hui C., Zakaria, Mohamad Shukri
Format: Article
Language:English
Published: Taylor's University 2023
Online Access:http://eprints.utem.edu.my/id/eprint/27334/2/0196026122023.PDF
http://eprints.utem.edu.my/id/eprint/27334/
https://jestec.taylors.edu.my/Vol%2018%20Issue%202%20April%202023/18_2_8.pdf
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spelling my.utem.eprints.273342024-07-04T10:56:14Z http://eprints.utem.edu.my/id/eprint/27334/ Minimization of machining process sequence based on ant colony algorithm and conventional method Abdullah, Haslina Law, Boon Hui C. Zakaria, Mohamad Shukri Machining airtime or non-productive time or airtime is a process of movement of the tool before shaping the workpiece. One of the methods to decrease the total machining time is by reducing airtime. Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. This algorithm was employed to decrease the machining airtime to enhance the effectiveness of the machining process. A three-dimensional model consisting of the drilling process and pocket milling process was developed using Solidworks software. Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. Hence, the results of the optimization were implemented in MasterCAM software to run the machining simulation. Then, the results of machining time that used the tool path generated by the Ant Colony algorithm method was compared with the machining time that used tool paths generated by conventional methods. Based on the simulation, the Ant Colony algorithm method is, on average, 10.8% better than conventional methods in reducing machining time. It can be concluded that the Ant Colony algorithm is capable of reducing airtime machining and enhancing the machining process's performance. Taylor's University 2023 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/27334/2/0196026122023.PDF Abdullah, Haslina and Law, Boon Hui C. and Zakaria, Mohamad Shukri (2023) Minimization of machining process sequence based on ant colony algorithm and conventional method. Journal of Engineering Science and Technology, 18 (2). pp. 949-962. ISSN 1823-4690 https://jestec.taylors.edu.my/Vol%2018%20Issue%202%20April%202023/18_2_8.pdf
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description Machining airtime or non-productive time or airtime is a process of movement of the tool before shaping the workpiece. One of the methods to decrease the total machining time is by reducing airtime. Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. This algorithm was employed to decrease the machining airtime to enhance the effectiveness of the machining process. A three-dimensional model consisting of the drilling process and pocket milling process was developed using Solidworks software. Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. Hence, the results of the optimization were implemented in MasterCAM software to run the machining simulation. Then, the results of machining time that used the tool path generated by the Ant Colony algorithm method was compared with the machining time that used tool paths generated by conventional methods. Based on the simulation, the Ant Colony algorithm method is, on average, 10.8% better than conventional methods in reducing machining time. It can be concluded that the Ant Colony algorithm is capable of reducing airtime machining and enhancing the machining process's performance.
format Article
author Abdullah, Haslina
Law, Boon Hui C.
Zakaria, Mohamad Shukri
spellingShingle Abdullah, Haslina
Law, Boon Hui C.
Zakaria, Mohamad Shukri
Minimization of machining process sequence based on ant colony algorithm and conventional method
author_facet Abdullah, Haslina
Law, Boon Hui C.
Zakaria, Mohamad Shukri
author_sort Abdullah, Haslina
title Minimization of machining process sequence based on ant colony algorithm and conventional method
title_short Minimization of machining process sequence based on ant colony algorithm and conventional method
title_full Minimization of machining process sequence based on ant colony algorithm and conventional method
title_fullStr Minimization of machining process sequence based on ant colony algorithm and conventional method
title_full_unstemmed Minimization of machining process sequence based on ant colony algorithm and conventional method
title_sort minimization of machining process sequence based on ant colony algorithm and conventional method
publisher Taylor's University
publishDate 2023
url http://eprints.utem.edu.my/id/eprint/27334/2/0196026122023.PDF
http://eprints.utem.edu.my/id/eprint/27334/
https://jestec.taylors.edu.my/Vol%2018%20Issue%202%20April%202023/18_2_8.pdf
_version_ 1804070312535392256
score 13.211869

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