MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD

ABDULLAH, H. and LAW BOON HUI, C. and ZAKARIA, M. S. (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.

Text J16002_8e58dd498d2f61c24f0578fbc4b1170f.pdf Restricted to Registered users only Download (647kB) | Request a copy

Abstract

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.

Item Type:	Article
Uncontrolled Keywords:	Ant colony algorithm, Machining sequence, MasterCAM
Subjects:	T Technology > TJ Mechanical engineering and machinery
Divisions:	Faculty of Mechanical and Manufacturing Engineering
Depositing User:	Mr. Mohamad Zulkhibri Rahmad
Date Deposited:	25 Sep 2023 01:39
Last Modified:	25 Sep 2023 01:39
URI:	http://eprints.uthm.edu.my/id/eprint/9968

Actions (login required)

View Item