Task scheduling based on genetic algorithm for robotic system in 5G manufacturing industry

Anwar Apandi, Nur Ilyana and Wan, Wing Sheng and Muhammad, N. A. (2022) Task scheduling based on genetic algorithm for robotic system in 5G manufacturing industry. International Journal Of Electrical Engineering And Applied Sciences (IJEEAS), 5 (1). pp. 9-15. ISSN 2600-7495

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Abstract

With the development of 5G technology, the robotic system has been bought into industrials. Even manufacturers plan the task flow by using project management. An error may occur and make the tasks overlap because they use the traditional scheduling method. It may waste much time between the tasks, and robots will get into standby mode to wait for the next tasks if the scheduling is failed. An algorithm with flexible scheduling is needed to arrange the tasks accordingly with the shortest total completion time. Genetic Algorithm (GA) is applied to task scheduling, and it provides a better solution from previous results or arrangements due to iteration. In this study, an analysis involves multi robots to complete various industrial operations, consisting of multi-tasks. To save time during processing and costs in production, GA may help it have the optimal value about total complete time to avoid any wastage. In short, the manufacturer will have higher productivity and better performance among the robots when applied a suitable Task Scheduling in the industry or workplace.

Item Type:	Article
Uncontrolled Keywords:	Genetic algorithm, Task scheduling, 5G, Robotic system, Manufacturing
Divisions:	Faculty of Electrical Engineering
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	16 Jan 2024 10:37
Last Modified:	16 Jan 2024 10:37
URI:	http://eprints.utem.edu.my/id/eprint/27023
Statistic Details:	View Download Statistic

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