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

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,...

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Main Authors: Anwar Apandi, Nur Ilyana, Wan, Wing Sheng, Muhammad, N. A.
Format: Article
Language:English
Published: Penerbit Universiti, UTeM 2022
Online Access:http://eprints.utem.edu.my/id/eprint/27023/2/6095-ARTICLE%20TEXT-17479-2-10-20220801.PDF
http://eprints.utem.edu.my/id/eprint/27023/
https://ijeeas.utem.edu.my/ijeeas/article/view/6095/4024
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spelling my.utem.eprints.270232024-01-16T10:37:31Z http://eprints.utem.edu.my/id/eprint/27023/ Task scheduling based on genetic algorithm for robotic system in 5G manufacturing industry Anwar Apandi, Nur Ilyana Wan, Wing Sheng Muhammad, N. A. 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. Penerbit Universiti, UTeM 2022-04 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/27023/2/6095-ARTICLE%20TEXT-17479-2-10-20220801.PDF 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 https://ijeeas.utem.edu.my/ijeeas/article/view/6095/4024
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 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.
format Article
author Anwar Apandi, Nur Ilyana
Wan, Wing Sheng
Muhammad, N. A.
spellingShingle Anwar Apandi, Nur Ilyana
Wan, Wing Sheng
Muhammad, N. A.
Task scheduling based on genetic algorithm for robotic system in 5G manufacturing industry
author_facet Anwar Apandi, Nur Ilyana
Wan, Wing Sheng
Muhammad, N. A.
author_sort Anwar Apandi, Nur Ilyana
title Task scheduling based on genetic algorithm for robotic system in 5G manufacturing industry
title_short Task scheduling based on genetic algorithm for robotic system in 5G manufacturing industry
title_full Task scheduling based on genetic algorithm for robotic system in 5G manufacturing industry
title_fullStr Task scheduling based on genetic algorithm for robotic system in 5G manufacturing industry
title_full_unstemmed Task scheduling based on genetic algorithm for robotic system in 5G manufacturing industry
title_sort task scheduling based on genetic algorithm for robotic system in 5g manufacturing industry
publisher Penerbit Universiti, UTeM
publishDate 2022
url http://eprints.utem.edu.my/id/eprint/27023/2/6095-ARTICLE%20TEXT-17479-2-10-20220801.PDF
http://eprints.utem.edu.my/id/eprint/27023/
https://ijeeas.utem.edu.my/ijeeas/article/view/6095/4024
_version_ 1789429987508486144
score 13.211869

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