Optimization of industrial machine maintenance scheduling using ant colony method

The importance of machine maintenance has been gradually recognized especially with the great attention in industrial sector. A company was named M is a manufacturing company which engaged in the industrial manufacturer of body pail cans. Previously, the process of machine maintenance at company M i...

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Main Authors: Soenandi Iwan Aang, Budiman Teuku Emily
Format: Article
Language:English
Published: EDP Sciences 2018-01-01
Series:MATEC Web of Conferences
Online Access:https://doi.org/10.1051/matecconf/201820402001
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spelling doaj-84af70d2729f4d7c96383ec1b3ffe4872021-02-02T06:58:47ZengEDP SciencesMATEC Web of Conferences2261-236X2018-01-012040200110.1051/matecconf/201820402001matecconf_imiec2018_02001Optimization of industrial machine maintenance scheduling using ant colony methodSoenandi Iwan AangBudiman Teuku EmilyThe importance of machine maintenance has been gradually recognized especially with the great attention in industrial sector. A company was named M is a manufacturing company which engaged in the industrial manufacturer of body pail cans. Previously, the process of machine maintenance at company M is to repair the machine when a problem occurs. This causes several machines to break down frequently and disrupt the production process. Furthermore, the purpose of this research is to determine the optimum and well-planned maintenance scheduling that can reduce the risk of-or prevent machine failures that may ruin the production process by doing the preventive maintenance in right time. Ant Colony Optimization (ACO) method was used in this research as maximizing the interval time between preventive maintenance periods before the trouble occurs based on previous breakdown data period as minimizing frequency of the task. In the principle of ACO, the required parameters are α, β, m, e, el. As a result of using ACO with the combination of parameters above, the optimal well-planned maintenance scheduling was obtained by using α=2, β=5, e=0.3, e1=0.96, and a number of ants needed. Finally, the optimizing of schedule maintenance has proposed in daily for next year period.https://doi.org/10.1051/matecconf/201820402001
collection DOAJ
language English
format Article
sources DOAJ
author Soenandi Iwan Aang
Budiman Teuku Emily
spellingShingle Soenandi Iwan Aang
Budiman Teuku Emily
Optimization of industrial machine maintenance scheduling using ant colony method
MATEC Web of Conferences
author_facet Soenandi Iwan Aang
Budiman Teuku Emily
author_sort Soenandi Iwan Aang
title Optimization of industrial machine maintenance scheduling using ant colony method
title_short Optimization of industrial machine maintenance scheduling using ant colony method
title_full Optimization of industrial machine maintenance scheduling using ant colony method
title_fullStr Optimization of industrial machine maintenance scheduling using ant colony method
title_full_unstemmed Optimization of industrial machine maintenance scheduling using ant colony method
title_sort optimization of industrial machine maintenance scheduling using ant colony method
publisher EDP Sciences
series MATEC Web of Conferences
issn 2261-236X
publishDate 2018-01-01
description The importance of machine maintenance has been gradually recognized especially with the great attention in industrial sector. A company was named M is a manufacturing company which engaged in the industrial manufacturer of body pail cans. Previously, the process of machine maintenance at company M is to repair the machine when a problem occurs. This causes several machines to break down frequently and disrupt the production process. Furthermore, the purpose of this research is to determine the optimum and well-planned maintenance scheduling that can reduce the risk of-or prevent machine failures that may ruin the production process by doing the preventive maintenance in right time. Ant Colony Optimization (ACO) method was used in this research as maximizing the interval time between preventive maintenance periods before the trouble occurs based on previous breakdown data period as minimizing frequency of the task. In the principle of ACO, the required parameters are α, β, m, e, el. As a result of using ACO with the combination of parameters above, the optimal well-planned maintenance scheduling was obtained by using α=2, β=5, e=0.3, e1=0.96, and a number of ants needed. Finally, the optimizing of schedule maintenance has proposed in daily for next year period.
url https://doi.org/10.1051/matecconf/201820402001
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AT budimanteukuemily optimizationofindustrialmachinemaintenanceschedulingusingantcolonymethod
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