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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2018-01-01
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Series: | MATEC Web of Conferences |
Online Access: | https://doi.org/10.1051/matecconf/201820402001 |
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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 |
work_keys_str_mv |
AT soenandiiwanaang optimizationofindustrialmachinemaintenanceschedulingusingantcolonymethod AT budimanteukuemily optimizationofindustrialmachinemaintenanceschedulingusingantcolonymethod |
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