USING ANFIS FOR MAINTENANCE PLANNING OF TEXTILE MACHINES

Considering the complexity of the wear of textile machines, a mathematical modeling of this phenomenon is not available in the existing literature. Based on the advantages of both fuzzy logic and neural networks, a neuro-fuzzy approach seems to be well suited for the prediction of the maintenance ac...

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Main Authors: ŞUTEU Marius Darius, BABAN Marius, BABAN Calin Florin, DERECICHEI (ŢAP) Alexandra Paula
Format: Article
Language:English
Published: Editura Universităţii din Oradea 2020-05-01
Series:Annals of the University of Oradea: Fascicle of Textiles, Leatherwork
Subjects:
Online Access:http://textile.webhost.uoradea.ro/Annals/Vol%2021-no%201-2020/Textile/Art.%20no.%20418%20pag%20123-126.pdf
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author ŞUTEU Marius Darius
BABAN Marius
BABAN Calin Florin
DERECICHEI (ŢAP) Alexandra Paula
author_facet ŞUTEU Marius Darius
BABAN Marius
BABAN Calin Florin
DERECICHEI (ŢAP) Alexandra Paula
author_sort ŞUTEU Marius Darius
collection DOAJ
description Considering the complexity of the wear of textile machines, a mathematical modeling of this phenomenon is not available in the existing literature. Based on the advantages of both fuzzy logic and neural networks, a neuro-fuzzy approach seems to be well suited for the prediction of the maintenance activities of textile machines. Therefore, the Adaptive Neuro Fuzzy Inference System (ANFIS) was proposed in this study to plan the maintenance activities of textile machines. The research was performed on the PEGASUS sewing machine at a working speed of 3100 stitches/minute. The sewing material used in the experiments was cotton, while NM 80 sewing needles were employed. The vibrations along the OZ axis and level of noise of the PEGASUS sewing machine were measured with appropriate devices. The ANFIS of the Matlab® software was used to plan the maintenance of textile machines. The amplitude of vibration and level of noise of the needles were used as inputs in the ANFIS system. The output of the ANFIS system was the time to replacement of the needles. The performance of the developed ANFIS system was expressed through the RMSE and MAPE measures. Considering their values, it may be pointed out that the ANFIS prediction system demonstrates good performance.
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spelling doaj.art-ac1ac2e0c6294efd905bef9d1b90f66a2022-12-22T03:09:22ZengEditura Universităţii din OradeaAnnals of the University of Oradea: Fascicle of Textiles, Leatherwork1843-813X2457-48802020-05-01211123126USING ANFIS FOR MAINTENANCE PLANNING OF TEXTILE MACHINESŞUTEU Marius Darius0BABAN Marius1BABAN Calin Florin2DERECICHEI (ŢAP) Alexandra Paula3University of Oradea, Faculty of Energy Engineering and Industrial Management, Department Textiles, Leather and Industrial Management, 410058, Oradea, RomâniaUniversity of Oradea, Faculty of Managerial and Technological Engineering, Department Industrial Engineering, 410087, Oradea, RomâniaUniversity of Oradea, Faculty of Managerial and Technological Engineering, Department Industrial Engineering, 410087, Oradea, RomâniaUniversity of Oradea, Faculty of Managerial and Technological Engineering, Department Industrial Engineering, 410087, Oradea, RomâniaConsidering the complexity of the wear of textile machines, a mathematical modeling of this phenomenon is not available in the existing literature. Based on the advantages of both fuzzy logic and neural networks, a neuro-fuzzy approach seems to be well suited for the prediction of the maintenance activities of textile machines. Therefore, the Adaptive Neuro Fuzzy Inference System (ANFIS) was proposed in this study to plan the maintenance activities of textile machines. The research was performed on the PEGASUS sewing machine at a working speed of 3100 stitches/minute. The sewing material used in the experiments was cotton, while NM 80 sewing needles were employed. The vibrations along the OZ axis and level of noise of the PEGASUS sewing machine were measured with appropriate devices. The ANFIS of the Matlab® software was used to plan the maintenance of textile machines. The amplitude of vibration and level of noise of the needles were used as inputs in the ANFIS system. The output of the ANFIS system was the time to replacement of the needles. The performance of the developed ANFIS system was expressed through the RMSE and MAPE measures. Considering their values, it may be pointed out that the ANFIS prediction system demonstrates good performance.http://textile.webhost.uoradea.ro/Annals/Vol%2021-no%201-2020/Textile/Art.%20no.%20418%20pag%20123-126.pdfwearvibrationnoiseanfisreplacement
spellingShingle ŞUTEU Marius Darius
BABAN Marius
BABAN Calin Florin
DERECICHEI (ŢAP) Alexandra Paula
USING ANFIS FOR MAINTENANCE PLANNING OF TEXTILE MACHINES
Annals of the University of Oradea: Fascicle of Textiles, Leatherwork
wear
vibration
noise
anfis
replacement
title USING ANFIS FOR MAINTENANCE PLANNING OF TEXTILE MACHINES
title_full USING ANFIS FOR MAINTENANCE PLANNING OF TEXTILE MACHINES
title_fullStr USING ANFIS FOR MAINTENANCE PLANNING OF TEXTILE MACHINES
title_full_unstemmed USING ANFIS FOR MAINTENANCE PLANNING OF TEXTILE MACHINES
title_short USING ANFIS FOR MAINTENANCE PLANNING OF TEXTILE MACHINES
title_sort using anfis for maintenance planning of textile machines
topic wear
vibration
noise
anfis
replacement
url http://textile.webhost.uoradea.ro/Annals/Vol%2021-no%201-2020/Textile/Art.%20no.%20418%20pag%20123-126.pdf
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