Application of Neural Network in Simple Tool Wear Monitoring and Indentification System in MDF Milling

This paper deals with simple neural network-based diagnostic system, applied to tool wear prediction in MDF milling. Ten tools were used for the test, and each one was consequently worn in the process of MDF milling. During the wearing process, the key process parameters were measured, such as cutti...

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Autor principal: Marcin Zbieć
Formato: article
Lenguaje:EN
Publicado: University of Zagreb, Faculty of Forestry and Wood Technology 2011
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Acceso en línea:https://doaj.org/article/8cb2d55c1c294407bc5c0dc31c6c9ca7
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spelling oai:doaj.org-article:8cb2d55c1c294407bc5c0dc31c6c9ca72021-12-02T02:18:44ZApplication of Neural Network in Simple Tool Wear Monitoring and Indentification System in MDF Milling0012-67721847-1153https://doaj.org/article/8cb2d55c1c294407bc5c0dc31c6c9ca72011-03-01T00:00:00Zhttp://hrcak.srce.hr/file/98496https://doaj.org/toc/0012-6772https://doaj.org/toc/1847-1153This paper deals with simple neural network-based diagnostic system, applied to tool wear prediction in MDF milling. Ten tools were used for the test, and each one was consequently worn in the process of MDF milling. During the wearing process, the key process parameters were measured, such as cutting and thrust forces, temperature and power consumption. The neural network-based system was used for tool wear prediction of all the tools except the fi rst one, based on data collected during the previous attempts. The test has shown that the proposed system has good prediction accuracy and that it could be a useful tool in the optimization of the woodworking process.Marcin ZbiećUniversity of Zagreb, Faculty of Forestry and Wood Technologyarticletool wearwood machining monitoringtool condition diagnostic systemForestrySD1-669.5ENDrvna Industrija, Vol 62, Iss 1, Pp 43-54 (2011)
institution DOAJ
collection DOAJ
language EN
topic tool wear
wood machining monitoring
tool condition diagnostic system
Forestry
SD1-669.5
spellingShingle tool wear
wood machining monitoring
tool condition diagnostic system
Forestry
SD1-669.5
Marcin Zbieć
Application of Neural Network in Simple Tool Wear Monitoring and Indentification System in MDF Milling
description This paper deals with simple neural network-based diagnostic system, applied to tool wear prediction in MDF milling. Ten tools were used for the test, and each one was consequently worn in the process of MDF milling. During the wearing process, the key process parameters were measured, such as cutting and thrust forces, temperature and power consumption. The neural network-based system was used for tool wear prediction of all the tools except the fi rst one, based on data collected during the previous attempts. The test has shown that the proposed system has good prediction accuracy and that it could be a useful tool in the optimization of the woodworking process.
format article
author Marcin Zbieć
author_facet Marcin Zbieć
author_sort Marcin Zbieć
title Application of Neural Network in Simple Tool Wear Monitoring and Indentification System in MDF Milling
title_short Application of Neural Network in Simple Tool Wear Monitoring and Indentification System in MDF Milling
title_full Application of Neural Network in Simple Tool Wear Monitoring and Indentification System in MDF Milling
title_fullStr Application of Neural Network in Simple Tool Wear Monitoring and Indentification System in MDF Milling
title_full_unstemmed Application of Neural Network in Simple Tool Wear Monitoring and Indentification System in MDF Milling
title_sort application of neural network in simple tool wear monitoring and indentification system in mdf milling
publisher University of Zagreb, Faculty of Forestry and Wood Technology
publishDate 2011
url https://doaj.org/article/8cb2d55c1c294407bc5c0dc31c6c9ca7
work_keys_str_mv AT marcinzbiec applicationofneuralnetworkinsimpletoolwearmonitoringandindentificationsysteminmdfmilling
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