Towards intelligent control system for computer numerical control machines

Advances in deep learning have led to impressive results in recent years. The new technologies such as convolutional neural networks, reinforcement learning and generative adversarial networks have shown a real promise for industrial and real-life applications. In this paper, the results of the expe...

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Główni autorzy:	Nikolaev, E. I., Николаев, Е. И.
Format:	Статья
Język:	English
Wydane:	Institute of Physics Publishing 2019
Hasła przedmiotowe:	Numerical control systems Reinforcement learning Automation Deep learning Engineering education Intelligent control Large dataset Machine learning Machine tools Neural networks Computer control systems
Dostęp online:	https://www.scopus.com/record/display.uri?eid=2-s2.0-85068641414&origin=resultslist&sort=plf-f&src=s&st1=Towards+intelligent+control+system+for+computer+numerical+control+machines&st2=&sid=d1b3a8e1a522cb2683562dcb2176121f&sot=b&sdt=b&sl=89&s=TITLE-ABS-KEY%28Towards+intelligent+control+system+for+computer+numerical+control+machines%29&relpos=0&citeCnt=0&searchTerm= https://dspace.ncfu.ru/handle/20.500.12258/6800
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spelling	ir-20.500.12258-68002020-09-03T14:27:35Z Towards intelligent control system for computer numerical control machines Nikolaev, E. I. Николаев, Е. И. Numerical control systems Reinforcement learning Automation Deep learning Engineering education Intelligent control Large dataset Machine learning Machine tools Neural networks Computer control systems Advances in deep learning have led to impressive results in recent years. The new technologies such as convolutional neural networks, reinforcement learning and generative adversarial networks have shown a real promise for industrial and real-life applications. In this paper, the results of the experimental research on designing, training and implementation of the intelligent control system for the computer numerical control (CNC) machine were presented. The results indicate that using the generative adversarial technique in conjunction with reinforcement learning is possible to design and train the control systems for the machine tools. Building intelligent models in the absence of large datasets of labelled data is a crucial task. One of the key points of this experimental study is the training of a model of the control system using a set of unmarked data. This is achieved by using a reinforcement learning technique. A designed model can be deployed on the physical machine tools like a computer numerical control machine. At the presented research the laser engraver CNC machine is used. In this paper, the architecture of the computer intelligent control system for the laser engraver and the process of its training are described. The proposed model can be applied to different types of CNC machines 2019-08-01T09:40:45Z 2019-08-01T09:40:45Z 2019 Статья Nikolaev, E.I. Towards intelligent control system for computer numerical control machines // IOP Conference Series: Materials Science and Engineering. - 2019. - Volume 537. - Issue 3. - Article number 032085 https://www.scopus.com/record/display.uri?eid=2-s2.0-85068641414&origin=resultslist&sort=plf-f&src=s&st1=Towards+intelligent+control+system+for+computer+numerical+control+machines&st2=&sid=d1b3a8e1a522cb2683562dcb2176121f&sot=b&sdt=b&sl=89&s=TITLE-ABS-KEY%28Towards+intelligent+control+system+for+computer+numerical+control+machines%29&relpos=0&citeCnt=0&searchTerm= http://hdl.handle.net/20.500.12258/6800 en IOP Conference Series: Materials Science and Engineering application/pdf application/pdf Institute of Physics Publishing
institution	СКФУ
collection	Репозиторий
language	English
topic	Numerical control systems Reinforcement learning Automation Deep learning Engineering education Intelligent control Large dataset Machine learning Machine tools Neural networks Computer control systems
spellingShingle	Numerical control systems Reinforcement learning Automation Deep learning Engineering education Intelligent control Large dataset Machine learning Machine tools Neural networks Computer control systems Nikolaev, E. I. Николаев, Е. И. Towards intelligent control system for computer numerical control machines
description	Advances in deep learning have led to impressive results in recent years. The new technologies such as convolutional neural networks, reinforcement learning and generative adversarial networks have shown a real promise for industrial and real-life applications. In this paper, the results of the experimental research on designing, training and implementation of the intelligent control system for the computer numerical control (CNC) machine were presented. The results indicate that using the generative adversarial technique in conjunction with reinforcement learning is possible to design and train the control systems for the machine tools. Building intelligent models in the absence of large datasets of labelled data is a crucial task. One of the key points of this experimental study is the training of a model of the control system using a set of unmarked data. This is achieved by using a reinforcement learning technique. A designed model can be deployed on the physical machine tools like a computer numerical control machine. At the presented research the laser engraver CNC machine is used. In this paper, the architecture of the computer intelligent control system for the laser engraver and the process of its training are described. The proposed model can be applied to different types of CNC machines
format	Статья
author	Nikolaev, E. I. Николаев, Е. И.
author_facet	Nikolaev, E. I. Николаев, Е. И.
author_sort	Nikolaev, E. I.
title	Towards intelligent control system for computer numerical control machines
title_short	Towards intelligent control system for computer numerical control machines
title_full	Towards intelligent control system for computer numerical control machines
title_fullStr	Towards intelligent control system for computer numerical control machines
title_full_unstemmed	Towards intelligent control system for computer numerical control machines
title_sort	towards intelligent control system for computer numerical control machines
publisher	Institute of Physics Publishing
publishDate	2019
url	https://www.scopus.com/record/display.uri?eid=2-s2.0-85068641414&origin=resultslist&sort=plf-f&src=s&st1=Towards+intelligent+control+system+for+computer+numerical+control+machines&st2=&sid=d1b3a8e1a522cb2683562dcb2176121f&sot=b&sdt=b&sl=89&s=TITLE-ABS-KEY%28Towards+intelligent+control+system+for+computer+numerical+control+machines%29&relpos=0&citeCnt=0&searchTerm= https://dspace.ncfu.ru/handle/20.500.12258/6800
work_keys_str_mv	AT nikolaevei towardsintelligentcontrolsystemforcomputernumericalcontrolmachines AT nikolaevei towardsintelligentcontrolsystemforcomputernumericalcontrolmachines
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Towards intelligent control system for computer numerical control machines

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