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Research Progress on the Architecture and Key Technologies of Machine Tool Intelligent Control System
KTH, Skolan för industriell teknik och management (ITM), Industriell produktion, Hållbara produktionssystem.ORCID-id: 0000-0001-8679-8049
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2021 (engelsk)Inngår i: Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, ISSN 0577-6686, Vol. 57, nr 9, s. 147-166Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Machine tool intelligent control system, as an integral part of future intelligent machine tools, plays a significant role in improving core competencies of manufacture. Compared with traditional CNC system, the intelligent one has the advantage of higher efficiency and more stable manufacturing quality. It's able to make intelligent decisions and substitute experiences of human operators. Considering that there are few reviews on intelligent control system of machine tools, the framework and architecture of the machine tool intelligent control system is proposed by analyzing features from four stages of historical development of the machine tool control system. From the perspective of advanced technology, the related key technologies and engineering applications are elaborated, such as artificial intelligence, digital twins and cloud services. At last, after analyzing several major challenges of intelligent machine tools and their countermeasures, the future development trend of machine tool intelligent control system is forecasted. 

sted, utgiver, år, opplag, sider
Chinese Mechanical Engineering Society , 2021. Vol. 57, nr 9, s. 147-166
Emneord [en]
Artificial intelligence, Cloud service, CNC machine tool, Digital twin, Intelligent control system, Computer architecture, Control systems, Intelligent control, Man machine systems, Manufacture, Advanced technology, Development trends, Engineering applications, Historical development, Intelligent decisions, Intelligent machine, Machine tool control, Manufacturing quality, Machine tools
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Identifikatorer
URN: urn:nbn:se:kth:diva-310156DOI: 10.3901/JME.2021.09.147Scopus ID: 2-s2.0-85108741022OAI: oai:DiVA.org:kth-310156DiVA, id: diva2:1647587
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QC 20220328

Tilgjengelig fra: 2022-03-28 Laget: 2022-03-28 Sist oppdatert: 2022-06-25bibliografisk kontrollert

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Wang, Lihui

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