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MANUFACTURING: 作品数：811被引量：1840H指数：18; 导出分析报告; 相关领域：经济管理更多>>; 相关作者：崔学民黎难秋王刚冒国兵马永昌更多>>; 相关机构：清华大学上海大学北京航空航天大学南京航空航天大学更多>>; 相关期刊：更多>>; 相关基金：国家自然科学基金国家高技术研究发展计划中国博士后科学基金国家重点基础研究发展计划更多>>

Digital Twin Modeling Enabled Machine Tool Intelligence:A Review: 《Chinese Journal of Mechanical Engineering》2024年第2期29-54,共26页Lei Zhang Jianhua Liu Cunbo Zhuang; Supported by Tianjin Municipal University Science and Technology Development Foundation of China(Grant No.2021KJ176).; Machine tools,often referred to as the“mother machines”of the manufacturing industry,are crucial in developing smart manufacturing and are increasingly becoming more intelligent.Digital twin technology can promote m...; 关键词：Machine tool Digital twin Smart manufacturing SYNCHRONIZATION

Digital Twin for Integration of Design-Manufacturing-Maintenance:An Overview被引量：7: 《Chinese Journal of Mechanical Engineering》2022年第4期1-20,共20页Yang Fu Gang Zhu Mingliang Zhu Fuzhen Xuan; Supported by National Natural Science Foundation of China(Grant Nos.51922041,51835003).; Traditional design,manufacturing and maintenance are run and managed independently under their own rules and regulations in an increasingly time-and-cost inefective manner.A unifed platform for efcient and intelligent...; 关键词：Digital twin Design-manufacturing-maintenance integration Artifcial intelligence Deep learning Information fusion Cyber-physical systems

Subsurface Defect Evaluation of Selective-Laser-Melted Inconel 738LC Alloy Using Eddy Current Testing for Additive/Subtractive Hybrid Manufacturing被引量：5: 《Chinese Journal of Mechanical Engineering》2021年第6期224-239,共16页Sai Guo Guanhui Ren Bi Zhang; Supported by Basic Research Project of Science and Technology Plan of Shenzhen(Grant No.JCYJ20170817111811303).; New materials and manufacturing technologies require applicable non-destructive techniques for quality assurance so as to achieve better performance.This study comprehensively investigated the effect of influencing fa...; 关键词：Eddy current testing Subsurface defect Additive/subtractive hybrid manufacturing Selective laser melting Inconel 738LC alloy

Greentelligence:Smart Manufacturing for a Greener Future: 《Chinese Journal of Mechanical Engineering》2021年第6期159-164,共6页Xingyu Li Baicun Wang Tao Peng Xun Xu; Supported by Zhejiang Provincial Natural Science Foundation of China(Grant No.LY19E050019);Zhejiang Provincial Soft Science Research Project(Grant No.2022C35040);Zhejiang University“Hundreds of Talents”Program(Grant No.0020886).; 1 Introduction Global climate change has grown into one of the major concerns in global industrialization and economic development.Carbon dioxide(CO_(2)),one of the six Kyoto Protocol greenhouse gases(GHGs),is the mos...; 关键词：SMART GASES EMISSIONS

Deep Learning-Driven Data Curation and Model Interpretation for Smart Manufacturing被引量：7: 《Chinese Journal of Mechanical Engineering》2021年第3期52-72,共21页Jianjing Zhang Robert X.Gao; Characterized by self-monitoring and agile adaptation to fast changing dynamics in complex production environments,smart manufacturing as envisioned under Industry 4.0 aims to improve the throughput and reliability of...; 关键词：Deep learning Data curation Model interpretation

Multi-Scale Convolutional Gated Recurrent Unit Networks for Tool Wear Prediction in Smart Manufacturing被引量：2: 《Chinese Journal of Mechanical Engineering》2021年第3期130-145,共16页Weixin Xu Huihui Miao Zhibin Zhao Jinxin Liu Chuang Sun Ruqiang Yan; Supported in part by Natural Science Foundation of China(Grant Nos.51835009,51705398);Shaanxi Province 2020 Natural Science Basic Research Plan(Grant No.2020JQ-042);Aeronautical Science Foundation(Grant No.2019ZB070001).; As an integrated application of modern information technologies and artificial intelligence,Prognostic and Health Management(PHM)is important for machine health monitoring.Prediction of tool wear is one of the symboli...; 关键词：Tool wear prediction MULTI-SCALE Convolutional neural networks Gated recurrent unit

Industrial Internet-enabled Resilient Manufacturing Strategy in the Wake of COVID-19 Pandemic: A Conceptual Framework and Implementations in China被引量：1: 《Chinese Journal of Mechanical Engineering》2021年第3期169-174,共6页Tao Peng Qiqi He Zheng Zhang Baicun Wang Xun Xu; Supported by Natural Science Foundation of Zhejiang Province(Grant No.LY19E050019).; COVID-19 pandemic has accelerated the re-shaping of globalized manufacturing industry.Achieving a high level of resilience is thereby a recognized,essential ability of future manufacturing systems with the advances in...; 关键词：Resilient manufacturing Industrial Internet COVID-19 pandemic Manufacturing strategy

Advanced Data Collection and Analysis in Data‑Driven Manufacturing Process被引量：12: 《Chinese Journal of Mechanical Engineering》2020年第3期32-52,共21页Ke Xu Yingguang Li Changqing Liu Xu Liu Xiaozhong Hao James Gao Paul G.Maropoulos; Supported by National Natural Science Foundation of China(Grant No.51805260);National Natural Science Foundation for Distinguished Young Scholars of China(Grant No.51925505);National Natural Science Foundation of China(Grant No.51775278).; The rapidly increasing demand and complexity of manufacturing process potentiates the usage of manufacturing data with the highest priority to achieve precise analyze and control,rather than using simplified physical ...; 关键词：Data-driven manufacturing Intelligent manufacturing Process monitoring Data analysis Machine learning

A Deep Learning Approach for Fault Diagnosis of Induction Motors in Manufacturing被引量：19: 《Chinese Journal of Mechanical Engineering》2017年第6期1347-1356,共10页Si-Yu Shao Wen-Jun Sun Ru-Qiang Yan Peng Wang Robert X Gao; Supported by National Natural Science Foundation of China(Grant No.51575102);Fundamental Research Funds for the Central Universities of China;Jiangsu Provincial Research Innovation Program for College Graduates of China(Grant No.KYLX16_0191); Extracting features from original signals is a key procedure for traditional fault diagnosis of induction motors, as it directly influences the performance of fault recognition. However, high quality features need exp...; 关键词：Fault diagnosis Deep learning Deep beliefnetwork. RBM CLASSIFICATION

Future Digital Design and Manufacturing: Embracing Industry 4.0 and Beyond被引量：3: 《Chinese Journal of Mechanical Engineering》2017年第5期1047-1049,共3页Sheng-Feng Qin Kai Cheng; Digital design and manufacturing have been around for several decades from the numerical control of machine tools and automating engineering design in 1960s, through early Computer Aided Design （CAD）/Computer Aided ...; 关键词：Digital design Future manufacturing Industry 4.0

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