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  • Open Access


    Digital Twin Modeling and Simulation Optimization of Transmission Front and Middle Case Assembly Line

    Xianfeng Cao1, Meihua Yao2, Yahui Zhang3,*, Xiaofeng Hu4, Chuanxun Wu3

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3233-3253, 2024, DOI:10.32604/cmes.2023.030773

    Abstract As the take-off of China’s macro economy, as well as the rapid development of infrastructure construction, real estate industry, and highway logistics transportation industry, the demand for heavy vehicles is increasing rapidly, the competition is becoming increasingly fierce, and the digital transformation of the production line is imminent. As one of the most important components of heavy vehicles, the transmission front and middle case assembly lines have a high degree of automation, which can be used as a pilot for the digital transformation of production. To ensure the visualization of digital twins (DT), consistent control More > Graphic Abstract

    Digital Twin Modeling and Simulation Optimization of Transmission Front and Middle Case Assembly Line

  • Open Access


    Method for Detecting Industrial Defects in Intelligent Manufacturing Using Deep Learning

    Bowen Yu, Chunli Xie*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1329-1343, 2024, DOI:10.32604/cmc.2023.046248

    Abstract With the advent of Industry 4.0, marked by a surge in intelligent manufacturing, advanced sensors embedded in smart factories now enable extensive data collection on equipment operation. The analysis of such data is pivotal for ensuring production safety, a critical factor in monitoring the health status of manufacturing apparatus. Conventional defect detection techniques, typically limited to specific scenarios, often require manual feature extraction, leading to inefficiencies and limited versatility in the overall process. Our research presents an intelligent defect detection methodology that leverages deep learning techniques to automate feature extraction and defect localization processes. Our… More >

  • Open Access


    Intelligent Control of Cabin Environment Using Computational Fluid Dynamics for Intelligent Manufacturing

    Xi Wang*, Guangping Zeng

    FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.3, pp. 563-576, 2022, DOI:10.32604/fdmp.2022.017884

    Abstract An efficient and versatile intelligent algorithm is developed for the control of the cabin environment of wind power generators. The method can be used to monitor and solve wind power generation problems at the same time. It also provides several advantages with respect to other traditional methods which imply significant workload and maintenance personnel. The functional requirements of the intelligent control system are analyzed, and a control algorithm for the stepping motor is selected and evaluated. Through the comparative analysis of the active power and internal temperature curve for three kinds of output power of More >

  • Open Access


    Design and Application Research of a Digitized Intelligent Factory in a Discrete Manufacturing Industry

    Yefeng Liu1,2,*, Yuan Zhao1,2, Kangju Li1,2, Shengping Yu3, Shaowu Li4

    Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 1081-1096, 2020, DOI:10.32604/iasc.2020.010139

    Abstract The intelligent flexible system is a powerful means for manufacturing enterprises to achieve high efficiency and high output. The physical structure of the flexible system is constructed in this paper. The three systems; workshop intelligent logistics system, management and control system and three flexible processing that produce four products are given by the deeper design. The local workshop net which contains; position sensors, radio frequency identification (RFID), AGVs, intelligent machine, robots, raw materials and operation devices is constructed in this paper. The software, which includes gages, real-time workshops, logistics trolley, and information of all kinds More >

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