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  • Open Access

    ARTICLE

    A Hybrid Deep Learning and Machine Learning-Based Approach to Classify Defects in Hot Rolled Steel Strips for Smart Manufacturing

    Tajmal Hussain, Jungpyo Hong*, Jongwon Seok*

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2099-2119, 2024, DOI:10.32604/cmc.2024.050884 - 15 August 2024

    Abstract Smart manufacturing is a process that optimizes factory performance and production quality by utilizing various technologies including the Internet of Things (IoT) and artificial intelligence (AI). Quality control is an important part of today’s smart manufacturing process, effectively reducing costs and enhancing operational efficiency. As technology in the industry becomes more advanced, identifying and classifying defects has become an essential element in ensuring the quality of products during the manufacturing process. In this study, we introduce a CNN model for classifying defects on hot-rolled steel strip surfaces using hybrid deep learning techniques, incorporating a global… More >

  • Open Access

    ARTICLE

    A Hybrid Manufacturing Process Monitoring Method Using Stacked Gated Recurrent Unit and Random Forest

    Chao-Lung Yang1,*, Atinkut Atinafu Yilma1,2, Bereket Haile Woldegiorgis2, Hendrik Tampubolon3,4, Hendri Sutrisno5

    Intelligent Automation & Soft Computing, Vol.39, No.2, pp. 233-254, 2024, DOI:10.32604/iasc.2024.043091 - 21 May 2024

    Abstract This study proposed a new real-time manufacturing process monitoring method to monitor and detect process shifts in manufacturing operations. Since real-time production process monitoring is critical in today’s smart manufacturing. The more robust the monitoring model, the more reliable a process is to be under control. In the past, many researchers have developed real-time monitoring methods to detect process shifts early. However, these methods have limitations in detecting process shifts as quickly as possible and handling various data volumes and varieties. In this paper, a robust monitoring model combining Gated Recurrent Unit (GRU) and Random… More >

  • Open Access

    REVIEW

    Comprehensive Survey of the Landscape of Digital Twin Technologies and Their Diverse Applications

    Haiyu Chen1, Haijian Shao1,2,*, Xing Deng1, Lijuan Wang1, Xia Wang3

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 125-165, 2024, DOI:10.32604/cmes.2023.027834 - 22 September 2023

    Abstract The concept of the digital twin, also known colloquially as the DT, is a fundamental principle within Industry 4.0 framework. In recent years, the concept of digital siblings has generated considerable academic and practical interest. However, academia and industry have used a variety of interpretations, and the scientific literature lacks a unified and consistent definition of this term. The purpose of this study is to systematically examine the definitional landscape of the digital twin concept as outlined in scholarly literature, beginning with its origins in the aerospace domain and extending to its contemporary interpretations in More >

  • Open Access

    REVIEW

    Modeling Methods of 3D Model in Digital Twins

    Ruijun Liu1, Haisheng Li1,*, Zhihan Lv2

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 985-1022, 2023, DOI:10.32604/cmes.2023.023154 - 06 February 2023

    Abstract To understand the current application and development of 3D modeling in Digital Twins (DTs), abundant literatures on DTs and 3D modeling are investigated by means of literature review. The transition process from 3D modeling to DTs modeling is analyzed, as well as the current application of DTs modeling in various industries. The application of 3D DTs modeling in the fields of smart manufacturing, smart ecology, smart transportation, and smart buildings in smart cities is analyzed in detail, and the current limitations are summarized. It is found that the 3D modeling technology in DTs has broad More >

  • Open Access

    ARTICLE

    Industry 4.0: Architecture and Equipment Revolution

    Ahmed Bashar Fakhri1, Saleem Latteef Mohammed1, Imran Khan2, Ali Safaa Sadiq3,4, Basem Alkazemi5, Prashant Pillai4, Bong Jun Choi6,*

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1175-1194, 2021, DOI:10.32604/cmc.2020.012587 - 26 November 2020

    Abstract The development of science and technology has led to the era of Industry 4.0. The core concept is the combination of “material and informationization”. In the supply chain and manufacturing process, the “material” of the physical entity world is realized by data, identity, intelligence, and information. Industry 4.0 is a disruptive transformation and upgrade of intelligent industrialization based on the Internet-of-Things and Big Data in traditional industrialization. The goal is “maximizing production efficiency, minimizing production costs, and maximizing the individual needs of human beings for products and services.” Achieving this goal will surely bring about More >

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