Deep Learning-Based Identification of Steel Products

  • Li-Wei KangEmail author
  • You-Ting Chen
  • Wei-Chen Jhong
  • Chao-Yung Hsu
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 110)


To achieve smart manufacturing in Industry 4.0 for steel industry (or Steel 4.0), this paper proposes a smart steel manufacturing framework, where a deep learning-based automatic identification tracking method for steel products is developed. Automatically online tracking and identifying steel products on a production line is essential for smart manufacturing management since those products might be frequently moved and processed everywhere on the product flow. Existing approaches usually rely upon marking or embedding a series of identification codes on the steel surfaces. However, steel-making is usually processed under a very high temperature environment, making it difficult to well embed the identification codes with acceptable quality for further automatically online recognizing them. To tackle this problem, this paper presents a vision-based automatic identification tracking method without needing to embed any identification codes onto the steel product surfaces. The key idea is to utilize the essential identity of a steel product without extrinsic information embedded, achieved by automatically and deeply learning visual features from the steel image. The presented preliminary results have verified the efficiency of the proposed method.


Smart manufacturing Industry 4.0 Steel 4.0 Identification tracking Deep learning Convolutional neural networks Feature learning 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Li-Wei Kang
    • 1
    • 2
    • 3
    Email author
  • You-Ting Chen
    • 2
  • Wei-Chen Jhong
    • 2
  • Chao-Yung Hsu
    • 4
  1. 1.Graduate School of Engineering Science and TechnologyNational Yunlin University of Science and TechnologyYunlinTaiwan
  2. 2.Department of Computer Science and Information EngineeringNational Yunlin University of Science and TechnologyYunlinTaiwan
  3. 3.Artificial Intelligence Recognition Industry Service Research CenterNational Yunlin University of Science and TechnologyYunlinTaiwan
  4. 4.Automation and Instrumentation System Development SecChina Steel CorporationKaohsiungTaiwan

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