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The Algorithm Knowledge Base for Steel Production Process Optimization

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Advanced Manufacturing and Automation VII (IWAMA 2017)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 451))

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Abstract

The goal of algorithmic knowledge base is to solve the problems of various constraints and complicated process in the process of steel production. The optimal scheduling of resources, energy and technology is the core, and the optimization problem of production is solved quickly based on various intelligent optimization algorithms. Through the different optimization algorithms in the knowledge base to realize the optimization of various problems in steel production. Algorithms base collecting all kinds of optimization algorithm and application scenarios, establish intelligent algorithms base for iron and steel production process and providing intelligent decision support for intelligent steel production improving production efficiency and product quality.

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Acknowledgements

The authors would like to express appreciations to mentors in Shanghai University and Shanghai Baosight Software Corporation for their valuable comments and other helps. Thanks for the China’s National science and technology pillar program’s funding. The program number is No. 2015BAF22B01.

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Authors and Affiliations

  1. Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, Shanghai University, Shanghai, China

    Shuai Li & Lilan Liu

  2. Shanghai Baosight Software Co., Ltd., Shanghai, China

    Yiping Wu

  3. School of Business and Management, Plymouth University, Plymouth, UK

    Yi Wang

Authors
  1. Shuai Li
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  2. Lilan Liu
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  3. Yiping Wu
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  4. Yi Wang
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Corresponding author

Correspondence to Lilan Liu .

Editor information

Editors and Affiliations

  1. Department of Production and Quality Engineering, Norwegian University of Science and Technology, Trondheim, Sør-Trøndelag Fylke, Norway

    Kesheng Wang

  2. School of Business, Plymouth University, Plymouth, United Kingdom

    Yi Wang

  3. Department of Mechanical and Industrial Engineering, Norwegian University of Science and Technology, Trondheim, Sør-Trøndelag Fylke, Norway

    Jan Ola Strandhagen

  4. Shanghai Second Polytechnic University, Shanghai, China

    Tao Yu

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Li, S., Liu, L., Wu, Y., Wang, Y. (2018). The Algorithm Knowledge Base for Steel Production Process Optimization. In: Wang, K., Wang, Y., Strandhagen, J., Yu, T. (eds) Advanced Manufacturing and Automation VII. IWAMA 2017. Lecture Notes in Electrical Engineering, vol 451. Springer, Singapore. https://doi.org/10.1007/978-981-10-5768-7_57

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  • DOI: https://doi.org/10.1007/978-981-10-5768-7_57

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-5767-0

  • Online ISBN: 978-981-10-5768-7

  • eBook Packages: EngineeringEngineering (R0)

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