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Decision Support System for Atmospheric Corrosion of Carbon Steel Pipes

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3681))

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Abstract

Pipes of a plant should be properly managed, since corrosion of pipes cause leakage of dangerous material. But, the management is a hard and costly job. Though the pipes are maintained costly, the ratio of really corroded points to inspection points is 5-10 %. Then, if max of corrosion rate is find out using condition of the inspection point, inspection points can be reduced and much cost can be cut. In this work, corrosion rate model of atmospheric corrosion of a carbon steel pipe is proposed. Furthermore, decision support system for atmospheric corrosion of carbon steel pipes is developed. Using database collected from companies, investigation of database healthy is reported.

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Author information

Authors and Affiliations

  1. Department of Chemical Engineering, Kyushu University, Fukuoka, 812-8581, Japan

    Kazuhiro Takeda & Yoshifumi Tsuge

  2. Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, 808-0135, Japan

    Hisayoshi Matsuyama

  3. Tokyo Institute of Technology, Yokohama, 226-8503, Japan

    Eiji O’shima

Authors
  1. Kazuhiro Takeda
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  2. Yoshifumi Tsuge
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  3. Hisayoshi Matsuyama
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  4. Eiji O’shima
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Editor information

Editors and Affiliations

  1. School of Business, La Trobe University, 3086, Melbourne, Victoria, Australia

    Rajiv Khosla

  2. Centre for SMART systems Engineering Research Centre, University of Brighton, Moulsecoomb, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

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© 2005 Springer-Verlag Berlin Heidelberg

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Takeda, K., Tsuge, Y., Matsuyama, H., O’shima, E. (2005). Decision Support System for Atmospheric Corrosion of Carbon Steel Pipes. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552413_22

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  • DOI: https://doi.org/10.1007/11552413_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28894-7

  • Online ISBN: 978-3-540-31983-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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