Efficient management method of corrosion under insulation using group numbering of continuous conditions

Sunghye Moon*, Shigeyuki Tateno, Hisayoshi Matsuyama

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Corrosion is degradation of materials' properties due to interactions with the environments, and corrosion of most metal materials is inevitable. Corrosion damage can lead to fatal environmental consequences like toxic substance leakage, as well as huge maintenance and repairing costs during the suspension of process equipment in chemical and petroleum industries. There are many pipes whose outside surfaces are considerably corroded because many chemical and petrochemical plants in Japan have been used for 30 years or more. Corrosions on the outside surface of pipes progress slowly, and corrosion under insulation (CUI) is extremely difficult to detect and quantify. The proper points of pipe inspection are hard to find. Moreover, the insulation stripping work requires a large amount of time and cost. Besides, the successful managerial methods have not been established. The purpose of this research is to estimate CUI potential and corrosion rates by using case database and Group numbering of the continuous conditions.

Original languageEnglish
Title of host publicationICCAS 2010 - International Conference on Control, Automation and Systems
Pages590-595
Number of pages6
Publication statusPublished - 2010 Dec 1
EventInternational Conference on Control, Automation and Systems, ICCAS 2010 - Gyeonggi-do, Korea, Republic of
Duration: 2010 Oct 272010 Oct 30

Publication series

NameICCAS 2010 - International Conference on Control, Automation and Systems

Conference

ConferenceInternational Conference on Control, Automation and Systems, ICCAS 2010
Country/TerritoryKorea, Republic of
CityGyeonggi-do
Period10/10/2710/10/30

Keywords

  • CUI
  • Corrosion rate
  • Database modeling
  • Maintenance
  • Nondestructive testing

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering

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