Fuzzy-based failure diagnostic analysis in a chemical process industry

Mohammad Yazdi, Mahlagha Darvishmotevali

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

10 Citations (Scopus)

Abstract

Failure analysis is vital to prevent potential incidents in chemical process industries. The varieties of different failure analysis methods such as fault tree analysis (FTA) help assessors to optimize the amount of risk by providing corresponding corrective actions. However, such conventional failure analysis techniques still suffer from several shortages. As an example, availability of failure data in some cases is rare and besides they cannot be much more effective in dynamic structure. In this paper, a new framework based on probabilistic failure analysis using an integration of FTA and Petri-nets are proposed to provide ability in dynamic structure. Fuzzy logic is also used to deal with uncertainty conditions when there is a lack of information. A real case study of kick in chemical process industry is surveyed to show the effectiveness and efficiency of the proposed model.

Original languageEnglish
Title of host publication13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing — ICAFS-2018 -
EditorsJanusz Kacprzyk, Witold Pedrycz, Mo. Jamshidi, Fahreddin M. Sadikoglu, Rafik A. Aliev
PublisherSpringer-Verlag
Pages724-731
Number of pages8
ISBN (Print)9783030041632
DOIs
Publication statusPublished - 2019
Externally publishedYes
Event13th International Conference on Application of Fuzzy Systems and Soft Computing, ICAFS 2018 - Warsaw, Poland
Duration: 27 Aug 201828 Aug 2018

Publication series

NameAdvances in Intelligent Systems and Computing
Volume896
ISSN (Print)2194-5357

Conference

Conference13th International Conference on Application of Fuzzy Systems and Soft Computing, ICAFS 2018
Country/TerritoryPoland
CityWarsaw
Period27/08/1828/08/18

Keywords

  • Aggregation
  • Failure analysis
  • Uncertainty

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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