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dc.contributor.authorPanchal, Dilbagh
dc.contributor.authorSingh, Anupam K.
dc.contributor.authorChatterjee, Prasenjit
dc.contributor.authorZavadskas, Edmundas Kazimieras
dc.contributor.authorKeshavarz-Ghorabaee, Mehdi
dc.date.accessioned2023-09-18T17:33:44Z
dc.date.available2023-09-18T17:33:44Z
dc.date.issued2019
dc.identifier.issn1568-4946
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/124312
dc.description.abstractThe aim of this paper is to propose a new hybridized framework for analyzing the performance issues of a chemical process plant by utilizing uncertain, imprecise and vague information. In the proposed framework, Fuzzy Lambda–Tau (FLT) approach has been used for computing reliability, availability and maintainability (RAM) parameters of the considered system. Further, for enhancing the RAM characteristics of the system, improved Fuzzy Failure Mode Effect Analysis (FMEA) approach is adopted. Under improved Fuzzy FMEA approach, defined Fuzzy linguistic rating values in the form of triangular and trapezoidal Fuzzy numbers have been assigned by the experts to each risk factor of the listed failure causes. The proposed framework is demonstrated with an industrial application in a chlorine production plant of a chemical process industry. The results show decreasing trend for system availability and deposition of solid Nacl, mechanical failure, corrosion due to wet chlorine, scanty lubrication, improper adsorption and valve malfunctioning are identified as the most critical failure causes for the considered system. A comparative performance analysis between the proposed framework, Fuzzy technique for order of preference by similarity to ideal solution (Fuzzy TOPSIS), Fuzzy evaluation based on distance from average solution (Fuzzy EDAS) and Fuzzy Vlse Kriterijumska Optimizacija I Kompromisno Resenje (Fuzzy VIKOR) are then carried out to show the competence of the proposed framework. It is expected that the analytical results would be highly useful in formulating an optimal maintenance policy for such complex systems and may also be used for improving performance of similar plants.eng
dc.formatPDF
dc.format.extentp. 242-254
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbyScience Citation Index Expanded (Web of Science)
dc.source.urihttps://doi.org/10.1016/j.asoc.2018.10.033
dc.titleA new fuzzy methodology-based structured framework for RAM and risk analysis
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.references53
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionDr. B.R Ambedkar National Institute of Technology
dc.contributor.institutionJ.K. College Biraul-847203, A Constituent Unit of L.N.M.U.
dc.contributor.institutionMCKV Institute of Engineering
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.institutionGonbad Kavous University
dc.contributor.facultyStatybos fakultetas / Faculty of Civil Engineering
dc.contributor.departmentTvariosios statybos institutas / Institute of Sustainable Construction
dc.subject.researchfieldT 007 - Informatikos inžinerija / Informatics engineering
dc.subject.researchfieldT 002 - Statybos inžinerija / Construction and engineering
dc.subject.vgtuprioritizedfieldsSD0404 - Statinių skaitmeninis modeliavimas ir tvarus gyvavimo ciklas / BIM and Sustainable lifecycle of the structures
dc.subject.ltspecializationsL102 - Energetika ir tvari aplinka / Energy and a sustainable environment
dc.subject.enChlorine production plant
dc.subject.enfailure causes
dc.subject.enFuzzy Lambda–Tau
dc.subject.enimproved Fuzzy FMEA
dc.subject.enperformance comparison
dcterms.sourcetitleApplied soft computing
dc.description.volumevol. 74
dc.publisher.nameElsevier
dc.publisher.cityLondon
dc.identifier.doi2-s2.0-85055737988
dc.identifier.doi000454251200018
dc.identifier.doi10.1016/j.asoc.2018.10.033
dc.identifier.elaba32307491


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