dc.contributor.author | Panchal, Dilbagh | |
dc.contributor.author | Singh, Anupam K. | |
dc.contributor.author | Chatterjee, Prasenjit | |
dc.contributor.author | Zavadskas, Edmundas Kazimieras | |
dc.contributor.author | Keshavarz-Ghorabaee, Mehdi | |
dc.date.accessioned | 2023-09-18T17:33:44Z | |
dc.date.available | 2023-09-18T17:33:44Z | |
dc.date.issued | 2019 | |
dc.identifier.issn | 1568-4946 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/124312 | |
dc.description.abstract | The 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.format | PDF | |
dc.format.extent | p. 242-254 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.isreferencedby | Scopus | |
dc.relation.isreferencedby | Science Citation Index Expanded (Web of Science) | |
dc.source.uri | https://doi.org/10.1016/j.asoc.2018.10.033 | |
dc.title | A new fuzzy methodology-based structured framework for RAM and risk analysis | |
dc.type | Straipsnis Web of Science DB / Article in Web of Science DB | |
dcterms.references | 53 | |
dc.type.pubtype | S1 - Straipsnis Web of Science DB / Web of Science DB article | |
dc.contributor.institution | Dr. B.R Ambedkar National Institute of Technology | |
dc.contributor.institution | J.K. College Biraul-847203, A Constituent Unit of L.N.M.U. | |
dc.contributor.institution | MCKV Institute of Engineering | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
dc.contributor.institution | Gonbad Kavous University | |
dc.contributor.faculty | Statybos fakultetas / Faculty of Civil Engineering | |
dc.contributor.department | Tvariosios statybos institutas / Institute of Sustainable Construction | |
dc.subject.researchfield | T 007 - Informatikos inžinerija / Informatics engineering | |
dc.subject.researchfield | T 002 - Statybos inžinerija / Construction and engineering | |
dc.subject.vgtuprioritizedfields | SD0404 - Statinių skaitmeninis modeliavimas ir tvarus gyvavimo ciklas / BIM and Sustainable lifecycle of the structures | |
dc.subject.ltspecializations | L102 - Energetika ir tvari aplinka / Energy and a sustainable environment | |
dc.subject.en | Chlorine production plant | |
dc.subject.en | failure causes | |
dc.subject.en | Fuzzy Lambda–Tau | |
dc.subject.en | improved Fuzzy FMEA | |
dc.subject.en | performance comparison | |
dcterms.sourcetitle | Applied soft computing | |
dc.description.volume | vol. 74 | |
dc.publisher.name | Elsevier | |
dc.publisher.city | London | |
dc.identifier.doi | 2-s2.0-85055737988 | |
dc.identifier.doi | 000454251200018 | |
dc.identifier.doi | 10.1016/j.asoc.2018.10.033 | |
dc.identifier.elaba | 32307491 | |