A New hybrid LGPMBWM-PIV method for automotive material selection

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dc.contributor.authorWakeel, Saif
dc.contributor.authorBingöl, Sedat
dc.contributor.authorAhmad, Shafi
dc.contributor.authorBashir, M. Nasir
dc.contributor.authorEmamat, Mir Seyed Mohammad Mohsen
dc.contributor.authorDing, Zhou
dc.contributor.authorFayaz, H.
dc.date.accessioned2022-03-03T13:30:50Z
dc.date.available2022-03-03T13:30:50Z
dc.date.issued2021en_US
dc.departmentDicle Üniversitesi, Mühendislik Fakültesi, Makine Mühendisliği Bölümüen_US
dc.descriptionWOS:000752461700007
dc.description.abstractEfforts are continuously being made by researchers to improve fuel efficiency and to reduce CO2 emissions from the passenger cars. To achieve these goal, recent trend is to make the cars components light in weight for which manufacturing car roofs using natural fiber reinforced composites (NFCs) is one of the method. Several natural fibers (NFs)are available as alternative reinforcements for the fabrication of NFCs. Different NFs possess different properties and therefore, it is necessary to select the most appropriate natural fiber for fabrication of the composites which in turn will lead to the desired performance of the vehicle. Selection of the optimal natural fiber, amongst the several alternatives, is basically a multi criteria decision making (MCDM) problem as selection is based on the evaluation of several conflicting criteria. In this study, twelve alternative natural fibers (Flax, Hemp, Jute, Kenaf, Ramie, Okra, PALF, Coir, Isora, Cotton, Banana and Sisal) and six evaluation criteria (Tensile strength, Stiffness, Failure strain, Density, Degradation temperature and Moisture gain) are considered and selection of the optimal NF is made using a newly developed hybrid MCDM method i.e. Linear goal programming model for Best-Worst method (LGPMBWM) and Proximity index value method (PIV). Results of the study reveal that among all considered natural fibers, Ramie fiber is the most suitable alternative for the fabrication of composites and coir fiber is the worst candidate for the same. Ranking results were also supported by five other MCDM methods as there was a strong correlation between PIV and other MCDM methods.en_US
dc.identifier.citationWakeel, S., Bingöl, S., Ahmad, S., Bashir, M.N., Emamat, M.S.M.M., Ding, Z. ve diğerleri. (2021). A New hybrid LGPMBWM-PIV method for automotive material selection. Informatica- An International Journal of Computing and Informatics, 45(1), 105-115.en_US
dc.identifier.doi10.31449/inf.v45i1.3246
dc.identifier.endpage115en_US
dc.identifier.issn0350-5596
dc.identifier.issn1854-3871
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85105479766
dc.identifier.scopusqualityQ3
dc.identifier.startpage105en_US
dc.identifier.urihttps://www.informatica.si/index.php/informatica/article/view/3246
dc.identifier.urihttps://hdl.handle.net/11468/9309
dc.identifier.volume45en_US
dc.identifier.wosWOS:000752461700007
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorWakeel, Saif
dc.institutionauthorBingöl, Sedat
dc.language.isoenen_US
dc.publisherSlovensko Drustvo Informatikaen_US
dc.relation.ispartofInformatica- An International Journal of Computing and Informatics
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectNatural fibresen_US
dc.subjectCar roofen_US
dc.subjectAutomotive material selectionen_US
dc.subjectLinear goal programming model for best worst methoden_US
dc.subject(LGPMBWM)PIV methoden_US
dc.titleA New hybrid LGPMBWM-PIV method for automotive material selectionen_US
dc.titleA New hybrid LGPMBWM-PIV method for automotive material selection
dc.typeArticleen_US

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