Selection of peanut butter machine by the integrated PSI-SV-MARCOS method

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dc.authoridÜre, Salim/0000-0003-4207-3761
dc.authoridStevi?, ?eljko/0000-0003-4452-5768
dc.authoridUlutaş, Alptekin/0000-0002-8130-1301
dc.authorwosidÜre, Salim/HHR-8498-2022
dc.authorwosidStevi?, ?eljko/P-6467-2018
dc.authorwosidUlutaş, Alptekin/HHZ-2996-2022
dc.contributor.authorToslak, Melike
dc.contributor.authorUlutas, Alptekin
dc.contributor.authorUre, Salim
dc.contributor.authorStevic, Zeljko
dc.date.accessioned2024-08-04T21:01:06Z
dc.date.available2024-08-04T21:01:06Z
dc.date.issued2023
dc.departmentİnönü Üniversitesien_US
dc.description.abstractProduction enterprises are enterprises that produce goods or services that aim to meet human needs such as machinery-equipment materials and labour. In order for a manufacturing enterprise to carry out its activities successfully, it must make the right choice when choosing its inputs. The correct execution of production activities and the selection of machinery, which requires high capital investments, also affect the efficiency of the enterprises, the correct use of materials and their costs. Therefore, it is an important decision for business managers to choose the right machine. At this stage, multi-criteria decision making (MCDM) methods are used for choosing the right machine. MCDM methods are methods used in the evaluation of alternatives using more than one criterion. In addition, the MCDM method is used in machine selection as well as in many areas. In this study, PSI, SV and MARCOS methods, which are among the MCDM methods, were used for peanut butter machine selection. First, the criteria and alternatives to be used for the peanut butter machine selection were determined by interviewing a peanut butter factory manager. In the study, while the criteria weights were determined, PSI and SV methods were used, while the machines were ranked with the MARCOS method. In addition, the MARCOS method was compared with other MCDM methods such as PIV, CODAS and WEDBA methods. After the rankings were found according to the methods, the relations between the rankings were examined using the Spearman Correlation method. The main purpose of the study is to determine the suitable butter machine for a peanut paste production factory. Contribution of this study to the literature PSI, SV and MARCOS methods were used together for the first time. In addition, no study has been found in the literature related to peanut butter machine. Therefore, this study is original and contributes to the literature.en_US
dc.identifier.doi10.3233/KES-230044
dc.identifier.endpage86en_US
dc.identifier.issn1327-2314
dc.identifier.issn1875-8827
dc.identifier.issue1en_US
dc.identifier.startpage73en_US
dc.identifier.urihttps://doi.org/10.3233/KES-230044
dc.identifier.urihttps://hdl.handle.net/11616/104093
dc.identifier.volume27en_US
dc.identifier.wosWOS:001029119100004en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherIos Pressen_US
dc.relation.ispartofInternational Journal of Knowledge-Based and Intelligent Engineering Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMachine selectionen_US
dc.subjectmulti-criteria decision makingen_US
dc.subjectMARCOS methoden_US
dc.titleSelection of peanut butter machine by the integrated PSI-SV-MARCOS methoden_US
dc.typeArticleen_US

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