Design and Analysis of Cpm and Cpmk Indices for Uncertainty Environment by Using Pythagorean Fuzzy Sets

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dc.contributor.authorYalcin S.
dc.contributor.authorKaya I.
dc.date.accessioned2024-03-13T10:00:55Z
dc.date.available2024-03-13T10:00:55Z
dc.date.issued2022
dc.departmentİstanbul Beykent Üniversitesien_US
dc.description2022 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2022 -- 20 November 2022 through 21 November 2022 -- -- 185700en_US
dc.description.abstractProcess capability analysis (PCA) is a statistical analysis tool to examine variability of the process that causes faults for outputs and reduces customer satisfaction level. So, it is a completely effective method to improve the process' quality. One of the effective methods is process capability indices (PCIs) that are used to analyze the capability of any process by using specification limits (SLs) and process' variation. Especially in real case problems, there are many factors that causing uncertainty for the process. Although traditional PCIs are effective tools to analyze variation of process, they caused some misleading results and incorrect interpretations when the process has uncertainties. To overcome the problem, the PCIs have been re-designed under uncertainty to increase their effectiveness by using fuzzy sets (FSs). In recently, some fuzzy set extensions (FSEs) have been derived to deal with uncertainty and they can model uncertainties of process more effectively. In this paper, Pythagorean Fuzzy Sets (PFSs), one of the most common FSEs, are used to analyze process capability bu improving some PCIs based on PFSs. For this aim, generally used PCIs called Cpm and Cpmk are re-designed by using PFSs as the first time in the literature. The mathematical structures of these two indices are re-formulated and PCIs based on PFSs (PFPCIs) have been derived. Additionally, an application related with dimensions of a gear for a piston is also applied to analyze usage of proposed PFPCIs. The obtained results confirmed that the indices Cpm and Cpmk based on PFSs are more capable for modelling uncertainty and give more information and have more sensitiveness than the traditional PCIs. © 2022 IEEE.en_US
dc.identifier.doi10.1109/3ICT56508.2022.9990663
dc.identifier.endpage297en_US
dc.identifier.isbn9781665451932
dc.identifier.scopus2-s2.0-85146416964
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage293en_US
dc.identifier.urihttps://doi.org/10.1109/3ICT56508.2022.9990663
dc.identifier.urihttps://hdl.handle.net/20.500.12662/2855
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2022 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2022en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectfuzzy set extensionsen_US
dc.subjectProcess capability analysisen_US
dc.subjectprocess capability indicesen_US
dc.subjectPythagorean fuzzy setsen_US
dc.subjectquality improvementen_US
dc.titleDesign and Analysis of Cpm and Cpmk Indices for Uncertainty Environment by Using Pythagorean Fuzzy Setsen_US
dc.typeConference Objecten_US

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