Two-Dimensional Uncertainty Analysis for Cp and Cpk Process Capability Indices

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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 an efficient statistical technique for calculating of process' ability to meet predetermined specification limits (SLs) that defined by customer, engineers or designers. Measurements and evaluations for PCA may be vague, incomplete or inaccurate in the real-case problems. In that cases, the process capability should be successfully measured by using fuzzy set extensions to model uncertainties of the process. One of fuzzy set extensions named Pythagorean fuzzy Sets (PFSs) that also contains the non-membership function can be employed as an effective tool to model uncertainty better than traditional fuzzy sets (TFSs). In this paper, a novel approach based on PFSs is suggested to increase flexibility and sensitivity of the PCA and to successfully model the uncertainties. For this aim, two of frequently used process capability indices (PCIs) Cp and Cpk, are analyzed based on PFSs. Then, the Pythagorean fuzzy process capability indices (PFPCIs) have been derivate respectively for the indices Cp and Cpk and the mathematical backgrounds of these indices have been developed for the first time in the literature. Additionally, the proposed indices Cp and Cpk have been applied to a real case problem from manufacturing industry. The obtained PCIs based on PFSs provide some additional flexibility and information about the process since they better modeled process uncertainty. Moreover, it is demonstrated that the proposed PFCPIs can be effectively applied on process to manage PCA. © 2022 IEEE.en_US
dc.identifier.doi10.1109/3ICT56508.2022.9990896
dc.identifier.endpage423en_US
dc.identifier.isbn9781665451932
dc.identifier.scopus2-s2.0-85146440308en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage419en_US
dc.identifier.urihttps://doi.org/10.1109/3ICT56508.2022.9990896
dc.identifier.urihttps://hdl.handle.net/20.500.12662/2856
dc.indekslendigikaynakScopusen_US
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.subjectprocess capability analysisen_US
dc.subjectPythagorean fuzzy process capability indicesen_US
dc.subjectPythagorean fuzzy setsen_US
dc.titleTwo-Dimensional Uncertainty Analysis for Cp and Cpk Process Capability Indicesen_US
dc.typeConference Objecten_US

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