Finite Mixture Model-Based Analysis of Yarn Quality Parameters

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dc.authoridKoyuncu, Melik/0000-0003-0513-6276
dc.authoridKaraka�, Esra/0000-0002-8333-3091
dc.contributor.authorKarakas, Esra
dc.contributor.authorKoyuncu, Melik
dc.contributor.authorUkelge, Mulayim Ongun
dc.date.accessioned2026-02-27T07:33:09Z
dc.date.available2026-02-27T07:33:09Z
dc.date.issued2025
dc.description.abstractThis study investigates the applicability of finite mixture models (FMMs) for accurately modeling yarn quality parameters in 28/1 Ne ring-spun polyester/viscose yarns, focusing on both yarn imperfections and mechanical properties. The research addresses the need for advanced statistical modeling techniques to better capture the inherent heterogeneity in textile production data. To this end, the Poisson mixture model is employed to represent count-based defects, such as thin places, thick places, and neps, while the gamma mixture model is used to model continuous variables, such as tenacity and elongation. Model parameters are estimated using the expectation-maximization (EM) algorithm, and model selection is guided by the Akaike and Bayesian information criteria (AIC and BIC). The results reveal that thin places are optimally modeled using a two-component Poisson mixture distribution, whereas thick places and neps require three components to reflect their variability. Similarly, a two-component gamma mixture distribution best describes the distributions of tenacity and elongation. These findings highlight the robustness of FMMs in capturing complex distributional patterns in yarn data, demonstrating their potential in enhancing quality assessment and control processes in the textile industry.
dc.identifier.doi10.3390/app15126407
dc.identifier.issn2076-3417
dc.identifier.issue12
dc.identifier.urihttp://dx.doi.org/10.3390/app15126407
dc.identifier.urihttps://hdl.handle.net/20.500.14669/4448
dc.identifier.volume15
dc.identifier.wosWOS:001515114100001
dc.indekslendigikaynakWeb of Science
dc.language.isoen
dc.publisherMDPI
dc.relation.ispartofApplied Sciences-Basel
dc.relation.publicationcategoryMakale - Uluslararas� Hakemli Dergi - Kurum ��retim Eleman�
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20260302
dc.subjectfinite mixture model
dc.subjectexpectation-maximization algorithm
dc.subjectPoisson mixture
dc.subjectgamma mixture
dc.subjectyarn quality
dc.titleFinite Mixture Model-Based Analysis of Yarn Quality Parameters
dc.typeArticle

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