Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/18788
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dc.contributor.authorKolarevic, Milan-
dc.contributor.authorRasinac, Mladen-
dc.contributor.authorMinić, Duško-
dc.contributor.authorĐorđević, Aleksandar-
dc.contributor.editorMinić, Duško-
dc.date.accessioned2023-09-06T06:34:00Z-
dc.date.available2023-09-06T06:34:00Z-
dc.date.issued2023-
dc.identifier.isbn978-86-81656-63-1en_US
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/18788-
dc.descriptionTPD 2023en_US
dc.description.abstractResponse surface methodology, or RSM, is a collection of mathematical and statistical techniques useful for the modeling and analysis of problems in which a response of interest is influenced by several variables and the objective is to optimize this response. In mixture experiments, the factors are the components or ingredients of a mixture, and consequently their levels are not independent. For example, if x1, x2, . . . , xp denote the proportions of p components of a mixture, then 0 ≤ xi ≤ 1 i = 1, 2, . . . , p and x1 + x2 + · · · + xp = 1 (i.e., 100 percent) This paper presents the RA-TeS software for RSM of three-component mixture systems developed at Faculty of Mechanical and Civil Engineering in Kraljevo. The fitted models are analyzed to assess their adequacy and to determine the significance of the model terms. This involves conducting analysis of variance (ANOVA) to test the statistical significance of the factors and their interactions. The optimized levels of the mixture components are determined based on the fitted models and the desired response. Optimization techniques, such as RSM, are employed to find the optimal factor settings that maximize or minimize the response variable. Overall, Response Surface Methodology for Mixture Experiments provides a systematic approach for studying and optimizing mixture processes. It allows for efficient exploration of the factor space, modeling of the relationship between mixture components and response variables, and identification of optimal factor settings to achieve desired outcomes.en_US
dc.description.sponsorshipThe Ministry of Science, Technological Development and Innovation of the Republic of Serbia - contract record number: 451-03-47/2023-01/200108en_US
dc.description.urihttps://ftn.pr.ac.rs/en_US
dc.language.isosren_US
dc.publisherFakultet Tehničkih nauka Kosovska Mitrovicaen_US
dc.rightsinfo:eu-repo/semantics/openAccess-
dc.sourceJedanaesti simpozijum o termodinamici i faznim dijagramimaen_US
dc.subjectResponse surface methodologyen_US
dc.subjectOptimizationen_US
dc.subjectMixture experimentsen_US
dc.subjectAnalysis of varianceen_US
dc.subjectRegresion analysisen_US
dc.titleRA-TeS Software for Response Surface Methodology of the Mixture Experimentsen_US
dc.typeconferenceObjecten_US
dc.description.versionPublisheden_US
dc.type.versionPublishedVersionen_US
Appears in Collections:Faculty of Mechanical and Civil Engineering, Kraljevo

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