Please use this identifier to cite or link to this item: http://ir.library.ui.edu.ng/handle/123456789/2036
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dc.contributor.authorAdeyeye, D. A.-
dc.contributor.authorOyawale, F. A.-
dc.date.accessioned2018-10-11T10:40:53Z-
dc.date.available2018-10-11T10:40:53Z-
dc.date.issued2008-
dc.identifier.issn1678-5878-
dc.identifier.otherJournal of the Brazilian Society of Mechanical Sciences and Engineering 30(4)-
dc.identifier.otherui_art_adeyeye_mixture_2008-
dc.identifier.urihttp://ir.library.ui.edu.ng/handle/123456789/2036-
dc.description.abstractThe traditional welding flux development has been by cost, material, time and labour intensive experiments. The extensive and expensive trial and error experimentation is needed because it is often difficult to know a priori how the flux ingredients interact to determine the operational characteristics of the flux and the final performance of the welded structure. The limitation of the traditional approach includes: (1) long lead-time (2) expensive experiments in terms of materials and energy consumption and labour requirements (3) the flux developed can not be guaranteed to be optimal and (4) inability to identify and quantify direct and interaction effects of flux ingredients. These constraints are due to the paucity of statistical modelling tools in welding flux technology. Since prediction models are derived from designed experiments, flux researchers need other methods by which flux experiments may be designed. This paper discusses a statistical modelling tool known as mixture experiment which has the potential to revolutionize welding flux development technology. Mixture design is discussed but not fully developed. The procedure of mixture experiment, analytical model forms and the sequence of model fitting are discussed. Areas of welding flux research where the various mixture designs may be useful are suggested.en_US
dc.language.isoenen_US
dc.publisherAssociação Brasileira de Engenharia e Ciências Mecânicas - ABCMen_US
dc.subjectmixture experimentsen_US
dc.subjectwelding fluxen_US
dc.subjectprediction modelen_US
dc.subjectoptimizationen_US
dc.titleMixture Experiments and their applications in welding flux designen_US
dc.typeArticleen_US
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