dc.date.accessioned2018-09-04T20:23:52Z
dc.date.available2018-09-04T20:23:52Z
dc.date.created2018-09-04T20:23:52Z
dc.date.issued2013
dc.identifierhttp://hdl.handle.net/10533/219765
dc.identifier1131105
dc.identifierWOS:000317817700001
dc.description.abstractThis paper discusses the development and evaluation of an estimation model of manufacturing costs of piping elements through the application of a Reduced Multivariate Polynomial (RMP). The model allows obtaining accurate estimations, even when enough and adequate information is not available. This situation typically occurs in the early stages of the design process of industrial products. The experimental evaluations show that the approach is capable, with a low complexity, of reducing uncertainties and to predict costs with significant precision. Comparisons with a neural network showed also that the RMP performs better considering a set of classical performance measures with the corresponding lower complexity and higher accuracy. Keywords. KeyWords Plus:REWEIGHTED LEAST-SQUARES; NEURAL-NETWORKS; REGRESSION; ALGORITHM; PRODUCT; SYSTEM
dc.languageeng
dc.relationhttps://www.hindawi.com/journals/mpe/2013/765956/
dc.relation10.1155/2013/765956
dc.relationinfo:eu-repo/grantAgreement//1131105
dc.relationinfo:eu-repo/semantics/dataset/hdl.handle.net/10533/93477
dc.relationinstname: Conicyt
dc.relationreponame: Repositorio Digital RI2.0
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Chile
dc.titleReduced Multivariate Polynomial Model for Manufacturing Costs Estimation of Piping Elements
dc.typeArticulo


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