2026-05-31T14:30:37Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/63582022-11-30T11:20:09Zcom_10259_6336com_10259_6335com_10259.4_106com_10259_2604com_10259_3830com_10259_5086col_10259_6337col_10259_3832

Martín, Óscar b8e82c82-cd88-4bf9-880d-f98b7f75ec71 600 Ahedo García, Virginia 10 600 0000-0002-9812-388X Santos Martín, José Ignacio 526 600 0000-0002-6653-043X Tiedra, Pilar de 255fb206-89cf-45fb-9e46-5157457d1ece 600 Galán Ordax, José Manuel 188 600 0000-0003-3360-7602 2022-01-25T13:15:38Z 2022-01-25T13:15:38Z 2016-10 0921-5093 http://hdl.handle.net/10259/6358 10.1016/j.msea.2016.08.112 In this work, the quality of resistance spot welding (RSW) joints of 304 austenitic stainless steel (SS) is assessed from its tensile shear load bearing capacity (TSLBC). A predictive model using a polynomial expansion of the relevant welding parameters, i.e. welding current (WC), welding time (WT) and electrode force (EF) and elastic net regularization is proposed. The predictive power of the elastic net approach has been compared to artificial neural networks (ANNs), previously used to predict TSLBC, and smoothing splines in the framework of a generalized additive model. The results show that the predictive and classification error of the elastic net model are statistically comparable to benchmarks of the best pattern recognition tools whereas it overcomes correlation problems and performs variable selection at the same time, resulting in a simpler and more interpretable model. These features make the elastic net model amenable to be used in the design of welding conditions and in the control of manufacturing processes. Spanish MICINN Project CSD2010-00034 (SimulPast CONSOLIDER-INGENIO 2010). application/pdf eng Elsevier Materials Science and Engineering: A. 2016, V. 676, p. 173-181 https://doi.org/10.1016/j.msea.2016.08.112 info:eu-repo/grantAgreement/MICINN/Plan Estatal de Investigación Científica y Técnica y de Innovación 2008-2011/CSD2010-00034/ES/Social and environmental transitions: simulating the past to understand human behaviour Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess Resistance spot welding AISI 304 stainless steel Tensile shear load bearing capacity Quality assessment Elastic nets Smoothing splines Ingeniería mecánica Materiales Mechanical engineering Materials Quality assessment of resistance spot welding joints of AISI 304 stainless steel based on elastic nets info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Materials Science and Engineering: A 676 173 181 THUMBNAIL Martin-msea_2016.pdf.jpg Martin-msea_2016.pdf.jpg IM Thumbnail image/jpeg 4425 https://riubu.ubu.es/bitstream/10259/6358/4/Martin-msea_2016.pdf.jpg b6fce431303a54833092df5c5b72a248 MD5 4 LICENSE license.txt license.txt text/plain; charset=utf-8 999 https://riubu.ubu.es/bitstream/10259/6358/3/license.txt b295bcbce42e2caabeb0c623d3860c06 MD5 3 CC-LICENSE license_rdf license_rdf application/rdf+xml; charset=utf-8 805 https://riubu.ubu.es/bitstream/10259/6358/2/license_rdf 4460e5956bc1d1639be9ae6146a50347 MD5 2 ORIGINAL Martin-msea_2016.pdf Martin-msea_2016.pdf application/pdf 1076375 https://riubu.ubu.es/bitstream/10259/6358/1/Martin-msea_2016.pdf 24ddfa88e76daa731d25d3176e9201ba MD5 1 10259/6358 oai:riubu.ubu.es:10259/6358 2022-11-30 12:20:09.876 Repositorio Institucional de la Universidad de Burgos bubrep@ubu.es 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