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CIRP Journal of Manufacturing Science and Technology(1)
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https://rdcu.be/cd80a(1)
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Ingeniería y operaciones afines(4)
Instrumentos de precisión y otros dispositivos(4)
Métodos informáticos especiales(4)
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Comparative Evaluation of Machine Learning Regressors for the Layer Geometry Pbkp_rediction in Wire arc Additive manufacturing
OtherAbstract: In this paper, a set of the most employed machine learning (ML) algorithms were trained and tested tPalabras claves:Autores:Germán Omar Barrionuevo ChiluizaFuentes:googleComparative analysis and experimental validation of statistical and machine learning-based regressors for modeling the surface roughness and mechanical properties of 316L …
OtherAbstract: This article analyzes the surface roughness and mechanical properties of 316L samples produced by SePalabras claves:Autores:Germán Omar Barrionuevo ChiluizaFuentes:googleComparative evaluation of supervised machine learning algorithms in the pbkp_rediction of the relative density of 316L stainless steel fabricated by selective laser melting
OtherAbstract: To find a robust combination of selective laser melting (SLM) process parameters to achieve the highPalabras claves:Autores:Germán Omar Barrionuevo ChiluizaFuentes:googleA machine learning approach for the pbkp_rediction of melting efficiency in wire arc additive manufacturing
OtherAbstract: Wire arc additive manufacturing (WAAM) appears as one of the most promising technologies due to itsPalabras claves:Autores:Germán Omar Barrionuevo ChiluizaFuentes:googleMicrohardness and wear resistance in materials manufactured by laser powder bed fusion: Machine learning approach for property pbkp_rediction
ArticleAbstract: Laser-based powder bed fusion (LPBF) technology is one of the most applied additive manufacturing prPalabras claves:Laser powder-bed-fusion, Machine learning, Microhardness, pbkp_rediction, Processing parameters, WearAutores:Barrionuevo G.O., Germán Omar Barrionuevo Chiluiza, Ramos-Grez J.A., Walczak M., Xavier Sánchez-SánchezFuentes:googlescopusPbkp_redicting the Ultimate Tensile Strength of AISI 1045 steel and 2017-T4 aluminum alloy joints in a laser-assisted rotary friction welding process using Machine learning: a …
OtherAbstract: Welding metal alloys with dissimilar melting points makes conventional welding processes not feasiblPalabras claves:Autores:Germán Omar Barrionuevo ChiluizaFuentes:google