Data Driven Performance Prediction in Steel Making

Autor: Fernando Boto, Maialen Murua, Teresa Gutierrez, Sara Casado, Ana Carrillo, Asier Arteaga

Publikováno v: Metals, Vol 12, Iss 2, p 172 (2022)

This work presents three data-driven models based on process data, to estimate different indicators related to process performance in a steel production process. The generated models allow the optimization of the process parameters to achieve optimal

Externí odkaz: https://doaj.org/article/e41c218eacf3446ca4fe6d7f5755e383

Tool-Path Problem in Direct Energy Deposition Metal-Additive Manufacturing: Sequence Strategy Generation

Autor: Roberto Santana, Diego Galar, Maialen Murua, Alfredo Suárez

Publikováno v: TECNALIA Publications
Fundación Tecnalia Research & Innovation
Addi. Archivo Digital para la Docencia y la Investigación
instname
IEEE Access, Vol 8, Pp 91574-91585 (2020)
IEEE Access
Addi: Archivo Digital para la Docencia y la Investigación
Universidad del País Vasco

The tool-path problem has been extensively studied in manufacturing technologies, as it has a considerable impact on production time. Additive manufacturing is one of these technologies; it takes time to fabricate parts, so the selection of optimal t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::db5a9c28a9d28f13d850975aaa22fc0b
http://hdl.handle.net/11556/930

Feature extraction-based prediction of tool wear of Inconel 718 in face turning

Autor: Roberto Santana, Alfredo Suárez, Anders Wretland, Maialen Murua, L.N. López de Lacalle

Publikováno v: TECNALIA Publications
Fundación Tecnalia Research & Innovation

Tool wear is a recurring topic in the cutting field, so obtaining knowledge about the tool wear process and the capability of predicting tool wear is of special importance. Cutting processes can be optimised with predictive models that are able to fo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d45e736e063101bf98af313c6a46ae50
http://hdl.handle.net/11556/616

MOTOR DE ANÁLISIS BASADO EN TÉCNICAS DE APRENDIZAJE AUTOMÁTICO PARA LA IDENTIFICACIÓN DE VARIABLES CRÍTICAS EN PROCESOS MULTIETAPA: APLICACIÓN A LA INSTALACIÓN DE REMACHES CIEGOS

Autor: Maialen Murua, Fernando Veiga Suarez, Juan Antonio Ortega Lalmolda, Alberto Diez Olivan, Mariluz Penalva Oscoz

Publikováno v: Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
instname
TECNALIA Publications
Fundación Tecnalia Research & Innovation
DYNA

Quality control in manufacturing is a recurrent topic as the ultimate goals are to produce high quality products with less cost. Mostly, the problems related to manufacturing processes are addressed focusing on the process itself putting aside other

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d11a3a8a009317893c1b5f463630da1a