Process optimization in advance manufacturing

dc.contributor.advisor	Herrero Villalibre, Saioa
dc.contributor.advisor	Homchaudhuri, Baisravan
dc.contributor.author	Alonso Cuende, Adrián
dc.contributor.other	Master de Ingeniería (Ind902)
dc.contributor.other	Ingeniariako Master (Ind902)
dc.date.accessioned	2024-10-31T18:45:44Z
dc.date.available	2024-10-31T18:45:44Z
dc.date.issued	2024-10-31
dc.identifier.uri	http://hdl.handle.net/10810/70277
dc.description.abstract	This project explores the application of Machine Learning as a tool for parameter tuning in optimal control and optimization problems of additive manufacturing. The primary objective is to increase the yield of metal additive manufactured parts because critical components require special relative densities.	es_ES
dc.language.iso	eng	es_ES
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	machine learning	es_ES
dc.subject	fabricación aditiva	es_ES
dc.title	Process optimization in advance manufacturing	es_ES
dc.type	info:eu-repo/semantics/masterThesis
dc.date.updated	2024-10-16T10:35:42Z
dc.language.rfc3066	es
dc.rights.holder	©2024, el autor
dc.contributor.degree	Master en Ingenieria industrial.Ingeniariako Indsutriala Master	es_ES
dc.identifier.gaurassign	166770-929290