Data analysis to assess part quality in DED-LB/M based on in-situ process monitoring

Pilar Rey (1) , Camilo Prieto (1) , Carlos González (1) , Konstantinos Tzimanis (2) , Thanassis Souflas (2) , Panagiotis Stavropoulos (2) , Jitendra Singh Rathore (3) , Vincent Bergeaud (4) , Caroline Vienne (3) , Philippe Bredif (3)

1 AIMEN Technology Centre, Polígono Industrial de Cataboi SUR-PPI-2 (Sector) 2, Parcela 3, O Porriño, E36418, Spain
2 Laboratory for Manufacturing Systems and Automation (LMS), University of Patras, Rio, Patras 26504, Greece
3 LMC (CEA, LIST) - Laboratoire Méthodes CND (CEA, LIST)
4 LDI - Laboratoire Développement Informatique

Mots clés: in-situ monitoring Direct Energy Deposition Additive Manufacturing data analytics part quality; in-situ monitoring; Direct Energy Deposition; Additive Manufacturing; data analytics; part quality

Domaines: Sciences de l'ingénieur [physics]; Matériaux

Pilar Rey, Camilo Prieto, Carlos González, Konstantinos Tzimanis, Thanassis Souflas, et al.. Data analysis to assess part quality in DED-LB/M based on in-situ process monitoring. Procedia CIRP, 2022, 111, pp.345-350. ⟨10.1016/j.procir.2022.08.036⟩. ⟨hal-04548538⟩