Automatised quality assessment in additive layer manufacturing using layer-by-layer surface measurements and deep learning - Roux, Léopold Le; Liu, Chao; Ji, Ze; Kerfriden, Pierre; Gage, Daniel; Feyer, Felix; Körner, Carolin; Bigot, Samuel (Procedia CIRP, 2021)
Additive manufacturing (AM) has gained high research interests in the past but comes with some drawbacks, such as the difficulty to do in-situ quality monitoring. In this paper, deep learning is used on electron-optical images taken during the Electron Beam Melting (EBM) process to classify the quality of AM layers to achieve automatized quality assessment. A comparative study of several mainstream Convolutional Neural Networks to classify the images has been conducted. The classification accuracy is up to 95 %, which demonstrates the great potential to support in-process layer quality control of EBM.And the error analysis has shown that some human misclassification were correctly classified by the Convolutional Neural Networks.
CRIS-Team Scopus Importer:2021-06-04
Keywords: Additive Manufacturing; Artificial Intelligence; Image recognition; Quality control; Transfert learning

Impact of Particle Size Distribution in the Preform on Thermal Conductivity, Vickers Hardness and Tensile Strength of Copper-Infiltrated AISI H11 Tool Steel - Vetter, Johannes; Beneder, Samuel; Kandler, Moritz; Feyer, Felix; Körner, Carolin; Schmidt, Michael (Materials, 2023)
Spontaneous infiltration of a porous preform by a metallic melt provides the potential of generating metal matrix composites (MMCs) with tailored combinations of material properties at low cost. The bulk of tool inserts for injection molding must sustain high mechanical and thermal loads and simultaneously exhibit high thermal conductivity for efficient temperature control of the mold insert. To fulfill these contradictory requirements, AISI H11 tool steel preforms were infiltrated by liquid copper. The impact of the fine powder fraction (0 wt.% to 15 wt.%) blended to a coarse H11 powder in the preform on thermal conductivity, Vickers hardness and tensile strength was elucidated. The thermal conductivity of the composites could be enhanced by a factor of 1.84 (15 wt.% fine powder) and 2.67 (0 wt.% fine powder) with respect to the sintered H11 tool steel. By adding 15 wt.% fine powder to the coarse host powder, the tensile strength and Vickers hardness of the copper-infiltrated steel were 1066.3 ±108.7 MPa and 366 ± 24 HV1, respectively, whereas the H11 tool steel yielded 1368.5 ± 89.3 MPa and 403 ± 17 HV1, respectively. Based on the results obtained, an appropriate particle size distribution (PSD) may be selected for preform preparation according with the requirements of a future mold inser

Increasing the conductivity of aluminium high-pressure die casting alloy AlSi9Cu3Fe (226D) by Sr modification of eutectic and intermetallic phases - Feyer, Felix; Weigand, Michael; Randelzhofer, Peter; Körner, Carolin (Materials Science and Engineering B-Advanced Functional Solid-State Materials, 2025)
High-pressure die casting alloys are currently optimized to have an excellent castability and to fulfil the mechanical properties of the demanded parts. In general the conductivity of these alloys decreases from the efforts to improve the mechanical properties and the castability. Although new components in the mobility and communication sector demand alloys with improved conductivity. Focus of the work is the evaluation of influence of modification on the conductivity and mechanical properties of high-pressure die casting alloy AlSi9Cu3Fe. A new Cu-die design with vacuum assistance which mimics the microstructure of high-pressure die castings on lab scale for high throughput investigation was used. The combination of modification of the Si phase and intermetallic phases morphology and distribution collectively influences the properties of the alloy. The extent of modification is connected to the level of alloying elements and Sr content present. The conductivity is increased by more than 10
Keywords: Al alloys; Si modification; Conductivity; Hardness; High throughput

Influence of Mould Filling and Microstructure on Conductivity in Aluminium High Pressure Die Casting Parts - Feyer, Felix; Randelzhofer, Peter; Körner, Carolin (COMAT 2024, 2024)