Additive Manufacturing: Materials, Alloy Development, Microstructure and Properties: Additive Manufacturing of Al- and Ti-based Alloys
Program Organizers: Prashanth Konda Gokuldoss, Tallinn University of Technology; Zhi Wang, South China University of Technology; Jurgen Eckert, Erich Schmid Institute of Materials Science; Filippo Berto, Norwegian University of Science and Technology
Wednesday 8:00 AM
November 4, 2020
Room: Virtual Meeting Room 3
Location: MS&T Virtual
Session Chair: Sudhakar Vadiraja, Montana Tech
8:00 AM Invited
Additive Manufacturing of Metallic Materials: Mechanical Properties: Prashanth Konda Gokuldoss1; 1Tallinn University Of Technology
Laser-based powder bed fusion processes like the selective laser melting (SLM) produces 3-D metal parts by selective melting of powders dictated by CAD data. Because of the high degree of freedom, it is possible to build parts with extremely complex geometries that would otherwise be difficult or impossible to produce using conventional manufacturing processes. However, until now, only conventional alloys like the AlSi10Mg, 316L, Ti6Al4V, etc. that either is developed for cast or wrought processes have been used for fabrication. Some of the alloys work well for the additive manufacturing process like the Al12Si, AlSi10Mg because they have good fluidity and are readily weldable. Nevertheless, most of the materials fabricated by SLM show superior mechanical properties than their case counterparts. Even though superior mechanical properties were recorded, there are reports showing the premature failure of the materials and the reasons will be discussed in detail.
8:20 AM
Microstructural Evolution and Mechanical Properties of Cast and Additive Manufactured AlSi10Mg at Different Heat-treated Conditions: Shawkat Imam1; Ahmed Paridie1; Meysam Haghshenas1; 1University of Toledo
This study aims at assessing the effect of solution heat treatment (at a temperature just below the eutectic temperature) followed by various cooling rates on microstructure and the mechanical properties, employing a depth-sensing nanoindentation platform, of additively manufactured AlSi10Mg and the cast counterpart. To this end, cast and additively manufactured parts were solutionized at 520°C for 2 h followed by water quenching, air cooling, and furnace cooling. Results show extensive evolutions in the microstructure (e.g. size and morphology of eutectic-silicon phase) and the mechanical properties of the heat-treated materials relative to the as-printed and as-cast materials. Upon solutionizing treatment, the eutectic-silicon is first fragmented, then spheroidized, and finally coarsened when cooled with slow rates. The microstructural evolution directly affects the mechanical properties of the studied materials. The results of this study provide insights into the control of microstructure and hence mechanical properties of AlSi10Mg alloy by addressing suitable heat treatment.
8:40 AM
Microstructure and Mechanical Property of Additively Manufactured Zr-modified AA6061 Alloy: Le Zhou1; Abhishek Mehta1; Holden Hyer1; Thinh Huynh1; Sharon Park1; Devin Imholte2; Nicolas Woolstenhulme2; Daniel Wachs2; Yongho Sohn1; 1University of Central Florida; 2Idaho National Laboratory
Aluminum alloy (AA) 6061 suffered from solidification cracking when manufactured by laser powder bed fusion (LPBF) regardless of processing parameters. To improve its printability without challenging the equipment, AA6061 is modified by alloying with 1wt.% of Zr. In this work, powders of AA6061 and AA6061+Zr were gas atomized and used to manufacture samples by LPBF for microstructural characterization and mechanical testing. Cracks were eliminated for AA6061+Zr samples at all processing parameters. Large columnar grains observed in AA6061 samples were disrupted with Zr addition, and fine columnar and equiaxed grains formed in the AA6061+Zr alloy. The as-built AA6061+Zr with nearly-full density exhibited a yield stress of 210MPa and fracture strain of 27%. After T6 heat treatment, the yield stress improved to 300MPa while fracture strain was 14%, which is slightly better than conventional T6 AA6061 alloy. Microstructure and mechanical properties were correlated to the processing parameters and heat treatment.
9:00 AM
Toward In-Situ Flaw Detection in Laser Powder Bed Fusion Additive Manufacturing: Brett Diehl1; Zackary Snow1; Abdalla Nassar1; Edward Reutzel1; 1Applied Research Laboratory, Pennsylvania State University
Process monitoring in additive manufacturing should allow components to be certified cheaply and rapidly and opens the possibility of healing defects, if detected. Here, neural networks (NNs) and convolutional neural networks (CNNs) are trained to detect flaws in layerwise images of a build, using labeled XCT data as a ground truth. Multiple images were recorded after each layer before and after recoat with various lighting conditions. Classifying networks were given a single image or multiple images of various lighting conditions for training and testing. CNNs demonstrated significantly better performance than NNs when testing and training on data from the same component. CNNs also performed better when training on all data available from one build, and testing on data from an unseen build. CNNs demonstrated accuracies of 93% when testing and training within the same component, and 79% when testing on a previously unseen build. CNNs were demonstrated to have superior generalizability compared to NNs. As well, data fusion techniques were shown to raise the out of class accuracy to 83%. It was determined that the size of voids was a strong determining factor in whether they can be detected with these classifiers in layerwise imagery; classifiers trained on only large voids were able to achieve out of class accuracy of 87%.
9:20 AM
Mapping Relationships between Process Parameters, Microstructure, and Properties for Wire Feed – DED of Ti-6Al-4V: Ze Geng1; Zhening Yang1; Ali Guzel1; Amit Verma1; Anthony Rollett1; 1Carnegie Mellon University
Wire-feed direct energy deposition (WFDED) is an up-and-coming AM method because of its high deposition rates and flexible application. However, operating parameters in WFDED are not independent and the microstructure of the as-built part is hard to predict. To extend its application, it is crucial to find a way to predict the microstructure of as-built parts. In this work, we analyzed both Ti-6Al-4V single-bead and stacked-bead samples made with various power levels and speeds. Moreover, microstructure characterization and hardness measurements are correlated with the operating parameters. Multiple informatics methods are applied to the dataset to map the < process | microstructure | properties > relationships for better control of final microstructure/properties. The analysis provides insights into the scope of data analytics methods for quantifying process uncertainty.