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Meeting 2027 TMS Annual Meeting & Exhibition
Symposium AI-Enabled Materials Processing: Integrating Accelerated Experimental Workflows and Processing-Aware Machine Learning
Presentation Title Uncertainty-Aware Processing and Heat Treatment Design of Laser Powder Additive Manufactured Alloys
Author(s) S. Mohadeseh Taheri-Mousavi
On-Site Speaker (Planned) S. Mohadeseh Taheri-Mousavi
Abstract Scope Additive manufacturing provides new opportunities for alloy design. However, realization of computational designs requires processing design of alloys to robustly validate predictions in experiments. I will show two case studies that an uncertainty aware machine learning techniques could accelerate the processing design of additive manufactured alloys. First, I will show how combination of generative AI, sensitivity analyses, and uncertainty quantification can reliably design the heat treatment of Ni based superalloys to achieve robust strength in experiments. Second, I will show how combining Bayesian optimization with high throughput laser scanning of casted aluminum alloys could accelerate the processing and composition design of laser powder additive manufactured Al alloys. I will talk about challenges and opportunities to use this technique so that the down-selected compositions achieve enhanced properties in printed alloys from custom powder.
Proceedings Inclusion? Planned:
Keywords Additive Manufacturing, Machine Learning, Mechanical Properties

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