With guest speaker from Lawrence Livermore National Lab
Additive Manufacturing is a transformational technology – delivering lighter, stronger parts, and novel product capabilities. But it is a major challenge to ensure repeatable AM processes and quality parts with minimal defects. There is a high reliance on costly, time-consuming experimentation and prototyping. In this webinar, we explore how machine learning is being applied to tackle this problem. Gabe Guss of Lawrence Livermore National Labs presents work on applying the Alchemite™ machine learning method to predict and optimise print parameters for additively-manufactured parts. The Intellegens team discuss how such work has been proven to reduce experimental workloads while supporting better AM project outcomes. The session includes a live demonstration of the Alchemite™ software and an interactive Q&A.
- Data-driven Additive Manufacturing with Intellegens
- Case study – Project MEDAL with Boeing, GE Additive, Constellium
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