AI and Simulation-Driven Design for Advanced Manufacturing by Altair

Develop High Quality Defect Free Additive Manufacturing Parts through Design (DfAM), Machine Learning and Data Science.

Simon Zwingert

- Simulation Driven Design
- Machine Learning & AI for Design Engineering

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Design for additive manufacturing (DfAM)

Design for additive manufacturing (DfAM) is becoming key to exploit the freedoms of additive manufacturing (AM) while adhering to the process limitations. A good understanding includes: designing a part for the appropriate AM process, for minimal usage, for improved functionality and for part Consolidation. Here, the DfAM principles are elaborated, and its applications are demonstrated on industrial cases involving SLM process leading to lightweight designs and improvement of performances.

Application of machine learning

Application of machine learning is demonstrated on SLM process to build Artificial Intelligence – based solution AI for real-time melt-pool analytics for accelerated product development and production

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16 april 2024
NH Conference Centre Koningshof, Locht 117, 5504 RM Veldhoven

The aim of this Manufacturing Technology Conference is to bring together technicians from the design and manufacturing industry to share knowledge about manufacturability. With this annual Manufacturing Technology Conference, we increase knowledge about manufacturability for developers and help them look for possibilities that were previously unknown.

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