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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Sign up for the Manufacturing Technology Conference 2100

01 january 2100
Brainport Industries Campus BIC 1 5657BX

Quality control is extremely important and should be given attention from the very beginning of the design.

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