Abstract
Additive Manufacturing (AM) processes are widely used to create complex three-dimensional products by depositing material layer by layer. This approach contrasts significantly with subtractive manufacturing processes, where material is removed to shape the final product. In wire-arc directed energy deposition (wa-DED), a generative scheme is employed to build parts from the base up using power supplied by a welding arc. When optimizing wa-DED processes, it is crucial to predict welding power, deposition speed, and thermal history to enable accurate modeling of the process. These parameters are typically predicted based on material properties, part geometry, deposition method, and the limitations of the printing machine.
| Original language | English |
|---|---|
| Title of host publication | Proceeding of SIM-AM 2025 Conference |
| Publisher | Scipedia S.L |
| Publication status | Published - 11 Sept 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Research Field
- Numerical Simulation of Lightweight Components and Processes
Keywords
- AI-based predictive models
- Additive manufacturing
- Process modelling
- Real-time models
- Power prediction
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