Melt Pool Area Control in Directed Energy Deposition Using Iterative Learning Control and Substrate Pre-heating*

Le résumé fourni par la source

This paper proposes an Iterative Learning Control (ILC) algorithm to determine the laser power input during the deposition of each layer, in order to regulate the m0065lt pool area (MPA) in the Directed Energy Deposition (DED) metal additive manufacturing process. Based on the laser power applied and the corresponding MPA error obtained experimentally, the ILC algorithm updates the laser power so that the MPA error is reduced in the next iteration. It turns out that, even with the well-tuned ILC algorithm, the MPA error persists in lower layers due to the heat dissipation properties of the cold substrate. As a remedy of this issue, the substrate pre-heating strategy is introduced. The combination of the ILC algorithm with the substrate pre-heating shows the potential in minimizing the MPA error across all the layers of the deposited part, thereby enhancing the quality in DED process.

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