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How to Tune Machine Settings to Optimize Industrial Metal Additive Manufacturing

Additive Science helps engineers optimize the melt pool and print porosity of a metal additive manufacturing machine.

Setting up an industrial metal additive manufacturing machine traditionally requires a lot of trial and error. Engineers need to ensure that their parts print correctly both internally and externally.

ANSYS Additive Suite helps engineers ensure their parts print properly the first time. However, this assessment focuses on designing the part to minimize deformations and internal stresses. It doesn’t look into how the 3D printer settings could affect the materials.

If the 3D printer settings create a melt pool that is too large or too small, then engineers may not get the results they need. Additionally, if the part has the wrong porosity, it won’t have material properties that engineers intended.

This is where ANSYS Additive Science comes into play. The tool uses machine parameters and material properties in order to help engineers optimize the melt pool and print porosity of their metal additive manufacturing machine.

How Single Bead Simulations Optimize a Metal Additive Manufacturing Machine’s Resolution

“Single bead simulations model one pass of a laser over the metal powder layer. This simulation gives the engineer an idea of the melt pool dimensions produced by the additive manufacturing machine,” said Zack Francis, a software developer for ANSYS’ additive manufacturing technology.

The user interface of Additive Science’s single bead simulation. Users input variables into a questionnaire and the software runs a parametric study based on the inputs.

The melt pool’s dimensions define the smallest print resolution of a metal additive manufacturing machine.

By cycling through a series of printer settings, such as the laser’s power and speed, engineers can weigh the trade-offs between different outcomes like resolution and build rate.

The melt pool will also be affected by the base plate temperature, layer thickness and alloy. Additive Science takes all of these inputs into consideration when running the single bead simulation. The final input that Additive Science needs is the bead length, which dictates the length of the simulation.

Engineers can also set Additive Science to automatically cycle through a series of single bead simulations based on an array of input parameters. This will help the engineer find optimal 3D printer settings faster than if they manually cycled through the simulation or physical tests.

How to Optimize the Porosity of Metal Additive Manufactured Parts

“Now that the engineers have settled on a melt pool, the next step is to ensure that the 3D printer settings will produce a solid build or an acceptable level of porosity,” said Francis.

Experimental porosity results found from two different parameter settings on a metal additive manufacturing machine.

To run a porosity simulation on Additive Science, engineers first have to set the dimensions of the simulated test print. Engineers then input a series of 3D printer settings, such as:

  • Hatch spacing.
  • Layer rotation angle.
  • Starting layer angle.
  • Slicing stripe width.

Additive Science will also need the optimal inputs that were found in the single bead simulation to run the porosity simulation. These parameters include:

  • Material.
  • Base plate temperature.
  • Layer thickness.
  • Laser power.
  • Laser speed.

Once again, engineers can input the porosity simulation variables as an array of input parameters to speed up the optimization of the metal additive manufactured machine.

Once the simulation is completed, Additive Science will predict the test print’s void ratio, powder ratio and solid ratio. Engineers can then use this data to fully optimize the 3D printer settings.

To learn more about how to optimize 3D printer settings, watch the webinar: Metal Additive Manufacturing Simulation Using ANSYS Solutions Featuring the New Additive Science Tool. Or learn about the capabilities of ANSYS Additive Science.