Reporting on the latest case studies and research results in metal 3D printer R&D

Reporting on the latest case studies and research results in metal 3D printer R&D

3rd report: Development of an algorithm for deriving laser conditions for metal power (world first)

This is described as a world first, but in fact this sort of algorithm may have been developed by a competing company for in-house use only. At the least, we can say there is no commercially available laser condition software for metal powder. This sort of algorithm may be an enticing vision for companies trying to newly enter the field, and for metal 3D printer users who are trying to set new metal powder conditions.

The reason why is that setting laser conditions for each metal powder of metal 3D printers likely takes considerable time at each company in the industry. Steps like the following are repeated over and over:

  • Multiple condition settings
  • Shaping of multiple test pieces
  • Testing and evaluating those test pieces

In the course of experiments, laser conditions are varied in a trial-and-error fashion: output (P), velocity (V), pitch (S), etc... Data is created, followed by shaping, and testing/evaluation, and then the process is repeated... Until recently, we have gone through these lengthy processes to find the optimal conditions.
This was a task that took a long time, frequently involved starting over, and was extremely troublesome.

For about eight years, we have engaged in trial-and-error, always wondering: Can’t this process somehow be done more efficiently? Can’t it be simulated on a computer?
Today, if the component information on a metal powder is input, together with other necessary information...

Target values like the following are automatically output:

This enables a major reduction in time.

Four years ago, we discovered a certain relationship, put together tentative formulas, and calculated back from the tentative method. We repeated this trial-and-error experimentation for a few years, and derived the current formulas. In this way, we have reached a point where there is no deviation in central values. Even today, we are continuing to improve precision while enlisting the cooperation of universities and other organizations.

This column is not a technical column, and has turned out like a blog article reporting on the current situation, so I hope you will forgive me.

Kazuho Morimoto
Representative Director
OPM Laboratory Co., Ltd.