The advantage of the metal-based powder bed fusion using a laser beam (PBF-LB/M) is the recyclability of an unused powder deposited around the built part. However, this technique requires a high-power heat source to complete the building process, generating metal vapor jets and spatter particles. The contamination of such oxidized particles in the powder bed can affect the reusability of the powder. In this study, the changes in the bulk density, flowability, thermal conductivity, and laser absorption of a Ni-based powder after the reuse process were evaluated, and their effects on the building characteristic and spatter behavior were investigated. The results indicate that the proportion of a coarse powder increased due to the contamination of spatter particles, leading to the change in the particle size distribution of the reuse powder. The oxidized particles in the reuse powder increased the flowability and bulk density, and their property change impacted the thermal conductivity and laser absorptivity of the powder. At the laser power of 300 W, scanning speed of 600 mm/s, spot diameter of 100 μm, and layer thickness of 50 μm, the height and width of the built structure, denuded width, and number of spatter particles increased for the reuse powder due to the difference in the building aspect. When the particle size distribution of the reuse powder was similar as that of the virgin powder, the morphological change of the built structure and the number of spatter particles were comparatively suppressed.

We proposed a method that, when given a language instruction, determines an appropriate robot motion procedures and the used tools for that task. In addition, our method generated a motion trajectory for a robot to execute the task. The proposed method uses a large language model (LLM) to determine robot motion procedures and tools. However, LLM may determine in inappropriate procedures and tools. For example, for the motion of “put matcha powder,” LLM may actually propose that the matcha be scooped by a natsume or poured into a bowl. The other example of output is the procedure for stirring the mixture with only matcha powder in chawan. To correct this error, our method focuses on part function. An everyday object has a role assigned to each region of that object, such as “scoop” or “stir”. The tool used for scooping must have scoop function. Thus, there are certain constraints on function and motion. The proposed method uses functional constraints and LLM to modify the correct procedures and tools. Experimental results confirmed that the proposed method was able to generate robot motion trajectory to execute a task from language instruction.