3D printing technology for metal products: from an automatic design system to a real part
Bibliographic record
Abstract
The aim of the present study involves the adaptation of a robotic complex based on an industrial robot for 3D printing of metal products by arc welding, the development of a technological process system for printing a real part, as well as an evaluation of the potential for obtaining high-quality metal products using existing equipment. For 3D printing of metal products, a robotic complex based on a KR 210 R2700 PRIME industrial robot (KUKA, Germany) and an S3 mobil SpeedPulse welding machine (Lorch, Germany) were used. 3D object models for printing were created in Autodesk Fusion 360 software. The dedicated Ultimaker Cura 3D printing program was applied for slicing the models into layers. The simulation of the printing process and programming of an industrial robot was carried out using the RoboDK software (Canada). As a result, a technological process for 3D printing an impeller prototype from the design stage to the manufacture of a finished metal product has been developed. A detailed methodology for adapting an industrial KUKA robot for the process of metal product 3D printing using the arc welding method is presented. Following the creation of the 3D model of the impeller in the CAD system, its slicing into layers was performed in a slicer program. In the course of preliminary experiments, the optimal technological parameters of the torch movement speed during weld surfacing of 3 mm/s were determined for the 3D printing of carbon steel workpieces. A carbon steel impeller prototype was printed using a welding machine and a welding wire. The developed technological process for 3D printing of metal products using the arc welding method has demonstrated the potential use of an industrial robot in combination with a welding machine for use as an industrial 3D printer. Future studies will focus on developing a technological process for finishing parts produced by means of 3D printing, as well as printing parts from expensive materials and alloys containing titanium and nickel.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".