The robotic welding industry suffers from the following pain points:
- High defect rates due to fixed working paths not accounting for material tolerance – this is a particular issue with arc welding
- Lack of robustness due to limitations in welding materials and factory lighting
- Teaching and calibration process is tedious
Using artificial intelligence, we can empower the entire robotic welding process with a ‘hand-eye’ system. Before welding, the system can suggest parameters appropriate for the material, simplifying the calibration process. During welding, positioning will be more precise by reprogramming the welding path according to material variance. After welding is complete, quality assurance can be automated quickly and accurately.
Cāng zhú is a popular Chinese herbal medicine created from the dried roots of Atractylodes lancea. A key part of the production process is inspecting each herb sample for any of 12 possible defects that must be identified and addressed to ensure quality. Previously, this was a manual and error-prone process, with only an 88% accuracy rate for defect detection.
By introducing a robotic inspection station to the production line, it will be possible to leverage AI-driven image classification, automatically identifying images pertaining to any given defect. This improves not only the efficiency of the human operators in the validation process, but also the quality of the overall manufacturing process.