BETTER THAN THE HUMAN EYE
QUALIFY YOUR PRODUCTS
Germany is world-renowned for high-quality mechanical engineering. This sector is dominated by companies that produce components for the global market with the highest precision and unmatched quality. This advantage must be maintained and expanded through relentless innovation and inventiveness. Detailed knowledge of processes and results is incorporated into the improvement of manufacturing. A few highly qualified engineers are irreplaceable in this process. Unfortunately, they have to spend a lot of time in quality control, a concentrated but grueling job.
It therefore stands to reason to use AI to automate quality control and implement it on a much larger scale. The only problem is that mechanical engineers rarely have experience in software development.
The Kapp Niles company therefore decided to use AIUI to bring AI into its operational processes, but without learning deep understanding in programming languages and AI frameworks. The unique user interface quickly created a neural network that had learned everything the engineers needed to know and provided quality assurance in checking interface structures. To the surprise of the project team, the AI was also able to provide statistics about defects in production more transparently than ever before, leading directly to manufacturing improvements.
The company was able to take an innovative step to stay significantly ahead of the competition and offer better products to their customers faster and at lower prices. This did not require the creation of a separate IT department.
- AI image recognition
Industrial image processing via AI algorithms, robust even with uneven exposure
- Fully automatic control
Fully automatic scanning and comprehensive evaluation
- Quality management
Quantitative defect detection now enables a better evaluation process that was previously subjective.
Process Analysis (1 day):
- Diamonds are electroplated with nickel onto a steel surface.
- Defects of various types can form in the process
- Quality control is performed by an experienced operator under the microscope by 100% inspection.
Process evaluation (1 day):
- The goal is the error-free, fully automated detection of voids in the diamond bed
AI Development (14 days):
- Acquisition of a webcam microscope for digital image data acquisition.
- Acquisition of ~300 images of various exposure, grain size, shape
- Data labeling by Kapp Niles staff, i.e., marking the defects in AI-UI.
- Training of artificial intelligence with AI-UI
Testing (1 day):
- Use of extra images, to test AI prediction goodness on unseen data
Documentation (1 day):
- AI-UI is designed so that documentation happens automatically
Go-live (1 day):
- On the part of the customer, an interface between the camera microscope and AI-UI was established
- AI-UI provided automatic quality analysis