Machine Vision for manufacturing
Inspection of Painted Surfaces
The visual inspection of metallic and reflective surfaces can be very challenging in practice. However, by optimally coordinating software and hardware, especially in lighting, even the smallest defects can be reliably detected.
- Identification of paint defects on painted surfaces
- Classification of defects (e.g. scratches, dust inclusions, etc.)
- Output of the exact defect positions on the object (CAD coordinates)
- Display and documentation of the results
Automotive industry, paint shop
The inspection and presence check of parts can be automated with the AI Scanner. In this way, it is possible to ensure that no parts have been forgotten after manual assembly and that they have been attached without errors.
Checking presence of parts, Checking for freedom from defects
Automotive industry, assembly
Label Inspection and OCR-Scan
During the production of labels printing errors can occur. These can be checked for correctness on different surfaces using 2D image data analysis.
OCR (Optical Character Recognition) scanning can be used to efficiently read out codes and autonomously enter those into databases.
- Checking correctness of labels
- Reading out barcodes and text using OCR technology
Field of application:
Circuit Board Inspection
Due to high cycle times, the final visual inspection of circuit boards and PCBs can easily become a bottleneck in the production process. Autonomous inspection can ensure a precise and time-efficient quality assurance.
- Inspection for completeness and deviations
- Feature inspection of controllers, solder joints etc.
- Output of defect position
Field of application:
Circuit board industry, final inspection
Counting of Objects
Across industries, counting objects and products is a reocurring task in the production process. This task can be automated using AI models based on image data alone.
- Output of count per time unit
- Display of deviations of target/actual number
- Tracking in a database
Weld Seam Inspection
Visual inspection of welds, by the human eye only, is often inconsistent and subjective. An autonomous inspection can optimize this process. Since several weld seams at different positions can be inspected at the same time, the time spent on this process step can be significantly reduced.
- Detection of surface and form defects on weld seams
- Inspection for anomalies
- Optical measurement
- Autonomous Data acquisition and generation of reports