Visual inspection by AI
with AI.SEE™ from elunic

Visual inspection describes the visual inspection of a product or manufactured part for defects or production errors. As a result of digitalization, applications based on AI (artificial intelligence) are used today to inspect products efficiently and accurately. As a non-destructive quality assurance method, visual inspection is particularly suitable for detecting scratches or cracks as well as cavities, casting defects or other external defects.

Visual inspection in quality assurance

Instead of an automated visual inspection system, companies often still rely on the use of trained employees for visual quality assurance. However, manual visual inspection usually does not prove to be the optimal method for quality assurance. Constantly increasing quality demands from customers and the processing industry are pushing manual visual inspection to its limits. Although non-destructive visual inspection can usually be optimally integrated into the production process without significantly disrupting it, there are often problems with the efficiency and consistency of manual inspection. If the quality requirements demand a visual inspection of each individual product, a visual inspection by employees can no longer guarantee the cycle times in most cases.

Automated visual inspection by AI.SEE™

An automated AI-based solution for visual inspection with the help of inspection software therefore brings significant efficiency gains. In addition, an AI-based autonomous visual inspection leads to a significant increase in quality by avoiding fluctuations in the quality of the end product.
With the help of AI.SEE™, every component produced can be checked efficiently and reliably based on defined criteria. The system also enables defects to be identified and documented in order to prevent them in the future. Find out if AI.SEE™ can automate your visual inspection with just a few questions!

Practical example of visual inspection - fault detection in solar cell production

Conventional visual defect detection systems use hard-coded rules to identify specific shapes or lines. The AI-based visual inspection with AI.SEE™ from elunic relies on neural networks that have been trained with extensive data sets and AI.

It takes a trained employee around 60 seconds to carry out a visual inspection of a solar panel, checking for 4 main types of defect. The AI-based inspection system from elunic inspects the same component in under 5 seconds and then transmits the defects found to the employee to confirm the visual inspection. This means that the employee only needs to check the relevant parts of a solar panel with their trained eye, which only takes around 10 seconds.

This reduced effort for the visual inspection offers another advantage in addition to the significant time savings. Even after many hours, the AI-based inspection system remains consistently reliable and independent of the physical and mental fatigue to which a person is exposed. The employee's concentration can therefore be used efficiently for the critical points in the visual inspection and the AI.SEE™ AI inspection system results in an even better detection rate for production defects.