There may be incorrect screw types, foreign objects such as stones, wood or metal parts as well as defective parts in a production batch. This high variance in the errors that occur requires comprehensive quality control with many different requirements.
Specialized inspection stations with separationThe use of numerous specialized inspection stations with different hardware and software leads to a high level of effort during setup and retrofitting. The test stations rely on the exact separation and positioning of the screws. This easily leads to blockages and misclassifications, especially in the case of defective or non-standard parts.
Inefficient inspection processesConventional inspection methods often lead to a high proportion of good parts being incorrectly rejected, which increases production costs. To reduce this pseudo scrap while maintaining quality, multiple inspection passes are often necessary, which increases production time and the risk of damage to the screws.
Our Light Field Lens HighRes provides precise image data, adapted to the width of the test strip and resolution required for defect detection.
UIA customized graphical user interface (GUI) visualizes incorrect bolt types, foreign parts and all specified defects. This enables operators to check the inspection results intuitively and efficiently.
Robust evaluations with multi-view AICustomized data curation and Multiview AI training provide a reliable Multiview AI model to analyze the screws. Our AI models are specially trained to detect and differentiate between certain types of defects. The AI analyzes all screws in the image area simultaneously and reliably, even with closely positioned components.
APIThe entire inspection system is seamlessly integrated into existing production lines without affecting the production flow. The use of APIs means that data is transferred and processed in real time, enabling an immediate response to detected defects.
Automated control is faster and more efficient than manual control by employees and requires fewer personnel. This significantly reduces process costs.
The AI-supported analysis minimizes false alarms and reduces the proportion of incorrectly rejected good parts. This leads to considerable cost savings by reducing material waste and rework.
The system is flexible and can be used for different types of screws without complex retrofitting. This saves time and costs during production changeovers.
The detailed inspection data allows manufacturing processes to be optimized. This increases efficiency and reduces production costs.
The retention of inspection data reduces the costs of traceability and warranties.
Compared to conventional individual inspection of each screw, the system enables up to a 20-fold increase in throughput. This leads to a significant acceleration of the production process.
The system can be seamlessly integrated into existing production lines, enabling continuous and automated quality control. This enables 100% control of the products during the production process.
The K|Lens light field sensor and multi-view AI enable precise detection of incorrect screw types, foreign objects and rotationally symmetrical defects. This ensures high product quality and minimizes the risk of defects in end products. As screws are often used in fully automated processes and even small errors can lead to downtime, you can ensure customer satisfaction with reliable quality control.
AI-supported analysis can analyze the screws while they are still on the conveyor belt. This eliminates the need for separation, which can lead to blockages.
The system can be adapted to new screw types with minimal training. This enables flexible and efficient quality control for changing production requirements.
The customized graphical user interface (GUI) visualizes all specified defects. This allows operators to check inspection results intuitively and efficiently.
The entire inspection system is smoothly integrated into existing production lines without affecting the production flow. Through the use of APIs, data transfer and processing takes place in real time, enabling an immediate response to detected defects.
