Production lines aim to ensure that products reach the end user with the highest quality and customer satisfaction. Additionally, detecting defective products at the earliest possible stage provides benefits to the manufacturer in terms of time, cost, quality, and brand prestige.
Our anomaly detection solutions can fully autonomously detect and separate defective products, a task that traditionally requires human labor. The artificial intelligence methods we run on our devices analyze images from industrial cameras to detect defective products with anomalies. Depending on our customers' requirements, the system can stop the conveyor belt, send a trigger to a separation console, or simply record and report statistics on defective products with anomalies. All these processes can be controlled and managed by the customer.
We optimize our anomaly detection system through many processes using the latest technologies and methods supported by industrial AI accelerator hardware. As a result, our system is capable of detecting anomalies at the real-time speeds and high accuracy rates that you need. Additionally, with our ongoing R&D efforts, we continue to expand our portfolio of high-performance models suitable for every scenario.
At the core of our system are various AI methods tailored to meet each customer's needs. Our in-house developed anomaly detection system features a generalized anomaly detection library. As part of the development process, we conducted demo tests for a wide range of products and application areas, enabling us to offer one of the most comprehensive solutions in the industry. Through this library, we quickly determine and integrate the most suitable AI model, optimal lighting conditions, required camera hardware, and necessary edge device configuration for your needs.
To offer our system to customers at affordable costs while maintaining high performance, we run it on industrial edge devices. We apply various optimizations at each step of the anomaly detection process to achieve this. For more detailed information on these optimizations, you can read our blog post.
