From defect to competitive advantage - with AI, quality assurance becomes a driver of efficiency and growth.
In the steel and metal processing industry, every detail counts: from material quality and dimensional accuracy to weld seams and surfaces. The highest product quality is essential, but manual inspections and traditional methods such as anomaly detection quickly reach their limits with increasing product diversity, tight tolerances and high deadline pressure.
Your AI-supported quality assurance offers companies decisive advantages along the entire value chain. Instead of merely detecting anomalies, the deep learning-based technology is able to precisely recognize different error patterns and thus consistently eliminate pseudo-defects. At the same time, automatic logging and storage ensures that all defect types are documented and traceable at all times. 36ZERO Vision's scalability and flexibility are particularly impressive in steel and metal processing, where high product diversity and changing requirements are part of everyday life. The solution is extremely cost-efficient, as it is hardware-agnostic and can be easily integrated into existing systems, thus reducing investment and maintenance costs. It also contributes to stable processes, less waste and reliable compliance with quality standards - clear added value in terms of sustainability and compliance with standards.
The possible applications are diverse: in raw material processing, AI enables the inspection of sheet metal, profiles, pipes and wires. In forming technology, it is used for surface inspection of cast and forged parts, while in joining technology, weld seams and soldered joints are reliably inspected. In machining, the technology also ensures reliable burr and chamfer inspection after turning, milling or grinding work. Finally, it supports both in-line and end-of-line inspections in assembly and final production. This makes quality assurance not only more efficient, but also a real competitive advantage.
The cloud platform is used to develop AI models individually for each application. It is initially trained with known error patterns and can be continuously improved through interaction with employees. It adapts flexibly to new product variants, applications and production conditions and standardizes quality decisions worldwide.
2D images from industrial cameras are analyzed autonomously, on-premise and in real time with the trained models, defect patterns are detected with the highest precision and workpieces are objectively evaluated. Surfaces, shape and dimensional accuracy can be checked without delay.
In addition to visual inspection, companies also rely on ultrasonic testing, X-ray testing, magnetic particle testing, penetrant testing, hardness testing and metallography, depending on requirements.
