A supplier in the metal finishing industry faced increasing pressure to automate its surface inspection process. Manual visual inspection had become a major cost driver due to high labor requirements and growing difficulties in recruiting skilled personnel for monotonous tasks. In addition, inconsistent inspection results led to quality issues and costly customer complaints.
With OEM customers demanding higher standards and automation as a prerequisite for maintaining supplier rankings, the company needed a solution that would ensure consistent inspection quality, reduce costs, and enable full process traceability.
The complexity of the inspection task was considerable. A wide variety of parts were processed on the same production line, featuring diverse geometries and surface characteristics such as concave and convex shapes, partial transparency, glossy coatings, and printed areas. Detecting typical defects like inclusions, bumps, and scratches with traditional camera-based systems proved highly challenging.
In collaboration with the customer, Data Spree implemented an AI-based surface inspection system that enables fully automated quality control within the existing production environment. The solution was integrated inline into the production line and connected directly to the robotic handling system for automated OK/NOK sorting.
Advanced deep learning algorithms analyze high-resolution image data in real time and detect even the smallest surface defects with high precision, regardless of variations in geometry, material, or reflection. The flexible system architecture allows the inspection of different part categories using the same setup, reducing changeover times and simplifying operation.
A transparent and intuitive user interface provides complete process traceability, allowing operators to monitor inspection results, review defect images, and analyze performance metrics. This ensures consistent quality assurance and supports continuous process optimization.
By introducing AI-based surface inspection, the customer significantly improved both product quality and process efficiency. The automated system ensures consistently precise defect detection, reduces manual effort, and minimizes downtime. The project demonstrates how intelligent vision technology elevates quality assurance in industrial manufacturing and lays the foundation for scalable and future-proof production processes.
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