Case Study: Wieland Group improves QA and scales visual inspection with Capgemini

Improving Wieland’s QA with AI-driven computer vision

Wieland Group, a global leader in copper and copper alloy semi-finished products, needed to improve manual visual quality inspection for its highly reflective, round metal components. The challenge was ensuring strict visual standards efficiently across production, and Wieland turned to Capgemini for support with AI-driven computer vision.

Capgemini developed and implemented a scalable computer vision solution based on a deep learning model, using edge computing and cloud-based management to enable real-time automated inspection. The result now supports more than 20 test cells and over 50 products, inspects up to one million parts per week, and maintains a scrap rate of 1.5%, while also giving Wieland a platform it can scale independently to additional use cases.

Wieland Group

Michael Demmer

Chief Strategy Officer