Schaeffler automates EV component inspection with machine vision across 4,800 annual projects

Schaeffler Special Machinery needed to transition from traditional automotive to electric vehicle manufacturing, which involves longer production cycles, more complex components (up to 100 individual parts), and higher demands for speed, flexibility, and innovation. Manual inspection of roller bearings and clutches was slow and inconsistent.

Schaeffler deployed Cognex In-Sight 2D machine vision systems for automated roller bearing needle counting despite variations in contrast, position, and size. For clutch inspection, they implemented PC-based VisionPro with edge learning technology to classify acceptable and defective clutches. The solutions were replicated across numerous machines at 13 locations on three continents.

The roller bearing solution was successfully deployed across numerous machines, automating verification that was previously manual. The clutch inspection concept was replicated hundreds of times across the organization. The edge learning technology streamlined clutch classification, reducing inspection times and improving consistency across their approximately 4,800 projects per year.

• Edge learning technology enables automated classification of acceptable vs. defective parts without extensive programming
• Scalable vision solutions can be replicated hundreds of times across global manufacturing operations
• EV manufacturing transition demands higher levels of automation and traceability than traditional automotive