360° Surface Inspection of Cylindrical Aluminum Bodies

High-quality surface integrity is essential in the production of automotive cylindrical aluminum components, where machining defects and material imperfections can impact downstream processes and product performance. To ensure reliable quality control, an automated inspection solution was implemented using a 360° panoramic endoscope combined with senswork's AI-powered image processing software Neuralyze®.

The system captures comprehensive images of the entire inner surface of the aluminum body and analyzes multiple height sections throughout the cylinder. Advanced deep learning algorithms evaluate the captured images to identify machining ridges, blowholes, pores, and other surface irregularities. This enables consistent inspection of reflective aluminum surfaces, a task that is often challenging for conventional vision systems.

By combining panoramic imaging with artificial intelligence, the inspection process significantly improves quality assurance efficiency. Deep learning-based analysis also achieves excellent reliability, even on highly reflective surfaces. This approach provides manufacturers with a reliable method for ensuring product quality of cylindrical aluminum bodies and reduces the risk of defective parts reaching subsequent production stages.

Not sure if you need Vision AI for your quality inspections? This white paper will help you decide whether or not you need deep learning for automating your quality inspections.