Leak Tester

Computer vision for quality control in manufacturing

Senior Design

Computer Science

Grotnes

Team

David Colle
Alex Nwanganga

Mentor

John Lancione, Grotnes Senior Engineer Manager Eric Selner, Grotnes Engineer Michael Mason, Senior Project Manager, Engineer Matias Soto, PhD Gunnar Lovhoiden, PhD

Partner

Grotnes

The Challenge

Niles Steel Tank faced quality control challenges with manual inspection processes leading to bottlenecks and inconsistent defect detection.

Our Solution

Implemented a machine learning-powered computer vision system for real-time defect detection, classification, and automated rejection of substandard parts.

Results

Reduced defect escape rate by 78%, increased throughput by 35%, and reduced inspection time per unit from 2 minutes to 15 seconds.