5 Preconceptions About AI-Based Visual Inspection – Debunked
In this foundational webinar, the Zetamotion team tackles the most common misconceptions surrounding AI in manufacturing quality control. From data requirements to reflectivity challenges, this session breaks down why traditional assumptions no longer apply—and how synthetic data is unlocking scalable, high-accuracy inspection systems.
Led by CEO Dr. Wilhelm Klein, the team walks through real-world case studies—like roof shingles, aerospace panels, and reflective materials—and explains how their Spectron™ platform achieves 99%+ accuracy from a single scan with minimal manual input.
Whether you’re just exploring AI or burnt out from pilot failures, this session offers a practical roadmap to make AI-powered visual inspection work—without needing a team of PhDs or thousands of real samples.
Key Topics Covered:
- Top 5 myths about AI in visual inspection—debunked
- Why machine vision struggles to scale with real-world variability
- How synthetic data eliminates massive data and labeling requirements
- Use cases: roof shingles, aerospace composites, reflective surfaces
- How Spectron simplifies installation and integrates with existing systems
“If your first AI pilot failed, it’s not your fault—most tools leave you doing the hard part. We don’t.” — Dr. Wilhelm Klein
💡 Bonus: Live Q&A on hardware compatibility, multi-part inspection, cost models, and how to get started with Spectron™.
