Whitepaper
Visual AI for Defect Detection in Manufacturing
Can AI-based visual inspection really deliver factory-grade reliability? In this whitepaper, we analyze what breaks most manufacturing defect detection systems—and how top teams overcome the hardest challenges with data-centric strategies, synthetic defects, and scalable QA workflows.
Get actionable insights and proven tools for:
- Reducing defect escapes: Why 65% of manufacturers still rely on error-prone manual inspection
- Preventing model collapse: How data scarcity and drift silently degrade production AI
- Building robust datasets: Tools for generating rare defect types with GANs and diffusion
- Scaling quality control: How Tesla, TSMC, and Samsung use AI to boost yield and cut costs
- Fixing failure modes: Labeling inconsistencies, generalization gaps, and explainability bottlenecks