• AOI-OPEN establishes a trustworthy AOI ecology via decentralized autonomous organizations (DAOs), enabling secure collaboration among software providers, hardware manufacturers, and factories.
• A parallel data pipeline generates large-scale virtual samples from small-scale real data, addressing data scarcity in AOI systems.
• Federated learning leverages distributed data resources across entities while preserving privacy, building robust inspection models.
• Experimental results on defect classification demonstrate improved data utilization and model accuracy under privacy-preserving conditions.