Assess feasibility with existing cameras and lighting
VISION AI
InspectAI
Low-data hybrid AI visual inspection — Combines rule-based logic and Hybrid AI to validate defect decisions while preserving evidence, dataset lineage and production operating criteria.
P0 · concept validationCombine rules and Hybrid AI for explainable decisions
Define KPI gates for false rejects, false accepts and takt time
COMPONENTS
Components
- Inspection recipe
- Hybrid AI model
- Decision and evidence UI
- Edge runtime
INTEGRATION
Integration
- GigE/USB3 cameras
- PLC triggers
- MES and quality database
- VisionOps
DELIVERABLES
Deliverables
- Sample evaluation report
- Inspection criteria and dataset version
- Model and recipe package
- FAT/SAT test items
VALIDATION ITEMS
What must be validated before specifications
Performance, specifications and schedule are confirmed only after validating the actual samples and site conditions.
- 01Target defect definition
- 02Sample representativeness
- 03Lighting and optical conditions
- 04Takt time
- 05False-reject and false-accept limits
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Validate feasibility with actual samples and site conditions
Product status and specifications are stated in the proposal based on validation and supply conditions.