AI-enabled Quality Inspection Implementation Guide
Being developed by MOZI with Hexagon and the Advanced Manufacturing Training Academy (AMTA) · under technical review
A practical guide for Singapore manufacturers, especially SMEs: prove value at one station first, then scale on evidence. MOZI turns the technology partner's methods into an executable roadmap, readiness assessment and role design.
- Six-stage roadmap
Define → Assess → Pilot → Deploy → Scale → Improve, with an evidence gate before each next stage.
- Readiness assessment
Five dimensions — ownership, inspection standards, data, technology integration and people — to find gaps before implementation.
- Layered architecture
Image capture, edge processing, data and model management, quality-workflow integration; stable imaging and traceability first.
- Human-in-the-loop
AI flags anomalies, inspectors review, quality leads decide; start in shadow mode and raise automation only after validation.
Six-stage roadmap with evidence gates
- 01
Define
Define the inspection decision: one product or station; separate screening from measurement
- 02
Assess
Confirm image and label readiness; plan independent validation
- 03
Pilot
Run in shadow mode against human inspection; assess misses, false alarms and review load
- 04
Deploy
Embed in the existing quality workflow with traceability and fallback
- 05
Scale
Re-validate for each new product or line; standardise versions and capture
- 06
Improve
Review new defects and false alarms; release model updates only after approval
The guide is under technical review; illustrations are conceptual, not measured project results.
Start with one real scenario
Tell us your industry, the capabilities you want to build and your current conditions.