An EMS cost comparison — the real hidden bill behind programming, false calls and downtime. AI AOI and traditional rule-based AOI aren't solving the same problem the same way.
For stable, highly repetitive lines, rule-based AOI still works; but when a manufacturer faces frequent new-product introductions, high changeover frequency and engineering-labor pressure, AI's advantage becomes clear. The costs you can't see on the quote are what really decide total cost of ownership.
Five cost dimensions worth comparing
- Programming & changeover cost: DaoAI cuts AOI programming from about three hours to about five minutes — ideal for high-mix, low-volume environments.
- False-call burden: false alarms from traditional systems consume huge amounts of engineer review time; DaoAI's semantic false-call filter sharply reduces this hidden cost.
- Upfront dependency: rule-based AOI relies heavily on complete CAD data and a component library, while AI AOI greatly lowers these prerequisites.
- Quality visibility: an AI system should support a real-time SPC dashboard, making process decisions more agile.
- Fit to production mode: line needs vary widely; evaluation should be based on real operational bottlenecks, not spec-sheet comparisons.
How EMS teams should evaluate
Don't look only at "can it detect." Put these side by side instead:
- Programming time per new board
- Labor needed to review false calls
- Dependence on design data (CAD / BOM)
- Speed at which quality information turns into process decisions
- How well the system fits your production mode
What's truly expensive isn't the machine — it's the programming, review and downtime it quietly eats every day.