Test is the only manufacturing step you pay for on every device and only get value from on the good ones. That makes test-cost engineering one of the highest-leverage levers in a program.
The goal is not to test less. It is to test smart: catch the failures that matter, learn yield fast, and keep the per-good-unit cost under control.
Why Cost per Good Unit, Not per Device
You pay the ATE and handler cost on every die you test, including the ones that fail. So the number that hits margin is cost per good unit, not cost per device tested.
This is exactly what the Test Cost & Yield Calculator shows: lower yield spreads the same test spend across fewer shippable parts.
- Test cost per good unit = total test spend divided by good units
- Yield improvements often beat faster handlers
- A few yield points can save more than cutting ATE rate
Design for Test (DFT) Pays Back Early
Scan chains, built-in self-test and boundary scan make faults observable so test time drops and fault coverage rises.
Good DFT also speeds yield learning, because you can localize failures instead of guessing — which shortens the loop from wafer return to fix.
ATE Rate and Test Time Strategy
ATE hourly rate varies enormously by platform; advanced SoC testers cost far more per hour than older ones. Matching the tester to the device avoids paying for capability you do not need.
Test time is the other lever. Trimming redundant patterns and prioritizing high-value tests reduces both cost and the risk of over-testing good parts.
Use MPW to Learn Yield Cheaply
Early MPW or engineering runs are the cheapest place to learn test limits and characterize yield before committing to high-volume test cost.
Treating test definition as a pre-tape-out task, not a post-wafer scramble, is what keeps the cost per good unit predictable at volume.
