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yieldHUB reduce test time by:
Use our Tests Not Failing with volume data to remove tests.
Analyze Test Time as if it was a test, so trends and all sorts of grouped analysis are available.
See the Delays in Production wafer to wafer, datalog to datalog.
Capture the % of units that falsely fail because of site to site variation.
See how test time correlates with bin numbers. Helps you resequence the tests to fail fast.
Reducing test time is often achieved by testing on more sites in parallel and eliminating redundant tests. Also by reducing set-up time for each lot and wafer.
Test time reduction can also be achieved by removing tests or switching tests around so that the top failing tests are always done near the start of testing. It’s also a fact that handlers in production can have highly variable index times which can reduce the effect of any test time improvement. Moreover, index time can dominate the test time of short test time devices if not captured and monitored.
yieldHUB captures test time if the test time and index time if they are stored in the datalogs. yieldHUB also visualises the delays in production wafer to wafer, datalog to datalog. It also detects tests that have never failed.
The % of units that falsely fail due to site to site variation is also captured. This allows you to picture how good and stable your parallel testing is.
Using the test time information, the site loss %, which tests never fail and visualising production delays will provide most of what you need to reduce test time.
UPH (Units Per Hour)
We can track UPH information once the start and end date of a wafer (or datalog in final test) is in the datalog. You will then be in a position to correlate UPH improvement with test time improvement.
This doesn’t always follow as it can happen that a test time improvement can lead to a handler index time increase.
Either way, the first thing to do is gather the data and the tools are there in yieldHUB to help you save your test cost taking the above, and, for example, site performance into account. Related question: Do you know the average number of sites your product is running on?
This is one example of a UPH visualisation in yieldHUB. Please contact us for more information.
Reducing test time is often achieved by testing on more sites in parallel and eliminating redundant tests. Also by reducing set-up time for each lot and wafer.
Test time reduction can also be achieved by removing tests or switching tests around so that the top failing tests are always done near the start of testing. It’s also a fact that handlers in production can have highly variable index times which can reduce the effect of any test time improvement. Moreover, index time can dominate the test time of short test time devices if not captured and monitored.
yieldHUB captures test time if the test time and index time if they are stored in the datalogs. yieldHUB also visualises the delays in production wafer to wafer, datalog to datalog. It also detects tests that have never failed.
The % of units that falsely fail due to site to site variation is also captured. This allows you to picture how good and stable your parallel testing is.
Using the test time information, the site loss %, which tests never fail and visualising production delays will provide most of what you need to reduce test time.
UPH (Units Per Hour)
We can track UPH information once the start and end date of a wafer (or datalog in final test) is in the datalog. You will then be in a position to correlate UPH improvement with test time improvement.
This doesn’t always follow as it can happen that a test time improvement can lead to a handler index time increase.
Either way, the first thing to do is gather the data and the tools are there in yieldHUB to help you save your test cost taking the above, and, for example, site performance into account. Related question: Do you know the average number of sites your product is running on ?
This is one example of a UPH visualisation in yieldHUB. Please contact us for more information.