Problems we solve for transport and automotive technology
Outlier Detection
Automatic detection of outliers via AECQ001 is critical and we support advanced algorithms also that the customer owns.
Characterisation
Characterisation ensures that variation in parametric behaviour due to allowed changes in Material or Test Conditions is understood early.
Burn-in and Life Test: Drift analysis
The analysis of population drift and individual die drift through burn-in and life test are very important and fully supported by yieldHUB.
Data cleansing
Multiple steps to test parts makes manual cleansing of the data difficult. yieldHUB automates this, even combining data from dozens of logs.
Traceability
yieldHUB supports traceability and fast analysis of returns.
Die Analysis
Sometimes a die (or part) needs thorough analysis across all tests, including how the tests compare. This capability is available in yieldHUB.
Outlier detection
“Outliers: parts whose parameters are statistically different from the typical part" AEC
Outlier detection is a method of identifying a member in the group that deviates grossly from the norm. You test semiconductors across different factors, e.g. voltage, current & compare the performance.
Burn-in and Drift Analysis
When you collect data at each step of burn-in or life test, you need to see how key tests drifted.
The ‘population’ drift is as important as the drift of any individual die. After collecting the data, you don’t want to have to take more than a few minutes setting up before you see the results.
Press release
yieldHUB chosen by EnSilica for yield management
yieldHUB announced EnSilica as a new customer. EnSilica is a provider of custom ASICS to the automotive, industrial and IoT markets. yieldHUB will be a key partner in enabling them to deliver these products.
Traceability
If you use fuses on your die to somehow encode lot id, wafer id and x/y then yieldHUB can use this information to make the die searchable in the database. If then there is a customer return, it will be possible to analyse how the die behaved for any tests it underwent in manufacturing.
Frequently Asked Questions
Is there a limit on the number of tests you support?
We have customers with 20000 tests in a datalog. We have yet to see an upper limit on how many tests the yieldHUB systems can support.
Do you support OTP?
Yes, we support OTP/Fuse ID for traceability.
Which data formats do you support?
We have yet to receive a data format we cannot support. Most common is STDF, but any type of text or binary format can be supported once it’s consistent.
What type of algorithms do you support for outlier detection?
AECQ001 provides algorithms that we implement in yieldHUB. In the same way, a customer can write scripts for even more advanced methods and we will support these without needing to know or see the inner workings.
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