Address fab-process-related issues to meet quality targets. Statistically analyze test data from multiple operations, utilizing proven PAT (Part Average Testing) algorithms to identify good outlier units. Power up OptimalPlus skills by learning how to execute Outlier Detection algorithms on test data using a pre-defined population. Explore how to integrate and combine these algorithms with a single rule "recipe" during multiple operations. Learn how to automatically switch units to different bins when the rule is applied in production.
Course Last Release Date or Version Number:
Instructor-led Classroom: 3-4 days (depending on the topics to be covered)
Customers in the Semiconductors industry
For those who are responsible for increasing product quality and reliability
Quality Engineers, Test & Product Engineers, IT System Administrators, and key users for enhanced training
Prior knowledge of the Global Operations learning path
An environment where the learner can practice
Gathered desired use cases to be covered in class
Provided information if the customer has a Vertica environment
OptimalPlus SW
Explain the value of the Outlier Detection solution
Distinguish between the way that each algorithm works
Design different virtual operation rules
Analyze rule results after applying an Outlier Detection algorithm
Please contact the Application/Support team for information or request the training outline.