Using ML In Manufacturing


How to prevent early life failures by applying machine learning to different use cases, and how to interpret models for different tradeoffs on reliability. Jeff David, vice president of AI solutions at PDF Solutions, digs down into how to utilize data to improve reliability. » read more

Ensuring HBM Reliability


Igor Elkanovich, CTO of GUC, and Evelyn Landman, CTO of proteanTecs, talk with Semiconductor Engineering about difficulties that crop up in advanced packaging, what’s redundant and what is not when using high-bandwidth memory, and how continuous in-circuit monitoring can identify potential problems before they happen. » read more

Cleaning Data For Final Test


John O’Donnell, CEO of yieldHUB, talks about why data integrity is so critical for final test, what can cause it to be less-than-perfect, what’s needed to improve the quality of that data, and how that impacts the overall yield in a fab. » read more

Using Big Data For Yield And Reliability


John O’Donnell, CEO of yieldHUB, talks about the importance of clean data for traceability, yield improvement and device reliability, where and how it gets cleaned, and why that needs to be accompanied by domain expertise. » read more

Scan Diagnosis


Jayant D’Souza, product manager at Mentor, a Siemens Business, explains the difference between scan test and scan diagnosis, what causes values in a scan test to change, how this can be used to hone in on the actual cause of a failure in a design, and how to utilize test hardware more efficiently. » read more

Testing Autonomous Vehicles


Jeff Phillips, head of automotive marketing at National Instruments, talks about how to ensure that automotive systems are reliable and safe, how test needs to shift to adapt to continual updates and changes, and why this is particularly challenging in a world where there is no known right answer. » read more

How To Ensure Reliability


Michael Schuldenfrei, corporate technology fellow at OptimalPlus, talks about how to measure quality, why it’s essential to understand all of the possible variables in the testing process, and why outliers are no longer considered sufficient to ensure reliability. » read more

Using Machine Learning To Break Down Silos


Jeff David, vice president of AI solutions at PDF Solutions, talks with Semiconductor Engineering about where machine learning can be applied into semiconductor manufacturing, how it can be used to break down silos around different process steps, how active learning works with human input to tune algorithms, and why it’s important to be able to choose different different algorithms for differ... » read more

How 5G Affects Test


David Hall, head of semiconductor marketing at National Instruments, talks with Semiconductor Engineering about architectural changes to infrastructure due to the rollout of 5G and how the move from macrocells to small cells is changing test requirements.         Subscribe to Semiconductor Engineering's YouTube Channel here » read more

Changes In Data Storage and Usage


Doug Elder, vice president and general manager of OptimalPlus, talks about what’s changing in the storage and collection, including using data lakes and data engineering to break down silos and get data into a consistent format, and why it’s essential to define data up front based upon how quickly it needs to be accessed, as well as who actually owns the data. » read more

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