Monitoring IC Abnormalities Before Failures


The rising complexities of semiconductor processes and design are driving an increasing use of on-chip monitors to support data analytics from an IC’s birth through its end of life — no matter how long that projected lifespan. Engineers have long used on-chip circuitry to assist with manufacturing test, silicon debug and failure analysis. Providing visibility and controllability of inter... » 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

Redefining Device Failures


Can a 5nm or 3nm chip really perform to spec over a couple decades? The answer is yes, but not using traditional approaches for designing, manufacturing or testing those chips. At the next few process nodes, all the workarounds and solutions that have been developed since 45nm don't necessarily apply. In the early finFET processes, for example, the new transistor structure provided a huge im... » read more

3 Big Data Mega Trends For 2020


What are the greatest trends and challenges that will define the automotive and semiconductor industries in 2020? Our e-book delves deep into three of these megatrends: Artificial intelligence and machine learning at scale Holistic quality solutions Connected supply chains With automotive and semiconductor manufacturers under mounting pressure to manufacture products of the hig... » read more

How Chips Age


Andre Lange, group manager for quality and reliability at Fraunhofer IIS’ Engineering of Adaptive Systems Division, talks about circuit aging, whether current methods of predicting reliability are accurate for chips developed at advanced process nodes, and where additional research is needed. » read more

Extreme Quality Semiconductor Manufacturing, Part 1: Automotive


By Ben Tsai and Cathy Perry Sullivan Across the full range of semiconductor device types and design nodes, there is a drive to produce chips with significantly higher quality. Automotive, IoT and other industrial applications require chips that achieve very high reliability over a long period of time, and some of these chips must maintain reliable performance while operating in an environmen... » 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

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

How Hardware Can Bias AI Data


Clean data is essential to good results in AI and machine learning, but data can become biased and less accurate at multiple stages in its lifetime—from moment it is generated all the way through to when it is processed—and it can happen in ways that are not always obvious and often difficult to discern. Blatant data corruption produces erroneous results that are relatively easy to ident... » read more

IP’s Growing Impact On Yield And Reliability


Chipmakers are finding it increasingly difficult to achieve first-pass silicon with design IP sourced internally and from different IP providers, and especially with configurable IP. Utilizing poorly qualified IP and waiting for issues to appear during the design-to-verification phase just before tape-out can pose high risks for design houses and foundries alike in terms of cost and time to... » read more

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