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One Test Is Not Always Enough


To improve yield, quality, and cost, two separate test parameters can be combined to determine if a part passes or fails. The results gleaned from that approach are more accurate, allowing test and quality engineers to fail parts sooner, detect more test escapes, and ultimately to improve yield and reduce manufacturing costs. New data analytic platforms, combined with better utilization of s... » read more

Geo-Spatial Outlier Detection


Comparing die test results with other die on a wafer helps identify outliers, but combining that data with the exact location of an outlier offers a much deeper understanding of what can go wrong and why. The main idea in outlier detection is to find something in or on a die that is different from all the other dies on a wafer. Doing this in the context of a die’s neighbor has become easie... » read more

Chasing Test Escapes In IC Manufacturing


The number of bad chips that slip through testing and end up in the field can be significantly reduced before those devices ever leave the fab, but the cost of developing the necessary tests and analyzing the data has sharply limited adoption. Determining an acceptable test escape metric for an IC is essential to improving the yield-to-quality ratio in chip manufacturing, but what exactly is... » read more

Hunting For Open Defects In Advanced Packages


Catching all defects in chip packaging is becoming more difficult, requiring a mix of electrical tests, metrology screening, and various types of inspection. And the more critical the application for these chips, the greater the effort and the cost. Latent open defects continue to be the bane of test, quality, and reliability engineering. Open defects in packages occur at the chip-to-substra... » read more

Adaptive Test Gains Ground


Not all devices get tested the same way anymore, and that’s a good thing. Quality, test costs, and yield have motivated product engineers to adopt test processes that fall under the umbrella of adaptive test, which uses test data to modify a subsequent test process. But to execute such techniques requires logistics that support analysis of data, as well as enabling changes to a test based ... » read more

Combining Machine Learning With Advanced Outlier Detection To Improve Quality And Lower Cost


In semiconductor manufacturing, a low defect rate of manufactured integrated circuits is crucial. To minimize outgoing device defectivity, thousands of electrical tests are run, measuring tens of thousands of parameters, with die that are outside of specified parameters considered as fails. However, conventional test techniques often fall short of guaranteeing acceptable quality levels. Given t... » 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

Who Is Responsible For Part Average Testing?


With ever-increasing demands in the automotive industry, more and more semiconductor companies are interested in monitoring and improving quality and reliability. Outlier detection and more specifically Part Average Testing (PAT) is the industry standard for the automotive industry. But, who is responsible for quality? Historically, OSATs are responsible for this. In the past, once they... » read more

Making AI More Dependable


Ira Leventhal, vice president of Advantest’s new concept product initiative, looks at why AI has taken so long to get going, what role it will play in improving the reliability of all chips, and how to use AI to improve the reliability of AI chips themselves. » read more

Finding Faulty Auto Chips


The next wave of automotive chips for assisted and autonomous driving is fueling the development of new approaches in a critical field called outlier detection. KLA-Tencor, Optimal+, as well as Mentor, a Siemens Business, and others are entering or expanding their efforts in the outlier detection market or related fields. Used in various industries for several years, outlier detection is one... » read more

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