Outsmarting Silent Data Corruption In AI Processors With Two-Stage Detection


Silent data corruption is on the rise following advancements in semiconductor technology. The explosion in AI for speech, image, video, and text processing leads to a growing complexity and diversity of hardware systems, bringing an increased risk to data integrity. SDC rate is much higher than software engineers expect, undermining the hardware reliability they used to take for granted. Rec... » read more

What Data Center Chipmakers Can Learn From Automotive


Automotive OEMs are demanding their semiconductor suppliers achieve a nearly unmeasurable target of 10 defective parts per billion (DPPB). Whether this is realistic remains to be seen, but systems companies are looking to emulate that level of quality for their data center SoCs. Building to that quality level is more expensive up front, although ultimately it can save costs versus having to ... » read more

Ramping Up IC Predictive Maintenance


The chip industry is starting to add technology that can predict impending failures early enough to stave off serious problems, both in manufacturing and in the field. Engineers increasingly are employing in-circuit monitors embedded in SoC designs to catch device failures earlier in the production flow. But for ICs in the field, data tracing from design to application use only recently has ... » read more

Coping With Parallel Test Site-to-Site Variation


Testing multiple devices in parallel using the same ATE results in reduced test time and lower costs, but it requires engineering finesse to make it so. Minimizing test measurement variation for each device under test (DUT) is a multi-physics problem, and it's one that is becoming more essential to resolve at each new process node and in multi-chip packages. It requires synchronization of el... » read more

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

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