tag: DR Yield

New Strategies For Interpreting Data Variability
By Gregory Haley - 09 Apr, 2024 - Comments: 0

Every measurement counts at the nanoscopic scale of modern semiconductor processes, but with each new process node the number of measurements and the need for accuracy escalate dramatically. Petabytes of new data are being generated and used in every aspect of the manufacturing process for informed decision-making, process optimization, and the continuous pursuit of quality and yield. Most f... » read more

DTCO/STCO Create Path For Faster Yield Ramps
By Laura Peters - 12 Mar, 2024 - Comments: 0

Higher density in planar SoCs and advanced packages, coupled with more complex interactions and dependencies between various components, are permitting systematic defects to escape traditional detection methods. These issues increasingly are not detected until the chips reach high-volume manufacturing, slowing the yield ramp and bumping up costs. To combat these problems, IDMs and systems co... » read more

AI/ML Challenges In Test and Metrology
By Gregory Haley - 12 Mar, 2024 - Comments: 0

The integration of artificial intelligence and machine learning (AI/ML) into semiconductor test and metrology is redefining the landscape for chip fabrication, which will be essential at advanced nodes and in increasingly dense advanced packages. Fabs today are inundated by vast amounts of data collected across multiple manufacturing processes, and AI/ML solutions are viewed as essential for... » read more

Pressure Builds On Failure Analysis Labs
By Laura Peters - 09 Jan, 2024 - Comments: 0

Failure analysis labs are becoming more fab-like, offering higher accuracy in locating failures and accelerating time-to-market of new devices. These labs historically have been used for deconstructing devices that failed during field use, known as return material authorizations (RMAs), but their role is expanding. They now are becoming instrumental in achieving first silicon and ramping yie... » read more

Fabs Begin Ramping Up Machine Learning
By Anne Meixner - 19 Dec, 2023 - Comments: 0

Fabs are beginning to deploy machine learning models to drill deep into complex processes, leveraging both vast compute power and significant advances in ML. All of this is necessary as dimensions shrink and complexity increases with new materials and structures, processes, and packaging options, and as demand for reliability increases. Building robust models requires training the algorithms... » read more

Closing The Test And Metrology Gap In 3D-IC Packages
By Gregory Haley - 12 Dec, 2023 - Comments: 0

The industry is investing in more precise and productive inspection and testing to enable advanced packages and eventually, 3D ICs. The next generations of aerospace, automotive, smartphone, and wearable tech most likely will be powered by multiple layers of intricately connected silicon, a stark departure from the planar landscapes of traditional integrated circuits. These 3D-ICs, compos... » read more

Fingerprinting Chips For Traceability
By Anne Meixner - 12 Dec, 2023 - Comments: 0

Semiconductor components increasingly require unclonable and tamper resistant identifiers, which are especially necessary as devices become increasingly heterogeneous collections of chiplets and subsystems. These fingerprints provide traceability, which contributes to process improvements and yield learning and enable tracking for a tightly managed supply chain. While some of this technology... » read more

New Insights Into IC Process Defectivity
By Laura Peters - 07 Nov, 2023 - Comments: 1

Finding critical defects in manufacturing is becoming more difficult due to tighter design margins, new processes, and shorter process windows. Process marginality and parametric outliers used to be problematic at each new node, but now they are persistent problems at several nodes and in advanced packaging, where there may be a mix of different technologies. In addition, there are more proc... » read more

Using Smart Data To Boost Semiconductor Reliability
By Laura Peters - 10 Oct, 2023 - Comments: 0

The chip industry is looking to AI and data analytics to improve yield, operational efficiency, and reduce the overall cost of designing and manufacturing complex devices. In fact, SEMI estimates its members could capture more than $60B in revenues associated through smart data use and AI. Getting there, however, requires overcoming a number of persistent obstacles. Smart data utilization is... » read more

Installing Yield Software Early In A Ramp Up
By Dieter Rathei - 10 Oct, 2023 - Comments: 0

In 1999, the White Oak Semiconductor Fab in Richmond, VA, was awarded the prestigious “Top Fab of the Year” (yes, that actually existed – proof attached!) by the leading semiconductor magazine of the time. Back then, I was a young engineer on the ramp up team and I recall that the reason we were chosen for the award was the incredibly short time in which we were able to ramp up production... » read more

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