New Strategies For Interpreting Data Variability


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

Cost And Quality Of Chiplets


Chiplets add a whole new challenge for the semiconductor industry. How much testing is enough? How do you optimize system binning? What’s the right amount of burn-in? The answers to these questions will vary, depending upon cost and quality tradeoffs, the number and source of the chiplets, and real-world workloads and projected lifespans. Marc Jacobs, senior director of solutions architectur... » read more

AI/ML Challenges In Test and Metrology


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

Strategies For Detecting Sources Of Silent Data Corruption


Engineering teams are wrestling with how to identify the root causes of silent data corruption (SDC) in a timely and cost-effective way, but the solutions are turning out to be broader and more complex than simply fixing a single defect. This is particularly vexing for data center reliability, accessibility and serviceability (RAS) engineering teams, because even the best tools and methodolo... » read more

Adaptive Test Ramps For Data Intelligence Era


Widely available and nearly unlimited compute resources, coupled with the availability of sophisticated algorithms, are opening the door to adaptive testing. But the speed at which this testing approach is adopted will continue to vary due to persistent concerns about data sharing and the potential for IP theft and data leakage. Adaptive testing is all about making timely changes to a test p... » read more

ML-Assisted IC Test Binning With Real-Time Prediction At The Edge


IC Test is a critical part of semiconductor manufacturing and proper die binning and material disposition has an important impact on the overall yield and on the process monitoring and failure mode diagnostics. Edge analytics are becoming an increasingly important aspect of die disposition. By intercepting parts in real-time at the wafer test step, we can save downstream processing needs. In th... » read more

Glass Substrates Gain Foothold In Advanced Packages


Glass substrates are starting to gain traction in advanced packages, fueled by the potential for denser routing and higher signal performance than the organic substrates used today. There are still plenty of problems to solve before this approach becomes mainstream. While glass itself is cheap and shares some important physical similarities to silicon, there are challenges with buildup, stre... » read more

Pressure Builds On Failure Analysis Labs


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

In-Product BTI Aging Sensor For Reliability Screening And Early Detection Of Material At Risk


We have developed a new reliability monitoring suite, within a proprietary IP block that we call a CV Core, with aging sensors embedded in the product layout and testable through the product I / O interface. We illustrate the application of the sensor suite with an example of the PMOS NBTI monitor, testable at the wafer level during product electrical wafer sort (EWS), as well after packaging a... » read more

Fabs Begin Ramping Up Machine Learning


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

← Older posts Newer posts →