Installing Yield Software Early In A Ramp Up


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

Using Deep Data Analytics To Enhance Reliability Testing The Fast Roadmap for Zero Defects


proteanTecs and ELES have partnered together to enhance reliability testing with deep data analytics. This collaboration enables SoC manufacturers to improve their qualification envelope to achieve lifetime reliability, shorten their root cause analysis time, and reduce operational costs. This innovative approach adds parametric measurements during the stress test in order to accurately and pre... » read more

proteanTecs On-Chip Monitoring And Deep Data Analytics System


High reliability applications in service-critical markets, such as autonomous driving and cloud computing, demand maximum performance and minimal power and cost. Reducing design margins while maintaining high reliability becomes imperative. State-of-the-art silicon processes offer mainly logic density improvements at limited speedup. Worst-case design analysis is not cost effective anymore. ... » read more

A Practical DRAM-Based Multi-Level PIM Architecture For Data Analytics


A technical paper titled "Darwin: A DRAM-based Multi-level Processing-in-Memory Architecture for Data Analytics" was published by researchers at Korea Advanced Institute of Science & Technology (KAIST) and SK hynix Inc. Abstract: "Processing-in-memory (PIM) architecture is an inherent match for data analytics application, but we observe major challenges to address when accelerating it usi... » read more

Smart Manufacturing Makes Gains In Chip Industry


Lights out manufacturing is gaining steam across the semiconductor industry, accelerating productivity, improving quality, and reducing costs and environment impact. These benefits are the result of years of strategic investments in technologies like machine-to-machine communication, data analytics, and robotics to achieve higher levels of autonomy. Semiconductor factories have long depen... » read more

Risks And Faults We Can Detect Using Machine Learning And Physics


In its earliest form, technicians manually took condition status readings from individual pieces of equipment and used them to shape maintenance conclusions. Today, critical machine and system data can be streamed continuously, automatically, from industrial internet of things (IIoT) sensors for real-time analytics, diagnostics, and suggested actions. Click here to read more. » read more

Multivariate Analysis For Full Process Visibility


In semiconductor manufacturing, especially in electrical test data, but also in other parameters, there are often sets of parameters that are very highly correlated. Even a change in the correlation of those parameters may indicate a problem. For that reason, multivariate monitoring, or multivariate statistics, is applied to these parameters. Multivariate analysis, also known as multivariate... » read more

Data Analytics For The Chiplet Era


This article is based on a paper presented at SEMICON Japan 2022. Moore’s Law has provided the semiconductor industry’s marching orders for device advancement over the past five decades. Chipmakers were successful in continually finding ways to shrink the transistor, which enabled fitting more circuits into a smaller space while keeping costs down. Today, however, Moore’s Law is slowin... » read more

What Is Achievable With A Yield Management System?


Semiconductor manufacturers are under constant pressure to increase yields and cut costs. Yield Management Systems (YMS) are designed specifically to meet the needs of semiconductor manufacturers, enabling them to investigate yield excursions, streamline the manufacturing processes, optimize the supply chain, analyze tools and eliminate workplace inefficiencies. In terms of data challenges... » read more

Getting Smarter About Tool Maintenance


Chipmakers have begun to shift to predictive maintenance for process tools, but the hefty investment in analytics and engineering efforts means it will take some time for smart maintenance to become a widespread practice. Semiconductor manufacturers need to maintain a diverse set of equipment to process the flow of wafers, dies, packaged parts, and boards running through factories. OSAT and ... » read more

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