AI With Open And Scaled Data Sharing in IC Manufacturing (NIST)


A new workshop report titled "Artificial Intelligence with Open and Scaled Data Sharing in Semiconductor Manufacturing" was published by NIST. Abstract "The Workshop sponsored by the National Science Foundation (NSF) (NSF award 2334590, "Artificial Intelligence with Open and Scaled Data Sharing in the Semiconductor Industry") and supported by the National Institute of Standards and Techno... » read more

Using AI/ML To Find And Correlate IC Test Data


What causes low yield in wafers? Usually it's due to design or process changes, but sometimes yield issues occur even if there haven't been any changes from one manufacturing lot to the next. Finding the cause requires some sleuthing, and the best approach for pinpointing problems is to mine design, process, and manufacturing data, and to correlate that data by date and time, by which equipment... » read more

Virtual Metrology In Semiconductor Manufacturing


Fourth in a seven-part series: Virtual metrology may never be 100% perfect because of the almost unlimited number of changes in a fab tools and the unique chip and wafer designs they're being used to process. But there are places where virtual metrology does make sense. Jon Herlocker, vice president and general manager of software analytics at Cohu, talks about why virtual metrology will never ... » read more

Virtual Twins: Layers Of Challenges


Virtual twins can provide deep insights into complex systems at any point in time, but creating them requires integrating a stack of abstractions that don't naturally go together. One abstraction may be mechanical, another electrical, and the data used to create those abstraction layers needs to be fused together logically and updated over time. David Fried, corporate vice president at Lam Rese... » read more

Using AI For Fault Detection And Classification In Manufacturing


Third in a seven-part series: Classic fault detection and classification has some classic problems. It's reactive, time-consuming to set up, and any product change involves significant man-hours. Even then, it still misses a lot of problems, which result in scrap. This is where machine learning can excel, because it can sift through huge amounts of data from thousands of sensors and find outlie... » read more

How Semiconductor Fabs Use Water


Water — lots of it — is a critical enabler for advanced chip architectures, lithography, and back-end packaging. It feeds the ultra-pure water loops that touch every wafer, sluicing heat out of tools that run hotter at each node, and carrying spent chemistries to treatment. The natural reaction to reports that fabs “use millions of gallons of water” is concern, but the engineering re... » read more

Machine Learning In Semiconductor Manufacturing


Second in a seven-part series: Machine learning is a mathematical construct that is the foundation for nearly all the advancements in AI. ML came first, but it remains relevant even today. It can be applied to semiconductor fab for such things as predictive maintenance of manufacturing equipment, rather than just maintenance on a schedule, which decreases downtime. But getting this right is har... » read more

AI, From A To Z


First in a seven-part series: What's the difference between AI, ML, DL, LLMs, and agentic AI? Is it truly revolutionary, or is it an evolutionary series of steps that have enabled machines to do much more than in the past? Jon Herlocker, vice president and general manager of software analytics at Cohu, talks about the evolution of AI over nearly 70 years, the chain of innovation that has enable... » read more

Semiconductor Manufacturing Cybersecurity Consortium (SMCC)—SEMI E187 Compliance Guidance Report


Cyber threats continue to increase at alarming rates, for instance according to Forbes, 2023 saw a 72% increase in data breaches since 2021, which held the previous all-time record and The Federal Bureau of Investigation’s (FBI) 2023 Internet Crime Report further revealed an 81% rise in financial losses due to cybersecurity complaints, escalating from $6.9 billion to $12.5 billion. The FBI re... » read more

Analytical Methods For Analyzing PFAS In Semiconductor Wastewater (Oregon State University)


A new technical paper titled "Practical Guidance on Selecting Analytical Methods for PFAS in Semiconductor Manufacturing Wastewater" was published by researchers at Oregon State University, Corvallis. Abstract "The focus of this review is to provide an overview of the nomenclature, structure, and properties of perfluoroalkyl and polyfluoroalkyl substances (PFAS) that dictate the selection o... » read more

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