tag: machine learning

Virtual Metrology In Semiconductor Manufacturing
By Ed Sperling - 19 Sep, 2025 - Comments: 0

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

Using AI For Fault Detection And Classification In Manufacturing
By Ed Sperling - 05 Sep, 2025 - Comments: 0

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

AI Meets Device Modeling: Transforming Compact Modeling With Machine Learning
By Yiao Li - 28 Aug, 2025 - Comments: 1

As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure reliable circuit simulation and design. Correspondingly, these accuracy requirements raise demands on the accuracy and efficiency of device modeling. Modern device models often involve hundreds o... » read more

Machine Learning In Semiconductor Manufacturing
By Ed Sperling - 22 Aug, 2025 - Comments: 0

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

Wire-Friendly Domain-Specific Processor for Angstrom-Era Nodes with High Core Density (Politecnico di Torino, imec et al.)
By Technical Paper Link - 19 Aug, 2025 - Comments: 0

A new technical paper titled "Physical Design Exploration of a Wire-Friendly Domain-Specific Processor for Angstrom-Era Nodes" was published by researchers at Politecnico di Torino, EPFL, National Technical University of Athens and imec. Abstract "This paper presents the physical design exploration of a domain-specific processor (DSIP) architecture targeted at machine learning (ML), address... » read more

Data Feed Forward And How It Works: Part 1
By Roberto Colecchia - 12 Aug, 2025 - Comments: 0

With data analytics, manufacturers can gain unparalleled insights into their testing processes, identify patterns, predict failures, and optimize operations. From improving yield rates to reducing testing costs, data analytics not only enhance the quality of semiconductor devices but also drives innovation and competitiveness in the industry. Traditionally, data analytics has been performed ... » read more

AI, Product Lifecycle Management, Market Dynamics: Q&A With Jay Vleeschhouwer Of Griffin Securities 
By Bob Smith - 24 Jul, 2025 - Comments: 0

In the world of EDA, Jay Vleeschhouwer, managing director of software research at Griffin Securities, needs no introduction. His presentation on the State of EDA is standing room only at the yearly Design Automation Conference (DAC). He recently agreed to a discussion with me where we talked about AI and EDA, an interesting development with product lifecycle management and global dynamics af... » read more

Machine Learning Tools Help Bridge Design-To-Manufacturing Gap
By Katherine Derbyshire - 24 Jul, 2025 - Comments: 0

More aggressive feature scaling and increasingly complex transistor structures are driving a steady increase in process complexity, increasing the risk that a specified pattern may not be manufacturable with an acceptable yield. A single layer now requires more process steps, and each of those entails more tunable parameters than ever before. To help manage design risk, foundries provide det... » read more

The Data Dilemma In Semiconductor Testing And Why It Matters: Part 2
By Roberto Colecchia - 10 Jul, 2025 - Comments: 0

In Part 1, we explored the challenges of implementing machine learning and real-time analytics in semiconductor testing—chiefly, the difficulty of transferring device test data across multiple locations and organizations. In this post, we introduce Data Feed Forward (DFF) as it applies to ACS Advantest. What is ACS DFF? ACS DFF is a cloud-enabled solution designed to simplify, secure... » read more

Rethinking Scan Chains In Semiconductor Test
By Ed Sperling - 02 Jul, 2025 - Comments: 0

An explosion in design complexity, fueled by increased transistor density and fundamental shifts in chip architectures, are beginning to overwhelm traditional approaches to test. Defects can show up in the clock trees that drive scan chains, and even inside blocks of scan cells, which may number in the millions. Jayant D'Souza, technical product director for yield learning products in Siemens E... » read more

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