tag: OCD

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

Full Wafer OCD Metrology
By Nova - 06 Jun, 2023 - Comments: 0

Authored by: Daniel Doutt*a, Ping-ju Chena, Bhargava Ravooria, Tuyen K. Trana, Eitan Rothsteinb, Nir Kampelb, Lilach Tamamb, Effi Aboodyb, Avron Gerb, Harindra Vedalac ABSTRACT Optical Critical Dimension (OCD) spectroscopy is a reliable, non-destructive, and high-throughput measurement technique for metrology and process control that is widely used in semiconductor fabrication facilities (f... » read more

Metrology Options Increase As Device Needs Shift
By Laura Peters - 10 Jan, 2023 - Comments: 1

Semiconductor fabs are taking an ‘all hands on deck’ approach to solving tough metrology and yield management challenges, combining tools, processes, and other technologies as the chip industry transitions to nanosheet transistors on the front end and heterogenous integration on the back end. Optical and e-beam tools are being extended, while X-ray inspection is being added on a case-by-... » read more

Using BDA To to Predict SAQP Pitch Walk
By Technical Paper Link - 08 Nov, 2022 - Comments: 0

A new technical paper titled "Bayesian dropout approximation in deep learning neural networks: analysis of self-aligned quadruple patterning" was published by researchers at IBM TJ Watson Research Center and Rensselaer Polytechnic Institute. Find the technical paper here. Published November 2022.  Open Access. Scott D. Halle, Derren N. Dunn, Allen H. Gabor, Max O. Bloomfield, and Mark Sh... » read more

Methods To Overcome Limited Labeled Data Sets In Machine Learning-Based Optical Critical Dimension Metrology
By Onto Innovation - 07 Sep, 2022 - Comments: 0

With the aggressive scaling of semiconductor devices, the increasing complexity of device structure coupled with tighter metrology error budget has driven up Optical Critical Dimension (OCD) time to solution to a critical point. Machine Learning (ML), thanks to its extremely fast turnaround, has been successfully applied in OCD metrology as an alternative solution to the conventional physical... » read more

Nanosheet FETs Drive Changes In Metrology And Inspection
By Karen Heyman - 09 Aug, 2022 - Comments: 0

In the Moore’s Law world, it has become a truism that smaller nodes lead to larger problems. As fabs turn to nanosheet transistors, it is becoming increasingly challenging to detect line-edge roughness and other defects due to the depths and opacities of these and other multi-layered structures. As a result, metrology is taking even more of a hybrid approach, with some well-known tools moving... » read more

The Human Hand: Curating Good Data And Creating An Effective Deep-Learning R2R Strategy For High-Volume Manufacturing
By Onto Innovation - 09 Aug, 2022 - Comments: 0

Currently, the semiconductor manufacturing industry uses artificial intelligence and machine learning to take data and autonomously learn from that data. With the additional data, AI and ML can be used to quickly discover patterns and determine correlations in various applications, most notably those applications involving metrology and inspection, whether in the front-end of the manufacturing ... » read more

Speeding Up The R&D Metrology Process
By Mark LaPedus - 16 Jul, 2020 - Comments: 0

Several chipmakers are making some major changes in the characterization/metrology lab, adding more fab-like processes in this group to help speed up chip development times. The characterization/metrology lab, which is generally under the radar, is a group that works with the R&D organization and the fab. The characterization lab is involved in the early analytical work for next-generati... » read more

What’s Next With AI In Fabs?
By Mark LaPedus - 22 Apr, 2020 - Comments: 0

Semiconductor Engineering sat down to discuss the issues and challenges with machine learning in semiconductor manufacturing with Kurt Ronse, director of the advanced lithography program at Imec; Yudong Hao, senior director of marketing at Onto Innovation; Romain Roux, data scientist at Mycronic; and Aki Fujimura, chief executive of D2S. What follows are excerpts of that conversation. Part one ... » read more

Making Chips At 3nm And Beyond
By Mark LaPedus and Ed Sperling - 16 Apr, 2020 - Comments: 4

Select foundries are beginning to ramp up their new 5nm processes with 3nm in R&D. The big question is what comes after that. Work is well underway for the 2nm node and beyond, but there are numerous challenges as well as some uncertainty on the horizon. There already are signs that the foundries have pushed out their 3nm production schedules by a few months due to various technical issu... » read more

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