logo
ResearchBunny Logo
Human-machine collaboration for improving semiconductor process development

Engineering and Technology

Human-machine collaboration for improving semiconductor process development

K. J. Kanarik, W. T. Osowiecki, et al.

This groundbreaking research by Keren J. Kanarik and colleagues from Lam Research Corporation explores the application of Bayesian optimization algorithms in semiconductor chip fabrication. Discover how a hybrid strategy combining human expertise with computer efficiency significantly reduces costs while overcoming cultural challenges in collaboration.

00:00
00:00
Playback language: English
Abstract
Developing chemical plasma processes for semiconductor chip fabrication is costly and time-consuming. This paper investigates the use of Bayesian optimization algorithms to reduce this cost. A virtual process game was created to benchmark human engineers and computer algorithms. Results show that human engineers excel in early stages, while algorithms are more efficient near the target tolerances. A hybrid "human first-computer last" (HF-CL) strategy significantly reduced cost-to-target. The study also highlights cultural challenges in human-computer collaboration.
Publisher
Nature
Published On
Apr 27, 2023
Authors
Keren J. Kanarik, Wojciech T. Osowiecki, Yu (Joe) Lu, Dipongkar Talukder, Niklas Roschewsky, Sae Na Park, Mattan Kamon, David M. Fried, Richard A. Gottscho
Tags
Bayesian optimization
semiconductor fabrication
cost reduction
human-computer collaboration
hybrid strategy
Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny