Manufacturing / Semiconductors
SK hynix: Virtual process metrology and anomaly cause analysis
- Company
- SK hynix
- Country
- South Korea
- Adoption stage
- In operation
- Source published
- Date basis
- The date the source was published. It can differ from the date adoption started.
- How the source was checked
- Read the full source text
The work problem
Semiconductor processes go through metrology that measures the result to confirm the process ran correctly. When the metrology rate is low, it was hard to tell apart performance differences between tools that ran the same process. The overlay prediction model in the photolithography process also concentrated only on raising accuracy, so it was hard to explain how each input variable affected the result.
Technology and data
SK hynix uses Panoptes VM, an AI based virtual metrology solution, together with the industrial AI startup Gauss Labs. It has been in use on the production floor since 2022. Virtual metrology is a way of predicting process results that were not directly measured. Using operating data from Panoptes VM, the two companies built a tool-to-tool performance matching framework and jointly propose a way to detect tool anomalies early and diagnose the cause quickly. On the overlay side they added GRACE, a gradient descent based framework. GRACE quantifies the effect of input variables on the predicted result and provides indicators that explain model performance. SK hynix has applied GRACE on the production floor since the year before this announcement, using it to spot process anomalies in time and find the cause.
Results
The two companies are presenting two papers at SPIE Advanced Lithography + Patterning 2026, one in an oral presentation and one in a poster session. The papers carry joint research results based on data from operating Panoptes VM on the actual SK hynix production floor. They said the data demonstrates that performance differences between tools, which were hard to analyse because of the low metrology rate, can be identified effectively. Gauss Labs Chief Executive Officer Kim Young-han said the result came from continuing to find use cases on the manufacturing floor even after the solution was adopted.
Limits and open questions
The source has no figures on yield or metrology cost improvement. Indicators showing the scope and effect of GRACE on the floor were also not disclosed.
Sources
- SK하이닉스, 가우스랩스와 ‘SPIE AL 2026’ 참가… AI 기반 반도체 가상계측 관련 기술 논문 발표 , SK hynix Newsroomnews.skhynix.co.kr, Accessed
Compiled from public sources. These are not results from ATF Works customers.