Wafer-Level Etch Spatial Profiling for Process Monitoring from Time-Series with Time-LLM
Understanding wafer-level spatial variations from in-situ process signals is essential for advanced plasma etching process monitoring. While most data-driven approaches focus on scalar indicators such as average etch rate, actual process quality is determined by complex two-dimensional spatial distributions across the wafer. This paper presents a spatial regression model that predicts wafer-level etch depth distributions directly from multichannel in-situ process time series. We propose a Time-LLM-based spatial regression model that extends LLM reprogramming from conventional time-series forecasting to wafer-level spatial estimation by redesigning the input embedding and output projection...
| Authors | Hyunwoo Kim, Munyoung Lee, Seung Hyub Jeon et al. |
|---|---|
| Primary category | stat.AP |
| Published | 24 March 2026 |
| Last updated at source | 24 March 2026 |
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