Modeling Thickness Variation in Semiconductor Thin-Film Processes — A Spatial Decomposition Approach to Machine Learning (ML)
Thickness uniformity in thin-film deposition determines downstream yield and device performance. Variation arises along two distinct axes — within a single wafer (Within-Wafer, WiW) and across wafers over time (Wafer-to-Wafer, W2W). These two axes have different physical origins and demand different diagnostic treatments. Mixing them into a single ML target forces the model to learn…