A Novel Method for Deposit Accumulation Assessment in Dry Etching Chamber

Abstract

Particle contamination in the dry etching chamber is one of the major issues in the semiconductor manufacturing. Particles on the wafer surface may cause wafer defects and yield loss. Therefore, particle monitoring is important to support contamination control and predictive maintenance activities. To achieve this goal, this paper proposes a virtual metrology (VM) method to estimate the deposit accumulation on the chamber wall, which can be a major root cause of the particle contamination. In the proposed method, the piecewise linear approximation (PLA) is employed and modified to derive a general segmentation template for the trace signals. Based on the trace segmentation template, important features that relate to the deposit accumulation are better extracted and modeled. To justify the effectiveness of the proposed method, we validate our method on the etching data from three different maintenance cycles. In the results, the proposed method with trace segmentation has improved performance compared to the VM model that does not segment the data, as well as the VM model that partitions the trace data by step number. The deposit accumulation indicator given by the proposed method demonstrates a slow trend over etching cycles and it matches well with the off-line metrology measurements.