Contamination assessment of inductive couple plasma etching chamber under mixture of recipes using statistical method

Inductive Couple Plasma (ICP) etching tool has been commonly used for higher throughput and better width control in semiconductor processing. However, this process is often contaminated by particles, and Particle per Wafer Pass (PWP) test must be carried out to monitor the contamination. Unfortunately, in actual manufacturing, the gaseous recipes used during etching vary on the etched materials, which lead to unexpected and unpredictable byproducts and particle counts in a given production run, rendering the particle count from PWP highly stochastic which may result in missing of the time for necessary wet cleaning of the chamber. In this work, we analyze the daily PWP results from an inductively coupled plasma etching (ICP) chamber for an eight-month period. The behavior of the particle count can be modeled as a stochastic function of the accumulated gaseous recipes flowing though the chamber. The particle count is found to follow a Negative Binomial (NB) distribution with varied parameters. The model is useful in determining the optimal time for wet clean