The Effect of Initial State Estimates on Just-in-Time Adaptive Disturbanc Estimation

Abstract

Run-to-Run control algorithms for high-mix semiconductor processes typically require that the initial product state estimates have sufficient accuracy for satisfactory control. In this paper, we use historical process data and apply single observation just-in-time adaptive disturbance estimation (JADE) to find the initial product state estimates. Single observation JADE with random selection, high-frequency sampling, and exclusion of the earliest data from the average is shown to provide satisfactory initial product state estimates. The effect of initial state estimate accuracy is demonstrated by several simulation and industrial data examples. We also provide a method to estimate relative confidence between individual product state estimates, information that may be used to determine assignment of process error between the tool and product state.