Process trend monitoring using key sensitive index

Process monitoring is essential to maintain product quality in semiconductor manufacturing. However, unlike chemical processes, semiconductor manufacturing processes exhibit the following characteristics: (1) much shorter (minutes) and often variable (deliberately adjusted) batch time, (2) multiple processing steps (10-20) in each batch, (3) only some particular processing steps constituting the quality-determining steps, and (4) mixed products for the same batch processing. In this work, instead of incorporating a large number of trajectory data with variable batch time and possibly "missing" data for some process variables using multivariate statistics, a processinsight-based approach, key sensitive index (KSI), is taken. From process knowledge, the key sensitive time-slot in the recipe is identified. Next, possible key sensitive process variables (KSV) are selected and validated according to the process trend correlation. A simple batch reactor example is used to illustrate the KSV selection procedure. Then, an index for these variables is sought. Two integrated circuit processing examples from real fab data are used to illustrate the KSI-based approach and results clearly indicate that process trend is captured using KSI-based approach.