The appropriate definition and identification of total measurement uncertainty from a group of metrology tools is becoming ever important as process tolerances continue to shrink in today's data storage and semiconductor manufacturing environments. The precision-to-tolerance ratio needs to be properly defined and minimized in order to maintain capable process control. The task of identifying components contributing the total measurement uncertainty therefore poses a major challenge for both the metrology tool manufacture's and the system owners on the customer side. In this paper, two models are proposed to perform the estimation of total measurement uncertainty component and the corresponding precision-to-tolerance ratio estimation with the methodology of the analysis of variance. Two models are developed to suit the measurement characteristics difference. The first is a crossed model designed for the nondestructive measurements and the second is a nested model developed for the measurement environments where sample destruction is unavoidable. The models analyze precision components from an individual tool as well as the entire tool group so that the error from matching is accounted for. Optical overlay and CDSEM tools were both selected for study and the measurement data were used for precision analysis. The error contribution from the bias identification was performed using a CDAFM as a reference and a CDSEM as tool under test. The methodologies developed in this paper serve as a guide for the metrology tool manufacturers and tool users to systematically estimate the total measurement uncertainty and the related improvement for precise process control.
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