Diagnostic monitoring procedure for automated measurement systems

This paper describes a new method for monitoring the performance of metrology systems. The objective of the technique is to both identify deviant performance and estimate the likely cause. The method is driven by the assumption that all variation in a measurement system is systematic until proven random. This assumption in turn guides the choice of sampling plan and analysis to extract the maximum amount of information possible from a given number of measurements. Diagnostic capability is achieved by selecting a sampling plan which yields data for estimates of all known error modes of the instrument. Consequently, somewhat larger sampling plans are required and the technique is generally more appropriate for automated measurement systems. The concept is illustrated by example using automated scanning electron microscopes used for critical dimension measurement in the semiconductor manufacturing process. Experimental results illustrating the response of the monitor to programmed deviation are presented.