As semiconductor process technology moves to the 65 nm node and beyond, metrology requirements have become more stringent. Typical performance indicators of a metrology tool include its repeatability and reproducibility (R&R), and/or long-term reproducibility (or precision). Additionally, accuracy must also be considered.
One technique for accessing metrology tool accuracy is by comparing measurement data from a metrology tool under test (MTUT) with those from a reference metrology tool (RMT). For example, FIG. 1 shows a plot of critical dimension (CD) measurements from a MTUT, in this case a scanning electron microscope (SEM), with CD measurements from an atomic force microscope (AFM), RMT. Linear regression can be used to establish a relationship between the MTUT and the RMT. When performing regression, both the MTUT and the RMT are assumed to behave linearly. For example, the linear regression produces a best-fit straight line 110 represented by the equation y=a·x+b, where:                y is the MTUT data set,        x is the RMT data set, and        a and b are the linear regression slope and offset respectively.        
As shown in FIG. 1, the slope of the best-fit line is 1.2185, while its offset is 7.2768. This produces a regression residue (R2) of 0.9494, which is used as an accuracy index of the MTUT. Alternatively, the total measurement uncertainty (TMU) approach described in, for example, U.S. Pat. No. 7,221,989 may be used to compare the measurements. In such case, the TMU value is used as the accuracy index of the MTUT.
It is desirable to provide an improved method for assessing the accuracy of metrology tools.