# US 7,610,170 B2 · Method for enhancing the measurement capability of multi-parameter inspection systems > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 7,610,170 B2 - Document ID: US7610170B2 - Status: Granted - Kind: B2 - Application number: 11/858,442 - Filed: 2007-09-20 - Published: 2009-01-29 - Granted: 2009-10-27 - Earliest claimed: 2007-07-27 - Assignees: Industrial Technology Research Institute - Inventors: Chun Hung Ko; Yi Sha Kuo; Chung Chu Chang - Web page: https://patentgrep.com/patent/US7610170B2 ## CPC - G01N 21/47: Scattering, i.e. diffuse reflection (G01N21/25, G01N21/41 take precedence {G01N21/55 takes precedence}) - G01B 21/08: for measuring thickness - G01B 21/20: for measuring contours or curvatures, e.g. determining profile - G01N 21/211: {Ellipsometry (optical thickness measurement G01B11/06)} - G01N 2201/1296: using neural networks - G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q) - G01B: MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS ## Abstract A method for improving the measurement capability of multi-parameter inspection systems includes performing a measuring procedure to acquire a measured signature of a sample, calculating weighting factors representing a correlation between structural parameters of the sample by using a weighting algorithm, transforming the weighting factors into a sampling function by using a transforming rule, updating the measured signature to form an updated measured signature and generating a plurality of updated nominal signatures according to the sampling function, and comparing the updated measured signature and the updated nominal signatures to determine the structural parameters of the sample. ## Claims ### Claim 1 A method for enhancing the measurement capability of multi-parameter inspection systems, comprising: performing a measuring procedure to acquire a measured signature of a sample; calculating a plurality of weighting factors representing a correlation between structural parameters of the sample by using a weighting algorithm; transforming the weighting factors into a sampling function by using a transforming rule; updating the measured signature to form an updated measured signature and a plurality of updated nominal signatures according to the sampling function; comparing the updated measured signature and the nominal signatures to determine the structural parameters of the sample; and wherein the weighting algorithm is a linear artificial neural network algorithm. ### Claim 2 (depends on 1) The method for enhancing the measurement capability of multi-parameter inspection systems of claim 1, wherein the weighting factors are larger in high-correlation regions than those in low-correlation regions. ### Claim 3 (depends on 1) The method for enhancing the measurement capability of multi-parameter inspection systems of claim 1, further comprising a step of updating sampling numbers according to the sampling function. ### Claim 4 (depends on 3) The method for enhancing the measurement capability of multi-parameter inspection systems of claim 3, wherein the sampling function decreases the sampling numbers in the high-correlation regions. ### Claim 5 (depends on 3) The method for enhancing the measurement capability of multi-parameter inspection systems of claim 3, wherein the sampling function increases the sampling numbers in the low-correlation regions. ### Claim 6 (depends on 1) The method for enhancing the measurement capability of multi-parameter inspection systems of claim 1, wherein the sampling function divides the measured signature into a plurality of sub-regions based on the weighting factors, and allocates different sampling numbers to each sub-region. ### Claim 7 (depends on 1) The method for enhancing the measurement capability of multi-parameter inspection systems of claim 1, wherein the measured signature is a relation curve of an incident angle of an incident light and an intensity of a zero order diffraction light. ### Claim 8 (depends on 1) The method for enhancing the measurement capability of multi-parameter inspection systems of claim 1, wherein the nominal signatures are generated according to the values of the structural parameters of the sample. ### Claim 9 (depends on 1) The method for enhancing the measurement capability of multi-parameter inspection systems of claim 1, wherein the nominal signatures include s-polarized light and p-polarized light signatures. ### Claim 10 (depends on 1) The method for enhancing the measurement capability of multi-parameter inspection systems of claim 1, wherein the structural parameters are thicknesses, critical dimensions and sidewall angles of gratings. ### Claim 11 A method for enhancing the measurement capability of multi-parameter inspection systems, comprising: performing a measuring procedure to acquire a measured signature of a sample; calculating a plurality of weighting factors representing a correlation between structural parameters of the sample by using a weighting algorithm; generating a sampling function with sampling numbers corresponding to the weighting factors; performing another measuring procedure to acquire an updated measured signature of the sample and generating a plurality of nominal signatures according to the sampling numbers of the sampling function; comparing the updated measured signature and the nominal signatures to determine structural parameters of the sample; and wherein the weighting algorithm is a linear artificial neural network algorithm. ### Claim 12 (depends on 11) The method for enhancing the measurement capability of multi-parameter inspection systems of claim 11, wherein the step of generating a sampling function with sampling numbers corresponding to the weighting factors comprises: calculating the weighting factors representing the correlation between the structural parameters of the sample by using the weighting algorithm; and transforming the weighting factors into the sampling function by using a transforming rule. ### Claim 13 (depends on 12) The method for enhancing the measurement capability of multi-parameter inspection systems of claim 12, wherein the weighting factors in high-correlation regions are larger than those in low-correlation regions. ### Claim 14 (depends on 11) The method for enhancing the measurement capability of multi-parameter inspection systems of claim 11, further comprising a step of updating the sampling numbers according to the sampling function. ### Claim 15 (depends on 14) The method for enhancing the measurement capability of multi-parameter inspection systems of claim 14, wherein the sampling function decreases the sampling numbers in the high-correlation regions. ### Claim 16 (depends on 14) The method for enhancing the measurement capability of multi-parameter inspection systems of claim 14, wherein the sampling function increases the sampling numbers in the low-correlation regions. ### Claim 17 (depends on 11) The method for enhancing the measurement capability of multi-parameter inspection systems of claim 11, wherein the sampling function divides the measured signature into a plurality of sub-regions based on the weighting factors, and allocates different sampling numbers to each sub-region. ### Claim 18 (depends on 11) The method for enhancing the measurement capability of multi-parameter inspection systems of claim 11, wherein the measured signature is a relation curve of an incident angle of an incident light and an intensity of a zero order diffraction light. ### Claim 19 (depends on 11) The method for enhancing the measurement capability of multi-parameter inspection systems of claim 11, wherein the nominal signatures are generated according to the values of the structural parameters of the sample. ### Claim 20 (depends on 11) The method for enhancing the measurement capability of multi-parameter inspection systems of claim 11, wherein the nominal signatures include s-polarized light and p-polarized light signatures. ### Claim 21 (depends on 11) The method for enhancing the measurement capability of multi-parameter inspection systems of claim 11, wherein the structural parameters of the sample are thicknesses, critical dimensions, and sidewall angles of gratings. ### Claim 22 A multi-parameter inspection system, comprising: a nominal signature-generating module configured to generate a plurality of nominal signatures according to predetermined values of structural parameters of a sample; a calculating module configured to calculate weighting factors representing a correlation between the structural parameters of the sample; a sampling module configured to update a sampling number according to the weighting factors; a measuring module configured to acquire a measured signature of the sample according to the sampling number; a comparing module configured to determine the structural parameters of the sample according to the measured signature and the nominal signatures; and wherein the calculating module calculates the weighting factors according to a linear artificial neural network algorithm. ### Claim 23 (depends on 22) The multi-parameter inspection system of claim 22, wherein the weighting factors calculated by the calculating module are larger in high-correlation regions than in low-correlation regions. ### Claim 24 (depends on 22) The multi-parameter inspection system of claim 22, wherein the sampling module decreases the sampling numbers in high-correlation regions. ### Claim 25 (depends on 22) The multi-parameter inspection system of claim 22, wherein the sampling module increases the sampling numbers in low-correlation regions. ### Claim 26 (depends on 22) The multi-parameter inspection system of claim 22, wherein the sampling module divides the measured signature into a plurality of sub-regions based on the weighting factors, and allocates different sampling numbers to each sub-region. ### Claim 27 (depends on 22) The multi-parameter inspection system of claim 22, wherein the measured signature is a relation curve of an incident angle of an incident light and an intensity of a zero order diffraction light. ### Claim 28 (depends on 22) The multi-parameter inspection system of claim 22, wherein the nominal signatures are generated according to the nominal values of the structural parameters of the sample. ### Claim 29 (depends on 22) The multi-parameter inspection system of claim 22, wherein the nominal signatures include s-polarized light and p-polarized light signatures. ### Claim 30 (depends on 22) The multi-parameter inspection system of claim 22, wherein the structural parameters are thickness, critical dimension, and sidewall angle of gratings.