Process control of semiconductor fabrication based on spectra quality metrics
A process control method for manufacturing semiconductor devices, including determining a quality metric of a production semiconductor wafer by comparing production scatterometric spectra of a production structure of the production wafer with reference scatterometric spectra of a reference structure of reference semiconductor wafers, the production structure corresponding to the reference structure, the reference spectra linked by machine learning to a reference measurement value of the reference structure, determining a process control parameter value (PCPV) of a wafer processing step, the PCPV determined based on measurement of the production wafer and whose contribution to the PCPV is weighted with a first predefined weight based on the quality metric, and based on a measurement of a different wafer and whose contribution to the PCPV is weighted with a second predefined weight based on the quality metric, and controlling, with the PCPV, the processing step during fabrication.
1. A method for use in process control during manufacture of semiconductor devices on semiconductor wafers, the method comprising:
determining a quality metric of a production semiconductor wafer by comparing production scatterometric spectra of a production structure of the production semiconductor wafer with reference scatterometric spectra of a reference structure of one or more reference semiconductor wafers,
wherein the production structure corresponds to the reference structure, and
wherein the reference scatterometric spectra are linked by machine learning to a reference measurement value of the reference structure;
determining a process control parameter value of a semiconductor wafer processing step, wherein the process control parameter value is determined
a) based on a measurement of the production semiconductor wafer and whose contribution to the process control parameter value is weighted with a first predefined weight based on the quality metric of the production semiconductor wafer, and
b) based on a measurement of at least one different semiconductor wafer and whose contribution to the process control parameter value is weighted with a second predefined weight based on the quality metric of the production semiconductor wafer,
wherein the measurement of the production semiconductor wafer and the measurement of at least one different semiconductor wafer include any of a) the production scatterometric spectra and b) any other type of measurement produced using metrology techniques applicable to semiconductor wafers; and
controlling, with the process control parameter value, the semiconductor wafer processing step during semiconductor wafer fabrication.
2. The method according to claim 1 wherein the reference scatterometric spectra include multiple sets of sets of scatterometric spectra collected from the reference semiconductor wafers, wherein each of the sets of reference scatterometric spectra is linked by machine learning to a reference measurement value of the reference structure.
3. The method according to claim 1 wherein the quality metric is a measure of similarity of the production scatterometric spectra to the reference scatterometric spectra.
4. The method according to claim 1 wherein the controlling comprises providing the process control parameter value to an advanced process control system configured to control the semiconductor wafer processing step.
5. The method according to claim 1 wherein the reference semiconductor wafer and the production semiconductor wafer are fabricated using an identical fabrication process, and wherein the reference scatterometric spectra and the production scatterometric spectra are collected at an identical point during the fabrication process.
6. The method according to claim 1 wherein the at least one different semiconductor wafer is fabricated prior to fabrication of the production semiconductor wafer in a common lot of multiple semiconductor wafers representing a common product type.
7. The method according to claim 6 wherein the process control parameter value is determined based additionally on a measurement of at least one additional semiconductor wafer and whose contribution to the process control parameter value is weighted with a third predefined weight based on the quality metric, and
wherein the at least one additional semiconductor wafer is fabricated prior to fabrication of the production semiconductor wafer and in at least one different lot of multiple semiconductor wafers of the common product type.
8. The method according to claim 7 wherein the at least one different lot is produced within a predefined time period prior to fabrication of the production semiconductor wafer.
9. The method according to claim 8 wherein the process control parameter value is determined based additionally on a measurement of at least one different-product semiconductor wafer and whose contribution to the process control parameter value is weighted with a fourth predefined weight based on the quality metric, and
wherein the at least one different-product semiconductor wafer is fabricated prior to fabrication of the production semiconductor wafer and in at least one different-product lot of multiple semiconductor wafers of a different product type.
10. The method according to claim 9 wherein the at least one different-product lot is produced within a second predefined time period prior to fabrication of the production semiconductor wafer.
11. A system for use in process control during manufacture of semiconductor devices on semiconductor wafers, the system comprising:
a quality metric generator configured to determine a quality metric of a production semiconductor wafer by comparing production scatterometric spectra of a production structure of the production semiconductor wafer with reference scatterometric spectra of a reference structure of one or more reference semiconductor wafers,
wherein the production structure corresponds to the reference structure, and
wherein the reference scatterometric spectra are linked by machine learning to a reference measurement value of the reference structure;
a process controller configured to
determine a process control parameter value of a semiconductor wafer processing step, wherein the process control parameter value is determined
a) based on a measurement of the production semiconductor wafer and whose contribution to the process control parameter value is weighted with a first predefined weight based on the quality metric of the production semiconductor wafer, and
b) based on a measurement of at least one different semiconductor wafer and whose contribution to the process control parameter value is weighted with a second predefined weight based on the quality metric of the production semiconductor wafer,
wherein the measurement of the production semiconductor wafer and the measurement of at least one different semiconductor wafer include any of a) the production scatterometric spectra and b) any other type of measurement produced using metrology techniques applicable to semiconductor wafers, and
control, with the process control parameter value, the semiconductor wafer processing step during semiconductor wafer fabrication.
12. The system according to claim 11 wherein the reference scatterometric spectra include multiple sets of sets of scatterometric spectra collected from the reference semiconductor wafers, wherein each of the sets of reference scatterometric spectra is linked by machine learning to a reference measurement value of the reference structure.
13. The system according to claim 11 wherein the quality metric is a measure of similarity of the production scatterometric spectra to the reference scatterometric spectra.
14. The system according to claim 11 wherein the process controller is configured to provide the process control parameter value to an advanced process control system configured to control the semiconductor wafer processing step.
15. The system according to claim 11 wherein the reference semiconductor wafer and the production semiconductor wafer are fabricated using an identical fabrication process, and wherein the reference scatterometric spectra and the production scatterometric spectra are collected at an identical point during the fabrication process.
16. The system according to claim 11 wherein the at least one different semiconductor wafer is fabricated prior to fabrication of the production semiconductor wafer in a common lot of multiple semiconductor wafers representing a common product type.
17. The system according to claim 16 wherein the process controller is configured to determine the process control parameter value based additionally on a measurement of at least one additional semiconductor wafer and whose contribution to the process control parameter value is weighted with a third predefined weight based on the quality metric, and
wherein the at least one additional semiconductor wafer is fabricated prior to fabrication of the production semiconductor wafer and in at least one different lot of multiple semiconductor wafers of the common product type.
18. The system according to claim 17 wherein the at least one different lot is produced within a predefined time period prior to fabrication of the production semiconductor wafer.
19. The system according to claim 18 wherein the process controller is configured to determine the process control parameter value based additionally on a measurement of at least one different-product semiconductor wafer and whose contribution to the process control parameter value is weighted with a fourth predefined weight based on the quality metric, and
wherein the at least one different-product semiconductor wafer is fabricated prior to fabrication of the production semiconductor wafer and in at least one different-product lot of multiple semiconductor wafers of a different product type.
20. The system according to claim 11 wherein the production scatterometric spectra are measured by a metrology system integrated with a semiconductor wafer manufacturing system, and wherein the reference scatterometric spectra are obtained by a stand-alone metrology system employing conventional machine learning algorithms.