Measurement method, measurement system, and non-transitory computer readable medium
An object is to provide a measurement system or the like that enables selection of appropriate new measurement targets by performing measurement on a limited number of measurement points. Proposed is a system including a measurement tool; and a computer system configured to communicate with the measurement tool, in which the computer system is configured to calculate, based on feature data of a plurality of locations on a wafer received from the measurement tool, an in-plane distribution of the feature data on the wafer (C), select, based on the calculated in-plane distribution, a new measurement point for acquiring the feature data (D), calculate, based on feature data acquired by measuring the selected new measurement point (B), a new in-plane distribution of the feature data on the wafer (F), and output at least one of the feature data of the new measurement point and the in-plane distribution which are acquired by executing the selection of the new measurement point and the calculation of the new in-plane distribution at least once (H).
1. A system comprising:
a measurement tool configured to acquire feature data of an object on a wafer; and
a computer system configured to communicate with the measurement tool, wherein
the computer system is configured to perform
first processing of receiving feature data of a plurality of locations on the wafer from the measurement tool,
second processing of calculating, based on the feature data of the plurality of locations, an in-plane distribution of the feature data on the wafer,
third processing of selecting, based on the calculated in-plane distribution, a new measurement point for acquiring the feature data,
fourth processing of calculating, based on feature data acquired by the measurement tool performing measurement on the selected new measurement point, a new in-plane distribution of the feature data on the wafer, and
fifth processing of outputting at least one of the feature data of the new measurement point and the in-plane distribution which are acquired by executing the third processing and the fourth processing at least once.
2. The system according to claim 1 , wherein
the new measurement point is selected in the third processing such that, in the in-plane distribution obtained by the fourth processing, the feature data of the plurality of locations and the new measurement point is estimated with a smaller error than that in the in-plane distribution obtained by the second processing.
3. The system according to claim 1 , wherein
the computer system is configured to select, in the third processing, an unmeasured point at which an estimation value of the feature data obtained from the in-plane distribution is maximum, at which the estimation value is in top n (n is a natural number equal to or greater than 2) or at which the estimation value is equal to or greater than a predetermined value, or one or more unmeasured points separated by a predetermined distance from the unmeasured point.
4. The system according to claim 1 , wherein
the computer system is configured to select, in the third processing, an unmeasured point at which an estimation value of the feature data obtained from the in-plane distribution is minimum, at which the estimation value is in last n (n is a natural number equal to or greater than 2) or at which the estimation value is equal to or less than a predetermined value.
5. The system according to claim 4 , wherein
the computer system is configured to select one or more unmeasured points separated by a predetermined distance from the unmeasured point selected in the third processing.
6. The system according to claim 1 , wherein
the computer system is configured to select, in the third processing, an unmeasured point at which a spatial change value of the feature data obtained from the in-plane distribution is maximum.
7. The system according to claim 6 , wherein
the computer system is configured to select one or more unmeasured points separated by a predetermined distance from the unmeasured point selected in the third processing.
8. The system according to claim 1 , wherein
the computer system is configured to select, in the third processing, an unmeasured point at which a spatial change value of the feature data obtained from the in-plane distribution is minimum.
9. The system according to claim 1 , wherein
the computer system is configured to select, in the third processing, a measurement point at which a deviation between an estimation value of the feature data obtained from the in-plane distribution and a measurement value obtained by the measurement tool satisfies a predetermined condition.
10. The system according to claim 1 , wherein
the computer system is configured to select, in the third processing, an unmeasured point according to the feature data obtained from the set in-plane distribution or a probability of a spatial change value of the feature data obtained from the in-plane distribution.
11. The system according to claim 1 , wherein
the computer system is configured to calculate the in-plane distribution of the wafer by at least one of the second processing and the fourth processing.
12. The system according to claim 11 , wherein
the computer system is configured to calculate the in-plane distribution of the wafer by performing fitting using a Zernike polynomial.
13. The system according to claim 1 , wherein
the computer system is configured to calculate an in-plane distribution of at least one exposure field included in the wafer by at least one of the second processing and the fourth processing.
14. The system according to claim 13 , wherein
the computer system is configured to calculate the in-plane distribution of the exposure field by performing fitting using a Legendre polynomial.
15. The system according to claim 1 , wherein
the computer system is configured to repeat learning of a learning device based on reinforcement learning by selecting the new measurement point.
16. The system according to claim 1 , wherein
the measurement tool is a charged particle beam device.
17. The system according to claim 16 , wherein
the charged particle beam device includes an X-ray detector configured to detect an X-ray generated by irradiation of a charged particle beam to the wafer, and the feature data is an analysis result obtained based on an output of the X-ray detector.
18. The system according to claim 1 , wherein
the measurement tool is a scanning probe microscope.