US-12619219-B2 - Fabrication fingerprint for proactive yield management

Abstract

Systems and methods for improving wafer fabrication. Wafers may be inspected at various points in the fabrication process to generate inspection data. The inspection data and wafer-in-progress data may be used to identify defect patterns and tools and/or processes that cause wafer defects. The inspection data may be stacked to form virtual wafer maps that amplify signals to detect patterns more easily. Defect patterns and tools and/or processes may also be identified through machine learning models receiving artificial defect visualizations as input.

Inventors

• Prasad Bachiraju

Assignees

• ONTO INNOVATION INC.

Dates

Publication Date

20260505

Application Date

20220420

Claims (20)

1. 1 . A method for identifying a tool or process causing wafer defects, the method comprising: generating first inspection data by inspecting, by a first inspection device, a plurality of wafers after each of the plurality of wafers has been processed by a first fabrication tool performing a first fabrication process on each of the plurality of wafers and not by a second fabrication tool; generating second inspection data by inspecting, by a second inspection device, the plurality of wafers after each of the plurality of wafers has been processed by the second fabrication tool performing a second fabrication process on each of the plurality of wafers; generating a plurality of first wafer maps corresponding to the plurality of wafers based on the first inspection data; generating a plurality of second wafer maps corresponding to the plurality of wafers based on the second inspection data; stacking the plurality of first wafer maps together to provide a first stacked virtual wafer map; stacking the plurality of second wafer maps together to provide a second stacked virtual wafer map; performing spatial pattern recognition (SPR) operations on the first stacked virtual wafer map and the second stacked virtual wafer map; and based on an output of the SPR operations, identifying at least one of the tool or the process that caused a defect of at least one of the plurality of wafers.
2. 2 . The method of claim 1 , wherein one of the plurality of first wafer maps or the plurality of second wafer maps represents locations of defects of one of the plurality of wafers identified by the first inspection device or the second inspection device.
3. 3 . The method of claim 2 , wherein each of the plurality of first wafer maps and the plurality of second wafer maps is represented as an image.
4. 4 . The method of claim 2 , wherein each of the plurality of first wafer maps and the plurality of second wafer maps is represented as an artificially created visualization.
5. 5 . The method of claim 4 , wherein the artificially created visualization includes stacked wafer probe data or stacked metrology data.
6. 6 . The method of claim 1 , further comprising: providing an image or an artificially created visualization of one of the plurality of first wafer maps or the plurality of second wafer maps as input into a trained machine learning model; processing the image or the artificially created visualization by the trained machine learning model to generate another output; and based on the another output from the trained machine learning model, generating an indication of a type of the defect.
7. 7 . The method of claim 1 , further comprising: generating recognized fingerprint patterns based on an analysis of the plurality of first wafer maps and first wafer-in-progress (WIP) data for first wafers processed in a first fabrication facility, wherein the first WIP data includes process data and tool data for the first wafers corresponding to the plurality of first wafer maps; and storing the recognized fingerprint patterns into a fingerprint library.
8. 8 . The method of claim 7 , wherein performing the SPR operations includes comparing the first stacked virtual wafer map to the recognized fingerprint patterns in the fingerprint library.
9. 9 . The method of claim 7 , further comprising: generating other recognized fingerprint patterns based on an analysis of other wafer maps and second WIP data for second wafers processed in a second fabrication facility; and storing the other recognized fingerprint patterns in the fingerprint library.
10. 10 . The method of claim 7 , wherein the fingerprint library is stored in a cloud-based server accessible by a first computing device in the first fabrication facility and a second computing device in a second fabrication facility.
11. 11 . The method of claim 1 , wherein the SPR operations include using a fingerprint library generated from wafer-in-progress (WIP) data.
12. 12 . The method of claim 1 , wherein a first of the plurality of wafers and a second of the plurality of wafers are from different wafer lots, respectively.
13. 13 . The method of claim 1 , wherein the first inspection device is the same as the second inspection device.
14. 14 . A method for identifying a tool or process causing wafer defects, the method comprising: generating first inspection data by inspecting a wafer after the wafer has been processed according to a first fabrication process and not according to a second fabrication process; generating second inspection data by inspecting the wafer after the wafer has been processed according to the second fabrication process; generating a first wafer map based on the first inspection data; generating a second wafer map based on the second inspection data; performing operations on the first wafer map and the second wafer map; and based on an output of the operations, identifying at least one of the tool or the process that caused a defect of the wafer.
15. 15 . The method of claim 14 , wherein the first inspection data and the second inspection data are generated, respectively, by different inspection devices.
16. 16 . The method of claim 14 , wherein the operations include spatial pattern recognition operations.
17. 17 . The method of claim 14 , wherein the first fabrication process and the second fabrication process are performed by different fabrication tools.
18. 18 . The method of claim 14 , wherein the first fabrication process and the second fabrication process are different fabrication processes.
19. 19 . The method of claim 14 , wherein each of the first wafer map and the second wafer map is represented as an image.
20. 20 . The method of claim 14 , wherein each of the first wafer map and the second wafer map is represented as an artificially created visualization.

Description

RELATED APPLICATIONS This application claims priority to U.S. Provisional Patent Application Ser. No. 63/177,377, entitled FABRICATION FINGERPRINT FOR PROACTIVE YIELD MANAGEMENT, filed on Apr. 20, 2021, and U.S. Provisional Patent Application Ser. No. 63/252,281, entitled FABRICATION FINGERPRINT FOR PROACTIVE YIELD MANAGEMENT, filed on Oct. 5, 2021, the disclosures of which are hereby incorporated by reference in their entireties. FIELD OF DISCLOSURE The present disclosure is directed to semiconductor component manufacturing and defect and yield management. BACKGROUND Semiconductor wafers are manufactured or fabricated as part of the formation of semiconductor chips or other types of integrated circuits (ICs). The components of the ultimate IC may be incorporated into the wafer through a series of fabrication steps. The fabrication steps may include deposition steps where a thin film layer is added onto the wafer. The wafer then may be coated with a photoresist and the circuit pattern of a reticle may be projected onto the wafer using lithography techniques. Etching processes may then occur. Additional fabrication steps will be appreciated by those having skill in the art. At each fabrication step, the tool performing the fabrication step may cause defects or imperfections on the wafer. It is with respect to these and other general considerations that the aspects disclosed herein have been made. Also, although relatively specific problems may be discussed, it should be understood that the examples should not be limited to solving the specific problems identified in the background or elsewhere in this disclosure. SUMMARY Examples of the present disclosure describe systems and methods for improving wafer fabrication. In one aspect, the technology relates to a method for identifying a tool or process causing wafer defects. As used herein, a wafer defect is a physical defect in or on a wafer. The method includes inspecting, by an inspection device, a wafer to identify defects in the wafer after the wafer has been processed by at least one fabrication tool performing a fabrication process on the wafer; based on the inspection data generated from the inspection process, generating a wafer map; and a performing spatial pattern recognition (SPR) operation on the wafer map using a fingerprint library generated from wafer-in-progress (WIP) data, wherein the output of the SPR operation includes an identification of at least one of: a fabrication tool, a fabrication process, an inspection device, or an inspection process that caused a defect. As used herein, the term “inspection data” can include one or more of inspection test data, metrology test data, and/or electrical test data generated from respective processes. In an example, the output of the SPR includes a type of the defect. In another example, the fabrication tool is a fabrication tool in a production line. In another example, the wafer map is represented as data, rather than an image, representing the locations of the identified defects. In another example, the wafer map is a stacked virtual wafer map generated from wafer maps of a plurality of wafers that have been processed by the same tool. In a further example, the method further includes providing an image of the wafer map as input into a trained machine learning model; processing the image by the trained machine learning model to generate an output; and based on the output from the machine learning model, generating an indication of a type of defect represented in the wafer map. In a further example, the method further includes, based on the output, generating an indication of at least one of a tool or process that caused the defect. In another example, the method further includes generating at least one recognized fingerprint pattern based on an analysis of a first plurality of wafer maps and first wafer-in-progress (WIP) data for wafers processed in a first fabrication facility, wherein the first WIP data includes process and tool data for the wafers corresponding to the first plurality of wafer maps; and storing the generated at least one fingerprint pattern into a fingerprint library. In still another example, performing the SPR operation includes comparing the wafer map to fingerprint patterns in the fingerprint library. In yet another example, the method further includes generating another recognized fingerprint pattern based on an analysis of a second plurality of wafer maps and second WIP data for wafers processed in a second fabrication facility; and storing the another recognized fingerprint pattern in the fingerprint library. In still yet another example, the fingerprint library is stored in a cloud-based server accessible by a first computing device in the first fabrication facility and a second computing device in a second fabrication facility. In another aspect, the technology relates to a system for identifying a tool or a process causing wafer defects. The system includes at least one p