DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Acknowledgement is made of Applicant’s claim of priority from U.S. Provisional Application No. 63/181,902, filed April 29, 2021 and PCT Application No. PCT/EP2022/061319, filed April 28, 2022.
Status of Claims
Claims 1-20 are pending.
Response to Arguments
Applicant’s arguments, see p. 9, filed February 20, 2026, with respect to the 35 USC 112(b) rejections have been fully considered and are persuasive. The amendment of claims 4, 12 and 19 has overcome the previous rejections and therefore they have been withdrawn.
Applicant’s arguments, see p. 9-12, filed February 20, 2026, with respect to the 35 USC 103 rejections have been fully considered but they are not persuasive.
Applicant argues that the Chen and Kim references fail to teach that the patterns are “geometric patterns”. Specifically, Applicant argues that Chen’s patterns are a result of test data from already fabricated wafers, not “geometric patterns that represent features to be formed on a portion on a wafer”. Examiner respectfully disagrees. Chen teaches stored pattern information that can include pattern templates (i.e., a template represents features to be formed on a portion of a wafer) (see Chen, Para. [0042]). Additionally, Examiner asserts that the Chen reference teaches the patterns are geometric patterns. Fig. 5 of Chen illustrates examples of stored pattern templates and pattern definitions used to classify respective patterns for selected wafer maps. As shown in Fig. 5, the patterns demonstrate different geometric patterns of points in the template. Thus, Chen in view of Kim is sufficient to teach “geometric patterns”.
Applicant further argues that the Chen reference is non-analogous art. Examiner respectfully disagrees. The present application relates to clustering patterns of an integrated circuit layout. Similarly, the Chen reference classifies patterns of a wafer and clusters the patterns together. Additionally, Examiner notes that a reference is analogous art to the claimed invention if the reference is from the same field of endeavor as the claimed invention (even if it addresses a different problem) (see MPEP 2141.01(a)). Both the disclosed invention and the Chen reference are from a field of endeavor related to automated inspection of integrated circuit chips. Thus, the Chen reference is analogous art to the present application.
Applicant further argues that the proposed references do not teach the elements of dependent claims 5 and 6. Specifically, that the Bergman reference does not teach “evaluating a cohesion degree of the respective set of patterns to obtain an evaluation result; and determining whether to suspend the recursive partitions according to the evaluation result”. Examiner respectfully disagrees. As described in the 35 USC 103 rejections below, Bergman teaches terminating a hierarchical recursive partitioning based on the difference between two image regions and if any conditions are satisfied, the partition is accepted (see Bergman, Paras. [0092]-[0093]). Based on the broadest reasonable interpretation of “a cohesion degree” and “an evaluation result” as claimed, Bergman is sufficient to teach the limitation because Bergman teaches determining whether to suspend recursive partitions based on an evaluation result (i.e., termination decision), where the evaluation result is based on a cohesion degree (i.e., a difference between two image regions). Thus, the 35 USC 103 rejections are upheld, and consequently, THIS ACTION IS FINAL.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 8-9 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. (US 2013/0288403 A1) in view of Kim et al. (US 2018/0307792 A1).
Regarding claim 1, Chen teaches a system for grouping a plurality of geometric patterns extracted from image data (Chen, Para. [0025], system for automatically classifying and clustering failure patterns that provides accurate failure pattern recognition), the system comprising:
a controller including circuitry configured to cause the system to perform (Chen, Para. [0059], processes and logic flows described can be performed by one or more programmable processors executing one or more computer programs to perform functions by operating on input data and generating output):
receiving the image data including the plurality of geometric patterns that represent features to be formed on a portion of a wafer (Chen, Para. [0042], a respective pattern for each of the respective selected wafer maps is classified using the respective determined feature and a plurality of stored pattern information. Stored pattern information can include pattern definitions and pattern templates. Pattern definitions can include feature information, object index information and/or wafer map index information, attribute information, object information and image information on the wafer map (e.g. pixel information, angle information) for respective patterns (i.e., image data including patterns));
separating the plurality of geometric patterns geometric patterns (Chen, Para. [0042], a respective pattern for each of the respective selected wafer maps is classified using the respective determined feature and a plurality of stored pattern information. A k-nearest neighbor algorithm is used to classify the respective pattern for each of the respective selected wafer maps); and
performing, on a respective set of geometric patterns, a hierarchical clustering to obtain a plurality of subsets of geometric patterns by recursively evaluating features related to similarity between geometric patterns within the respective set of geometric patterns (Chen, Para. [0046], the plurality of respective classified patterns can be ranked using a clustering algorithm with stored patterns of substantially similar classification (e.g. localized, sector, center, scratch, edge, ring, radiation, donut or top/bottom.) In various embodiments, a hierarchical clustering method can be used to form a respective wafer fingerprint for each of the respective selected wafer maps. The distance of the closest points of the two clusters can be compared. If the computed cluster distance in either algorithm is below a certain predetermined threshold, then the two clusters are completely merged. Para. [0056], a plurality of the respective classified patterns are grouped into two or more pattern clusters. In various embodiments, a hierarchical clustering method or agglomerative clustering method can be used).
Although Chen teaches separating the plurality of patterns (i.e., classifying respective patterns) (Chen, Para. [0042]), Chen does not explicitly teach separating the plurality of geometric patterns “after Fourier Transform”. However, in an analogous field of endeavor, Kim teaches the images of the portions of the design layout (i.e., plurality of patterns) may be processed by an image processing algorithm, using a Fourier transform to generating a Fourier transform representation of the image. The Fourier transform representations of the images may then be input into a machine learning algorithm for analyzing the design layout. The machine learning algorithm may extract parameters from each of the images to provide relevant characteristics of each portion of the design layout. The parameters extracted from each image may then be input to a clustering method which performs unsupervised machine learning on the dataset provided by the parameters from each image in order to find clusters in the dataset. The clustering may use a number of different ways of dividing the parameters into clusters, such as principal component analysis (PCA) (Kim, Paras. [0070]-[0071]).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Chen with the teachings of Kim by including performing the pattern classification (i.e., separating the plurality of patterns) after performing a Fourier transform on the images. One having ordinary skill in the art would have been motivated to combine these references because doing so would improve analysis of designs of integrated circuits, as recognized by Kim. Thus, the claimed invention would have been obvious to one having ordinary skill in the art before the effective filing date.
Regarding claim 8, Chen in view of Kim teaches the system of claim 1, wherein the image data is in Graphic Database System (GDS) format, Graphic Database System II (GDS II) format, Open Artwork System Interchange Standard (OASIS) format, or Caltech Intermediate Format (CIF) (Kim, Para. [0068], the design layout (i.e., image data) may be provided as a Graphic Design System (GDS) file, an Open Artwork System Interchange Standard (OASIS) file, or any other type of file that may carry a design layout).
The proposed combination as well as the motivation for combining the Chen and Kim references presented in the rejection of Claim 1, apply to Claim 8 and are incorporated herein by reference. Thus, the system recited in Claim 8 is met by Chen in view of Kim.
Claim 9 recites a computer-readable storage medium storing a program with instructions corresponding to the elements recited in Claim 1. Therefore, the recited programming instructions of this claim are mapped to the proposed combination in the same manner as the corresponding elements in its corresponding system claim. Additionally, the rationale and motivation to combine the Chen and Kim references, presented in rejection of Claim 1, apply to this claim. Finally, the combination of the Chen and Kim references discloses a computer readable storage medium (Chen, Para. [0060], one or more modules of computer program instructions encoded on a tangible machine readable storage medium for execution by, or to control the operation of, data processing apparatus. The tangible storage medium can be a computer readable medium).
Claim 16 recites a method with steps corresponding to the elements of the system recited in Claims 1. Therefore, the recited steps of this claim are mapped to the proposed combination in the same manner as the corresponding elements in its corresponding system claim. Additionally, the rationale and motivation to combine the Chen and Kim references, presented in rejection of Claim 1, apply to this claim.
Claims 2-4, 10-12 and 17-19 are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. (US 2013/0288403 A1) in view of Kim et al. (US 2018/0307792 A1), as applied to claims 1, 8-9 and 16 above, and further in view of Agarwal et al. (US 2015/0112649 A1).
Regarding claim 2, Chen in view of Kim teaches the system of claim 1, wherein the circuitry is further configured to cause the system to perform:
performing Fourier Transform on the plurality of geometric patterns to obtain, respectively, a plurality of Fourier Transform based images in a frequency domain (Kim, Para. [0091], the Fourier transform representation is a two-dimensional representation in frequency domain of an image).
The proposed combination as well as the motivation for combining the Chen and Kim references presented in the rejection of Claim 1, apply to Claim 2 and are incorporated herein by reference.
Although Chen in view of Kim teaches performing Fourier transform to obtain images in a frequency domain (Kim, Para. [0091]), they do not explicitly teach “obtaining a plurality of vectors based on the plurality of Fourier Transform based images respectively”. However, in an analogous field of endeavor, Agarwal teaches the frequency domain feature extraction mechanism extracts a feature vector from the center of the diffraction pattern (Agarwal, Para. [0046]). Each sample is an m-dimensional vector derived from the frequency domain representation of pattern j (Agarwal, Para. [0061]).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date to modify the system of Chen in view of Kim with the teachings of Agarwal by including extracting vectors from the Fourier transform based images (i.e., frequency domain representation of pattern). One having ordinary skill in the art would have been motivated to combine these references because doing so would allow for clustering frequency domain features, as recognized by Agarwal. Thus, the claimed invention would have been obvious to one having ordinary skill in the art before the effective filing date.
Regarding claim 3, Chen in view of Kim further in view of Agarwal teaches the system of claim 2, and further teaches wherein the circuitry is further configured to cause the system to perform:
evaluating similarity of the plurality of geometric patterns based on distance features of the plurality of vectors (Agarwal, Para. [0063], the mechanism computes a Fast Fourier Transform (FFT) for each clip and applies a distance metric to the resulting feature vector and the centroids of known hotspot clusters. If the distance is low (high similarity) to a cluster, than the clip represents a potential hotspot).
The proposed combination as well as the motivation for combining the Chen, Kim and Agarwal references presented in the rejection of Claim 2, apply to Claim 3 and are incorporated herein by reference. Thus, the system recited in Claim 3 is met by Chen in view of Kim further in view of Agarwal.
Regarding claim 4, Chen in view of Kim teaches the system of claim 1, as described above.
Although Chen in view of Kim teaches k-means clustering (Kim, Para. [0099]), they do not explicitly teach “wherein the plurality of geometric patterns after Fourier Transform are separated into multiple sets of geometric patterns using a k-means algorithm based on the distance features”. However, in an analogous field of endeavor, Agarwal teaches the clustering algorithm uses the feature vectors to cluster hotspot clips. In one example embodiment, the clustering algorithm is a k-means clustering algorithm, which is a method of vector quantization originally from signal processing that is popular for cluster analysis in data mining. The k-means clustering algorithm aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster (Agarwal, Para. [0048]). K-means clustering aims to partition the n observations into k sets so as to minimize the within-cluster sum of squares (WCSS) (Agarwal, Para. [0049]). Assign each observation to the cluster whose mean yields the least within-cluster sum of squares. Since the sum of squares is the squared Euclidean distance, this is intuitively the “nearest” mean (Agarwal, Para. [0052]).
The proposed combination as well as the motivation for combining the Chen, Kim and Agarwal references presented in the rejection of Claim 2, apply to Claim 4 and are incorporated herein by reference. Thus, the system recited in Claim 4 is met by Chen in view of Kim further in view of Agarwal.
Claims 10-12 recite computer-readable storage mediums storing programs with instructions corresponding to the elements recited in Claims 2-4, respectively. Therefore, the recited programming instructions of these claims are mapped to the proposed combination in the same manner as the corresponding elements in their corresponding system claims. Additionally, the rationale and motivation to combine the Chen, Kim and Agarwal references, presented in rejection of Claim 2, apply to these claims. Finally, the combination of the Chen, Kim and Agarwal references discloses a computer readable storage medium (Chen, Para. [0060], one or more modules of computer program instructions encoded on a tangible machine readable storage medium for execution by, or to control the operation of, data processing apparatus. The tangible storage medium can be a computer readable medium).
Claims 17-19 recite methods with steps corresponding to the elements of the systems recited in Claims 2-4, respectively. Therefore, the recited steps of these claims are mapped to the proposed combination in the same manner as the corresponding elements in their corresponding system claims. Additionally, the rationale and motivation to combine the Chen, Kim and Agarwal references, presented in rejection of Claim 2, apply to this claim.
Claims 5-6, 13-14 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. (US 2013/0288403 A1) in view of Kim et al. (US 2018/0307792 A1), as applied to claims 1, 8-9 and 16 above, and further in view of Bergman et al. (US 2011/0013837 A1).
Regarding claim 5, Chen in view of Kim teaches the system of claim 1, as described above.
Although Chen in view of Kim teaches hierarchical clustering by recursively evaluating features (Chen, Para. [0046]), they do not explicitly teach “performing recursive partitions on the respective set of geometric patterns based on results of the recursively evaluating the feature at respective hierarchical levels”. However, in an analogous field of endeavor, Bergman teaches hierarchical recursive partitioning of an image (Bergman, Para. [0031]). After the graph has been created, the partitioning module recursively partitions the vertices into two subsets at each step. The recursive partitioning process can be terminated at any point, with the recursion varying in depth in different parts of the recursion tree (Bergman, Para. [0033]).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Chen in view of Kim with the teachings of Bergman by including performing recursive partitions on the image (i.e., set of patterns) based on evaluating the feature at respective hierarchical levels. One having ordinary skill in the art would have been motivated to combine these references because doing so would allow for automatic image segmentation in ways that require minimal manual intervention, as recognized by Bergman. Thus, the claimed invention would have been obvious to one having ordinary skill in the art before the effective filing date.
Regarding claim 6, Chen in view of Kim further in view of Bergman teaches the system of claim 5, and further teaches wherein the circuitry is further configured to cause the system to perform:
performing a cohesion test for evaluating the feature, the cohesion test comprising:
evaluating a cohesion degree of the respective set of geometric patterns to obtain an evaluation result (Bergman, Para. [0093]; Fig. 8, In accordance with the method of FIG. 8, for each image region (referred to as a "segment" in FIG. 8) in a pair of image regions the mean of each color channel (e.g., L, A, B) and the mean texture ("tex") is computed (FIG. 8, block 50). The differences between the computed mean values for the two image regions are computed (FIG. 8, block 52). If any of the global difference conditions listed in block 54 are satisfied, the partition is accepted (FIG. 8, block 56); otherwise, if any of the deviation magnitude conditions listed in block 58 are satisfied, the partition is accepted (FIG. 8, block 60); otherwise, the partition is rejected (FIG. 8, block 62)); and
determining whether to suspend the recursive partitions according to the evaluation result (Bergman, Para. [0092], FIG. 8 shows an embodiment of a method of terminating the hierarchical recursive partitioning in which the termination decision is based primarily on the difference between the two cut regions in the CIELAB color space or in color entropy).
The proposed combination as well as the motivation for combining the Chen, Kim and Bergman references presented in the rejection of Claim 5, apply to Claim 6 and are incorporated herein by reference. Thus, the system recited in Claim 6 is met by Chen in view of Kim further in view of Bergman.
Claims 13-14 recite computer-readable storage mediums storing programs with instructions corresponding to the elements recited in Claims 5-6, respectively. Therefore, the recited programming instructions of these claims are mapped to the proposed combination in the same manner as the corresponding elements in their corresponding system claims. Additionally, the rationale and motivation to combine the Chen, Kim and Bergman references, presented in rejection of Claim 5, apply to these claims. Finally, the combination of the Chen, Kim and Bergman references discloses a computer readable storage medium (Chen, Para. [0060], one or more modules of computer program instructions encoded on a tangible machine readable storage medium for execution by, or to control the operation of, data processing apparatus. The tangible storage medium can be a computer readable medium).
Claim 20 recites a method with steps corresponding to the elements of the system recited in Claims 5. Therefore, the recited steps of this claim are mapped to the proposed combination in the same manner as the corresponding elements in its corresponding system claim. Additionally, the rationale and motivation to combine the Chen and Kim references, presented in rejection of Claim 5, apply to this claim.
Claims 7 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. (US 2013/0288403 A1) in view of Kim et al. (US 2018/0307792 A1) further in view of Bergman et al. (US 2011/0013837 A1), as applied to claims 5-6, 13-14 and 20 above, and further in view of Niklas Karlsson (US 2017/0249652 A1).
Regarding claim 7, Chen in view of Kim further in view of Bergman teaches the system of claim 6, as described above.
Although Chen in view of Kim further in view of Bergman teaches a termination decision of recursive partition is based on an evaluation result (Bergman, Para. [0092]), they do not explicitly teach “receiving a user input indicating a parameter associated with evaluating the cohesion degree”. However, in an analogous field of endeavor, Karlsson teaches configuration parameters that can act as termination criteria for recursively partitioning P/V information to produce a representation of a P/V curve. It will be appreciated that the configuration parameters discussed above can be user defined parameters (e.g., through user input) (Karlsson, Para. [0041]).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Chen in view of Kim further in view of Bergman with the teachings of Karlsson by including that the parameter associated with evaluating the cohesion degree (i.e., the parameter for termination decision) is a user defined parameter (i.e., a user input indicating a parameter). One having ordinary skill in the art would have been motivated to combine these references because doing so would allow for user-defined termination criteria for terminating a recursive partitioning, as recognized by Karlsson. Thus, the claimed invention would have been obvious to one having ordinary skill in the art before the effective filing date.
Claim 15 recites a computer-readable storage medium storing a program with instructions corresponding to the elements recited in Claim 7. Therefore, the recited programming instructions of this claim are mapped to the proposed combination in the same manner as the corresponding elements in its corresponding system claim. Additionally, the rationale and motivation to combine the Chen, Kim, Bergman and Karlsson references, presented in rejection of Claim 7, apply to this claim. Finally, the combination of the Chen, Kim, Bergman and Karlsson references discloses a computer readable storage medium (Chen, Para. [0060], one or more modules of computer program instructions encoded on a tangible machine readable storage medium for execution by, or to control the operation of, data processing apparatus. The tangible storage medium can be a computer readable medium).
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Emma Rose Goebel whose telephone number is (703)756-5582. The examiner can normally be reached Monday - Friday 7:30-5.
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/Emma Rose Goebel/Examiner, Art Unit 2662
/AMANDEEP SAINI/Supervisory Patent Examiner, Art Unit 2662
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