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 .
Response to Arguments
Rejection under 35 USC 101
Per the applicant’s persuasive arguments the rejection under 35 USC 101 is withdrawn.
Rejection under 35 USC 103
Applicant's arguments filed have been fully considered but they are not persuasive. Applicant argues that the combination of Robles and Yong fail to disclose the claimed subject matter. Also, applicant states “Further, the distinction between the cited art and claim 16 may be significant because, as the Specification explains with respect to exemplary embodiments of the application consistent with claim 16, "[d]efect patterns may be decomposed into vectors that have a plurality of features, each of the features corresponding to one or more attributes of the defect pattern." Published Specification at [0055].”, (see Remarks page 26).
Examiner respectfully note that “[d]efect patterns may be decomposed into vectors that have a plurality of features, each of the features corresponding to one or more attributes of the defect pattern” is not claimed in claim 16.
Furthermore, examiner respectfully disagrees, the combination of Robles and Yong discloses all the limitation as claimed. Reference Robles in paragraph 0045, states “the pattern within the clipped area can be transformed to a density array 440, which can be expressed in a one-dimensional feature vector 450” which is read as a first fixed-dimensional feature vector, and paragraph 0057, states “Support vector machine models [which is read as trained model] are employed in some embodiments of the invention. The support vector machine models require the training and testing samples to be represented by one-dimensional (1D) vectors in the feature space”, and finally in paragraph 0010, it states “machine learning model may be used to classify the layout patterns into potential non-hotspots and potential hotspots”, [this is read as assigning the first fixed-dimensional feature vector to a class, as claimed.
And, reference Yong in col. 2 lines 23-26 states “bin a plurality of defects into a plurality of bins” and towards the end of the paragraph or lines 30-32, it states “Each of the class codes represents a different defect class” i.e. for defects are classified in various bins.
Therefore, it would have been obvious to one ordinary skilled in the art at the effective date of invention to combine the two references because they are analogous because they are solving similar problem of defect detection using image analysis. The teaching of Yong to classify the defect into a specific bin can be incorporated into the Robles system as suggested (see Robles paragraph 0010 classify the layout patterns i.e. the first fixed-dimensional feature vector), for suggestion, and this modification yields an improve defect review system (see Yong col. 2, lines 14-15) for motivation.
Therefore, rejections stand.
Regarding Double Patenting rejection
Applicant states “Since claims 16-35 of the instant application have not yet been indicated as allowable, it is believed that any submission of a Terminal Disclaimer or arguments as to the non-obvious nature of the claims would be premature. As such, it is respectfully requested that the Examiner hold this rejection in abeyance, and allow Applicant to address any remaining non-statutory double patenting issues once the rejection of the claims under 35 U.S.C. §§ 101 and 103 are resolved.”, (see Remarks pages 27-28).
Examiner respectfully noted the statement and the rejection stands.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
Claims 16-18, 21-22, 26-28 and 31-32 are rejected under 35 U.S.C. 103 as being unpatentable over Robles et al (US Pub. 2013/0031522) in view of Yong (US 10,204,290).
With respect to claim 16, Robles discloses A non-transitory computer readable medium storing a set of instructions that is executable by one or more processors of a system (see figure 6 and paragraph 0025) to cause the system to perform a method comprising:
receiving an image of a first pattern, (see paragraph 0009, wherein …context windows for the two feature encoding schemes are placed in different positions in each of training patterns);
generating a first fixed-dimensional feature vector using trained model parameters, the model parameters being based on the received image (see figure 4, and paragraph 0045, wherein …the pattern within the clipped area can be transformed to a density array 440, which can be expressed in a one-dimensional feature vector 450 “a first fixed-dimensional feature vector”; and paragraph 0057, wherein …Support vector machine models “trained model” are employed in some embodiments of the invention. The support vector machine models require the training and testing samples to be represented by one-dimensional (1D) vectors in the feature space…); and
assigning the first fixed-dimensional feature vector [a first bucket identity (ID)] (see paragraph 0010, wherein …machine learning model may be used to classify the layout patterns “assigning the first fixed-dimensional feature vector”…), as claimed.
However, Robles fails to explicitly disclose assigning the first fixed-dimensional feature vector a first bucket identity (ID), (emphasis added) as claimed.
Yong teaches assigning the first fixed-dimensional feature vector a first bucket identity (ID), (emphasis added; see col. 2, line 25, bin a plurality of defects into a plurality of bins, and within the same paragraph towards the last it states “Each of the class codes represents a different defect class”, i.e. each bin with a bucket ID) as claimed.
It would have been obvious to one ordinary skilled in the art at the effective date of invention to combine the two references because they are analogous because they are solving similar problem of defect detection using image analysis. The teaching of Yong to classify the defect into a specific bin can be incorporated into the Robles system as suggested (see Robles paragraph 0010 classify the layout patterns i.e. the first fixed-dimensional feature vector), for suggestion, and this modification yields an improve defect review system (see Yong col. 2, lines 14-15) for motivation.
With respect to claim 17, combination of Robles and Yong further discloses wherein in assigning the first fixed- dimensional feature vector the first bucket ID, the set of instructions causes the system to further perform: creating a new bucket ID for the first fixed-dimensional feature vector in response to a determination that the first pattern does not belong to one of a plurality of buckets corresponding to defect patterns, (see Yong, col. 2, lines 30-32 each of the class codes represent a different defect type) as claimed.
With respect to claim 18, combination of Robles and Yong further discloses wherein in assigning the first fixed- dimensional feature vector the first bucket ID, the set of instructions causes the system to further perform: mapping the first fixed-dimensional feature vector to the first bucket ID in response to a determination that the first pattern belongs to one of a plurality of buckets corresponding to defect patterns, (see Robles paragraph 0010, wherein … machine learning model may be used to classify the layout patterns into potential non-hotspots and potential hotspots…), as claimed.
With respect to claim 21, combination of Robles and Yong further discloses wherein the fixed-dimensional feature vector is a one-dimensional feature vector, (see Robles figure 4 numerical 450 one dimensional feature vector), as claimed.
With respect to claim 22, combination of Robles and Yong further discloses wherein the set of instructions causes the system to further perform the following to obtain the trained model parameters: obtaining a plurality of images of a plurality of patterns with assigned bucket IDs; and training model parameters for a deep learning network, (see Robles paragraph 0039 for Supervised machine learning, and Yong col. 5, lines 42-47), as claimed.
Claims 26-28 and 31-32 are rejected for the same reasons as set forth in the rejections of claims 16-18 and 21-22, because claims 26-28 and 31-32 are claiming subject matter of similar scope as claimed in claims 16-18 and 21-22.
Claims 19-20, 23-25, 29-30 and 33-35 are rejected under 35 U.S.C. 103 as being unpatentable over Robles et al (US Pub. 2013/0031522) in view of Yong (US 10,204,290) as applied to claim 17 above, and further in view of Duffy et al (US Pub. 2008/0250384).
With respect to claim 19, all the limitations are discloses by the combination of Chang and Yong as applied above in claim 17. However, they explicitly fail to disclose wherein the defect patterns comprise GDS information associated with defects, as claimed.
Duffy in the same field teaches wherein the defect patterns comprise GDS information associated with defects, (see paragraph 0070) as claimed.
It would have been obvious to one ordinary skilled in the art at the effective date of invention to combine the references as they are analogous because they are solving similar problem of wafer defect inspection and classification. The teaching of Duffy can be incorporated into the Robles and Yong’s system because Yong includes the design attributes for the machine learning (see col. 5, lines 42-45) and modification yields a improve rule based binning of defects (see Duffy paragraph 0071).
With respect to claim 20, for same reasons as set forth above for combing Robles, Yong and Duffy, combination further discloses wherein the defect patterns comprise information derived from the GDS information that includes number of sides, number of angles, dimension, shape, or a combination thereof, (see Duffy paragraph 0074 and 0075, measured in x and y, read as shape and sides) as claimed.
With respect to claim 23, for same reasons as set forth above for combing Robles, Yong and Duffy, combination further discloses wherein the set of instructions causes the system to further perform the following to obtain the trained model parameters: applying parameters of a single polygon located in a center of one of a plurality of images for the deep learning network, (see Duffy paragraph 0089) as claimed.
With respect to claim 24, for same reasons as set forth above for combing Robles, Yong and Duffy, combination further discloses wherein the set of instructions causes the system to further perform: pre-training a linear classifier network based on Graphic Data System (GDS) of a sample, (see Duffy paragraph 0070 and paragraph 0061 for training the classifier), as claimed.
With respect to claim 25, for same reasons as set forth above for combing Robles, Yong and Duffy, combination further discloses wherein the set of instructions causes the system to further perform: identifying a portion of the GDS that is associated with a region, generating label data for the portion of the GDS that indicates a location of the region, and that indicates a type of shape of polygon data associated with the portion of the GDS, and pre-training the linear classifier network based on the portion of the GDS and based on the label data, (see Duffy paragraphs 0070-0075) as claimed.
Claims 29-30 and 33-35 are rejected for the same reasons as set forth in the rejections of claims 19-20 and 23-25, because claims 29-30 and 33-35 are claiming subject matter of similar scope as claimed in claims 19-20 and 23-25.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 16-25 and 26-35 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-10 of U.S. Patent No. 11,756,182. Although the claims at issue are not identical, they are not patentably distinct from each other because claims in the instant application is obvious variant of the patented claims.
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 VIKKRAM BALI whose telephone number is (571)272-7415. The examiner can normally be reached Monday-Friday 7:00AM-3:00PM.
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/VIKKRAM BALI/Primary Examiner, Art Unit 2663
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