DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 04/07/2025 has been entered.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 3-6, 12-13, 14, 20, 23-26 and 29-30 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 3, 12 and 20 recite the limitation “potentially marginal quality,” but the limitation “potentially marginal quality” is a subjective term, and as such, indefinite.
Claim 6 and 14 recite the limitation “radius of three”, but it is not clear what the radius of three means, since there is no further recitation of any dimension related to the radius.
Previous rejection associated with “radius of three” with respect to claims 2, 11 and 18 are withdrawn in view of the Applicant’s amendment field on 04/07/2025.
Claim Rejections - 35 USC § 101
4. Previous rejection is withdrawn under the practical application.
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.
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 1-2, 7, 9-11 and 15-18 are rejected under 35 U.S.C. 103 as being unpatentable over Asbag et al., US-PGPUB 2019/0333208 (hereinafter Asbag) in view of Niewczas et al., US-PGPUB 2020/0272865 (hereinafter Niewczas) and Trumbauer et al., US-PGPUB 2018/0047149 (hereinafter Trumbauer)
Regarding Claims 1, 10 and 16-17. Asbag discloses
electrically testing a semiconductor wafer (Paragraphs [0004]-[0007]),
failed die clustering (Fig. 3, each square in the wafer is a die; Paragraph [0010], defect clusters; Paragraph [0003], Paragraphs [0043]-[0044], scanning at an entire die), comprising:
extracting a data set of failed die on the semiconductor wafer from a wafer map for the wafer (Fig. 2, 202; Paragraph [0010], obtain one more defect clusters; Paragraph [0046], can include false alarms or [0004], false positives; Paragraphs [0002]-[0003], semiconductor wafer); determining a density parameter for clustering the failed die (Paragraph [0010], spatial density; [0052]; [0062]; [0065]); removing false failures from the data set of failed die to generate a reduced data set of failed die (Paragraph [0082], nuisance defects are filtered out; where nuisance defects include false/alarms (Paragraphs [0048]-[0050]), removing failed die in low failure regions of the wafer from the reduced data set (Fig. 2, 203, defect filtration for the non-clustered defect), locating clusters of failed die in the reduced data set after removing the failed die in the low failure density regions (Fig. 2, 208; Paragraph [0034], Fig. 5 illustrating the DOI identified on a defect map; Paragraphs [0032]; [0035]; Paragraphs [0054]; [0062]-[0068])
Asbag does not disclose locating clusters of failed die in the reduced data set by executing a density-based spatial clustering of applications with noise (DBSCAN) algorithm with the density parameter, and applying a guard band to each located cluster.
Niewczas discloses classifying and locating the identified defects using DBSCAN (Paragraphs [0024], classification based on different features, Figs. 2A, B; [0026]-[0028])
Trumbauer discloses applying guard banding to located cluster (Fig. 10B; Paragraph [0034]; [0068]; [0072]; [0005])
At the time of the invention filed, it would have been obvious to a person of ordinary skill in the art to use the teaching of Niewczas and Trumbauer in Asbag and accurately locate clusters of failed die in the reduced data set, after removing the failed die in the low failure density regions by executing a density-based spatial clustering of applications with noise (DBSCAN) algorithm with the density parameter, and apply a guard band to each located cluster, so as to improve reliability.
Regarding Claims 2, 11 and 18. Asbag discloses a failed die is in a low failure density region when the die has less than three failed die neighbors within a radius of three die from the failed die (Paragraphs [0071]-[0072], filtering the non-clustered defects; Fig. 3, such as 307, 308)
Regarding Claim 7. Trumbauer discloses using a user specified width for the guard band (Figs. 8 and 9; Paragraphs [0021]-[0022])
Regarding Claims 9 and 15. Asbag discloses the wafer map is generated by electrical probe testing of the wafer (Paragraph [0046]; [0049])
8. Claims 3, 12 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Asbag, US-PGPUB 2019/033208 in view of Niewczas, US-PGPUB 2020/0272865 and Trumbauer, US-PGPUB 2018/0047149 as applied to Claim 1 above, and further in view of Moreno-Lizaranzu et al., “Improving Electronic Sensor reliability by robust outlier screening,” Sensors (2013) (hereinafter Moreno) (cited by the Applicant)
Regarding Claim 3. Asbag discloses failed die clustering (Fig. 3, each square in the wafer is a die; Paragraph [0010], defect clusters; Paragraph [0003], Paragraphs [0043]-[0044], scanning at an entire die), comprising:
connecting a semiconductor wafer to a testing system (Paragraphs [0004]-[0007]),
extracting a data set of failed die on the semiconductor wafer from a wafer map for the semiconductor wafer (Fig. 2, 202; Paragraph [0010], obtain one more defect clusters; Paragraph [0046], can include false alarms or [0004], false positives); determining a density parameter for clustering the failed die (Paragraph [0010], spatial density; [0052]; [0062]; [0065]); removing false failures from the data set of failed die to generate a reduced data set of failed die (Paragraph [0082], nuisance defects are filtered out; where nuisance defects include false/alarms (Paragraphs [0048]-[0050]), removing failed die in low failure regions of the wafer from the reduced data set (Fig. 2, 203, defect filtration for the non-clustered defect), locating clusters of failed die in the reduced data set after removing the failed die in the low failure density regions (Paragraph [0034], Fig. 5 illustrating the DOI identified on a defect map; Paragraphs [0032]; [0035]; Paragraphs [0054]; [0062]-[0068])
Asbag does not disclose locating clusters of failed die in the reduced data set by executing a density-based spatial clustering of applications with noise (DBSCAN) algorithm with the density parameter, and applying a guard band to each located cluster.
Niewczas discloses classifying and locating the identified defects using DBSCAN (Paragraphs [0024]; [0026]-[0028])
Trumbauer discloses applying guard banding to located cluster (Fig. 10B; Paragraph [0034]; [0068]; [0072]; [0005])
At the time of the invention filed, it would have been obvious to a person of ordinary skill in the art to use the teaching of Niewczas and Trumbauer in Asbag and accurately locate clusters of failed die in the reduced data set after removing the failed die in the low failure density regions by executing a density-based spatial clustering of applications with noise (DBSCAN) algorithm with the density parameter, and apply a guard band to each located cluster, so as to improve reliability.
Asbag further discloses locating clusters of trapped good die (Fig. 3, 303). The modified Asbag does not explicitly disclose indicating that the trapped die are of potentially marginal quality.
Moreno discloses locating clusters of trapped good die and indicating that the trapped die are of potentially marginal quality (Section 3.1; Fig. 5; Introduction)
At the time of the invention filed, it would have been obvious to a person of ordinary skill in the art to use the teaching of Moreno in the modified Asbag and locate clusters of trapped good die and indicate that the trapped die are of potentially marginal quality, so as to improve reliability.
Regarding Claims 12 and 20. Asbag discloses locating clusters of trapped good die (Fig. 3, 303). The modified Asbag does not explicitly disclose indicating that the trapped die are of potentially marginal quality.
Moreno discloses locating clusters of trapped good die and indicating that the trapped die are of potentially marginal quality (Section 3.1; Fig. 5; Introduction)
At the time of the invention filed, it would have been obvious to a person of ordinary skill in the art to use the teaching of Moreno in the modified Asbag and locate clusters of trapped good die and indicate that the trapped die are of potentially marginal quality, so as to improve reliability.
9. Claims 21 and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Asbag et al., US-PGPUB 2019/0333208 in views of Niewczas et al., US-PGPUB 2020/0272865 and Trumbauer et al., US-PGPUB 2018/0047149 as applied to Claim 1, and further in view of Balog, US-PGPUB 2007/0233629 (hereinafter Balog)
Regarding Claims 21-22. The modified Asbag does not further disclose including evaluating results of the testing versus statistical yield and bin limits, and further releasing the semiconductor wafer for further processing when the evaluated results meet or exceed the statistical yield and bin limits
Balog disclose including evaluating results of the testing versus statistical yield and bin limits, and further releasing the semiconductor wafer for further processing when the evaluated results meet or exceed the statistical yield and bin limits (Paragraph [0095])
Statistical bin limit is a benchmark for quality control in semiconductor industry. As such, at the time of the invention filed, it would have been obvious to a person of ordinary skill in the art to use the teaching of Balog in the modified Asbag and evaluate results of the testing versus statistical yield and bin limits, and further release the semiconductor wafer for further processing when the evaluated results meet or exceed the statistical yield and bin limits, so as to improve product reliability.
10. Claims 23 and 24 are rejected under 35 U.S.C. 103 as being unpatentable over Asbag, US-PGPUB 2019/033208 in views of Niewczas, US-PGPUB 2020/0272865, Trumbauer, US-PGPUB 2018/0047149 and Moreno-Lizaranzu et al., “Improving Electronic Sensor reliability by robust outlier screening,” Sensors (2013) as applied to Claim 3 above, and further in view of Balog, US-PGPUB 2007/0233629.
Regarding Claims 23 and 25. The modified Asbag does not further disclose including evaluating results of the testing versus statistical yield and bin limits, and further releasing the semiconductor wafer for further processing when the evaluated results meet or exceed the statistical yield and bin limits
Balog disclose including evaluating results of the testing versus statistical yield and bin limits, and further releasing the semiconductor wafer for further processing when the evaluated results meet or exceed the statistical yield and bin limits (Paragraph [0095])
Statistical bin limit is a benchmark for quality control in semiconductor industry. As such, at the time of the invention filed, it would have been obvious to a person of ordinary skill in the art to use the teaching of Balog in the modified Asbag and evaluate results of the testing versus statistical yield and bin limits, and further release the semiconductor wafer for further processing when the evaluated results meet or exceed the statistical yield and bin limits, so as to improve product reliability.
Allowable Subject Matter
Claims 4 and 13 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims and overcome the outstanding 112 rejection with respect to dependent claims 3 and 12.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding Claim 4 and 13. The prior arts do not teach or suggest a combination, including locating clusters of trapped good die further comprises: locating clusters of good die in a data set of good die on the wafer using the DBSCAN algorithm with minPts = 1 and eps = 1, wherein the data set of good die does not include any good die in the guard bands applied to the located clusters of failed die; and identifying clusters of trapped good die in the clusters of good die using a threshold number of die.
Claims 6 and 14 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding Claims 6 and 14. The prior arts do not teach or suggest a combination, including extract a data set of failed die on the semiconductor wafer from a wafer map for the wafer; determine a density parameter for clustering the failed die, remove false failures from the data set of failed die to generate a reduced data set of failed die, locate clusters of failed die in the reduced data set by executing a density- based spatial clustering of applications with noise (DBSCAN) algorithm with the density parameter, compute a count of failed die neighbors within a neighborhood of a radius of three for each failed die in the failed die data set, compute the density parameter based on an average count of failed die neighbors, a standard deviation of the counts of failed die neighbors, and a coefficient representing a relative density of the wafer, and applying a guard band to each located cluster of failed die in the reduced data set.
Response to Arguments
Applicant's arguments filed 04/07/2025 have been fully considered but they are not persuasive.
14. In regard to the 103 rejection, with respect to the independent claims, the Applicant argues the following: “Examiner determines that Asbag teaches,” extracting a data set of failed die on a wafer from a wafer map for the wafer (Fig. 2, 202l; Paragraph [0010], obtain one or more defect clusters; Paragraph [0046], can include false alarms or [0004], false positives)’ (OA, dated 11/08/2024 p. 6, lines 14-16). Asbag, however, does not support Examiners determination:
In Response, the Examiner respectfully disagrees. Asbag discloses extracting a data set of failed die on a wafer from a wafer map for the wafer (Fig. 2, step 202, defect cluster on a defect map; Paragraph [0010], obtain one more defect clusters; Paragraph [0046], can include false alarms or [0004], false positives), as shown below. Additionally, the claim does not recite “mapping the coordinate to any specific die(dies) as having defects”, and Applicant is once again arguing about a limitation that is not claimed.
Applicant argues the following:
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156
696
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134
694
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100
698
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226
698
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232
696
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In Response, the Examiner respectfully disagrees. Asbag discloses electrically testing a semiconductor wafer (Paragraphs [0004]-[0007]), and extracting a data set of failed die on the semiconductor wafer from a wafer map for the wafer (Fig. 2, 202; Paragraph [0010], obtain one more defect clusters; Paragraph [0046], can include false alarms or [0004], false positives; Paragraphs [0002]-[0003], semiconductor wafer); determining a density parameter for clustering the failed die (Paragraph [0010], spatial density; [0052]; [0062]; [0065]); removing false failures from the data set of failed die to generate a reduced data set of failed die (Paragraph [0082], nuisance defects are filtered out; where nuisance defects include false/alarms (Paragraphs [0048]-[0050]), removing failed die in low failure regions of the wafer from the reduced data set (Fig. 2, 203, defect filtration for the non-clustered defect), locating clusters of failed die in the reduced data set after removing the failed die in the low failure density regions (Fig. 2, 208; Paragraph [0034], Fig. 5 illustrating the DOI identified on a defect map; Paragraphs [0032]; [0035]; Paragraphs [0054]; [0062]-[0068])
Applicant argues the following:
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234
632
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314
617
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In Response, the Examiner respectfully disagrees. Asbag discloses removing failed die in low failure regions of the wafer from the reduced data set (Fig. 2, 203, defect filtration for the non-clustered defect), locating clusters of failed die in the reduced data set after removing the failed die in the low failure density regions (Fig. 2, 208). Meanwhile, Niewczas discloses classifying and locating the identified defects using DBSCAN (Paragraph [0028]) where the clusters are classified according to having similar features, as shown in Figs. 2A and 2B (Paragraph [0024]). Note that DBSCAN is a known method in semiconductor industry. Thus, the combination of Asbag and Niewczas would allow the locating and classification between the data set of failed die in low failure density region (or non-clustered defect) and data set of failed die in higher failure density region using DBSCAN (since different density regions have different features).
With respect to claims 2, 11 and 18, Applicant argues the following:
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810
724
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In Response, the Examiner respectfully disagrees, and state that Asbag discloses a failed die is in a low failure density region when the die has less than three failed die neighbors within a radius of three die from the failed die (Paragraphs [0071]-[0072], filtering the non-clustered defects; Fig. 3, such as 307, 308)
15. With respect to claim 3, the Applicant argues the following:
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396
712
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In Response, the Examiner respectfully disagrees. Asbag discloses locating clusters of trapped good die (Fig. 3, 303), and Moreno discloses locating clusters of trapped good die and indicating that the trapped die are of potentially marginal quality (Section 3.1; Fig. 5; Introduction).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HYUN D PARK whose telephone number is (571)270-7922. The examiner can normally be reached 11-4.
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/HYUN D PARK/Primary Examiner, Art Unit 2857