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 Amendment
The Amendment filed on 6/11/2026 has been entered. Claims 1-9, 13, 15-19 and 42-46 remain pending in the application. Applicant’s amendments to the claims have overcome each and every 112(b) rejection previously set forth in the non-final Office Action mailed 3/11/2026.
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 8, 9, 45 and 46 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.
Claim 45 recites “further comprising manufacturing the sample cartridge,” however, claim 1 is directed at “A method of detecting a defect in a sample cartridge.” Claim 45 is therefore unclear as claim 1 is seeming to be directed at detecting a defect in a sample cartridge and then claim 45 tries to add in a step of manufacturing the sample cartridge which seems to be a different method than detecting a defect. The examiner suggests to write 45 as its own independent claim which includes the manufacturing the sample cartridge and detecting a defect to improve clarity of the claim. Claims 8, 9 and 46 are rejected by virtue of their dependence on a rejected base claim.
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.
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.
Claim(s) 1-7, 13, 15-19, 42, 43 and 44 is/are rejected under 35 U.S.C. 103 as being unpatentable over United States Application Publication No. 2022/0114720, hereinafter Weinstein in view of CN 111721768, hereinafter Zhu and United States Application Publication No. 2016/0284075, hereinafter Phan.
Regarding claim 1, Weinstein teaches a method of detecting a defect in a sample cartridge (paragraphs [0021], [0032] and [0033]), the method comprising: obtaining, during a manufacturing process of the sample cartridge, a first data set from an optical sensor (paragraph [0123]); comparing the first data set (paragraphs [0110], [0138]-[0140]); and identifying a first defect of the sample cartridge based on a variance of the first data set from the first baseline (paragraphs [0110], [0138]-[0140]),
Weinstein fails to teach obtaining a second data set from an audio sensor; comparing the second data set and a second defect of the sample cartridge based on a variance of the second data set.
Zhu teaches a fusion welding system which utilizes an imagining camera and an ultrasonic detection module which is able to extract the internal position of the welding seam, shape size and texture information providing internal information about the seam (Zhu, page 3, paragraph 7).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have added an ultrasound microphone and added the data from the microphone to the device because it would be able to extract the internal position of the welding seam, shape size and texture information providing internal information about the seam (Zhu, page 3, paragraph 7).
Weinstein and Zhu fail to teach comparing the first data set to a first baseline and the second data set to a second baseline, each baseline being associated with acceptable sample cartridges.
Phan teaches a device for the structural analysis of a device in which a server utilizes machine learning algorithms to automatically identify structural and automatically recognize structures without defects, and use those structures as baselines to identify structures with defects because the system can be developed so that the identification of baselines and the structural defects can be made without human intervention (Phan, paragraph [0092]).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have utilized the method Phan which utilizes baselines and therefore would utilize a first and second baseline to compare the first and second data sets to, respectively, because it would allow for the system to identify baselines and the structural defects without human intervention (Phan, paragraph [0092]).
Regarding claim 2, Weinstein teaches wherein the defect is determined in an automated process in real-time during manufacturing of the sample cartridge (paragraphs [0138]-[0140]).
Regarding claim 3, Weinstein teaches wherein obtaining the first data set comprises obtaining one or more images (paragraph [0138]) from one or more RGB cameras and/or IR cameras (paragraph [0124]), wherein the first data set comprises a thermal image (paragraph [0124]).
Regarding claim 4, Weinstein teaches wherein identifying based on a variance utilizes an algorithm derived by machine/deep learning based on a plurality of data sets associated with acceptable sample cartridges and a plurality of data sets associated with cartridge defects (paragraph [0140]).
Regarding claim 5, Weinstein teaches extracting a feature from the one or more images that corresponds to a feature of the sample cartridge (paragraph [0138]).
Regarding claim 6, Weinstein teaches wherein the first data set comprises a plurality of consecutive images obtained during the manufacturing process (paragraph [0138]).
Regarding claim 7, Weinstein teaches wherein the first data set comprises a plurality of image from differing viewpoints during the manufacturing process (paragraph [0127]).
Regarding claim 13, modified Weinstein teaches wherein the second data set further comprises an ultrasound audio spectrum that is compared to a baseline of ultrasound audio of a successful weld, wherein the characteristic comprises peaks and/or variations in the ultrasound audio spectrum (see supra).
Regarding claim 15, Weinstein teaches wherein the variance comprises a deviation of an extracted feature from a corresponding feature of a baseline high-resolution image (paragraphs [0138]-[0140]).
Regarding claim 16, Weinstein teaches wherein the first and second data sets are input into a model that classifies the sample cartridge as pass or fail based on a defect prediction (paragraph [0140]).
Regarding claim 17, Weinstein teaches wherein the model is trained based on supervised and unsupervised machine learning (paragraph [0140]).
Regarding claim 18, Weinstein teaches wherein the model accesses the data sets through a cloud-based data sharing, training and prediction platform (paragraph [0125]).
Regarding claim 19, Weinstein teaches wherein at least one of the first and second data sets are obtained from an automation module of the automated manufacturing line of the cartridge (paragraphs [0138]-[0140]).
Regarding claim 42, modified Weinstein teaches wherein the optical sensor includes at least one of an IR camera (paragraph [0124]), a RGB camera (paragraph [0124]), or a high-resolution camera (paragraph [0124]); and wherein the audio sensor is an ultrasound microphone (see supra).
Regarding claim 43, modified Weinstein teaches wherein the first data set includes a plurality of consecutive images during the manufacturing process (paragraph [0138]), a plurality of images from different viewpoints during the manufacturing process (optional), or both; and wherein the second data set includes an ultrasound audio spectrum during the manufacturing process (see supra).
Regarding claim 44, modified Weinstein teaches wherein the first defect includes the variance from the first baseline data set for a chimney, a film seal, a weld (paragraphs [0138]-[0140]), or combinations thereof; and wherein the second defect includes the variance from the second baseline data set for the weld (see supra).
Claim(s) 1, 8, 9, 45 and 46 is/are rejected under 35 U.S.C. 103 as being unpatentable over United States Patent No. 8,474,226, hereinafter Izquierdo in view of Weinstein, Zhu and Phan.
Regarding claims 1 and 45, Izquierdo teaches a method of manufacturing a sample cartridge (abstract).
Izquierdo fails to teach obtaining, during a manufacturing process of the sample cartridge, a first data set from an optical sensor and a second data set from an audio sensor; comparing, the first data set to a first baseline and the second data set to a second baseline, each baseline being associated with acceptable sample cartridges; and identifying a first defect of the sample cartridge based on a variance of the first data set from the first baseline, a second defect of the sample cartridge based on a variance of the second data set from the second baseline, or both.
Weinstein teaches a method of detecting a defect in a sample cartridge (paragraphs [0021], [0032] and [0033]), the method comprising: obtaining, during a manufacturing process of the sample cartridge, a first data set from an optical sensor (paragraph [0123]); comparing the first data set to a first baseline (paragraphs [0110], [0138]-[0140]), each baseline being associated with acceptable sample cartridges (paragraphs [0110], [0138]-[0140]); and identifying a first defect of the sample cartridge based on a variance of the first data set from the first baseline (paragraphs [0110], [0138]-[0140]),
Weinstein fails to teach obtaining a second data set from an audio sensor; comparing the second data set to a second baseline and a second defect of the sample cartridge based on a variance of the second data set from the second baseline.
Zhu teaches a fusion welding system which utilizes an imagining camera and an ultrasonic detection module which is able to extract the internal position of the welding seam, shape size and texture information providing internal information about the seam (Zhu, page 3, paragraph 7).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have added an ultrasound microphone and added the data from the microphone to the device because it would be able to extract the internal position of the welding seam, shape size and texture information providing internal information about the seam (Zhu, page 3, paragraph 7).
Izquierdo, Weinstein and Zhu fail to teach comparing the first data set to a first baseline and the second data set to a second baseline, each baseline being associated with acceptable sample cartridges.
Phan teaches a device for the structural analysis of a device in which a server utilizes machine learning algorithms to automatically identify structural and automatically recognize structures without defects, and use those structures as baselines to identify structures with defects because the system can be developed so that the identification of baselines and the structural defects can be made without human intervention (Phan, paragraph [0092]).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have utilized the method Phan which utilizes baselines and therefore would utilize a first and second baseline to compare the first and second data sets to, respectively, because it would allow for the system to identify baselines and the structural defects without human intervention (Phan, paragraph [0092]).
Regarding claim 8, Izquierdo teaches wherein the manufacturing process comprises ultrasonic welding of a lid apparatus on a cartridge body of the sample cartridge (abstract).
Regarding claim 9, Izquierdo teaches wherein the manufacturing process comprises heat sealing of a thin film atop a lid apparatus on a cartridge body of the sample cartridge (abstract).
Regarding claim 46, Izquierdo teaches wherein the manufacturing includes assembling (abstract).
Response to Arguments
Applicant’s arguments, see pages 3-4, filed 6/11/2026, with respect to the rejection(s) of claim(s) 1-7 and 15-19 under 1-2(a)(1) have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Weinstein, Zhu and Phan.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 MATTHEW D KRCHA whose telephone number is (571)270-0386. The examiner can normally be reached M-Th 7am-5pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Maris Kessel can be reached at (571)270-7698. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MATTHEW D KRCHA/ Primary Examiner, Art Unit 1796
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