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 .
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 2-8 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.
Regarding claims 2-7, “industrial production elements of interest” render the claim indefinite because it is unclear if antecedence is claimed to the industrial production elements of interest recited in claim 1 or a separate set of industrial production elements of interest.
Claim 8 is indefinite by virtue of dependency on claim 6.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-3, 5-6, and 8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1
Step 1: Is the claim to a process, machine, manufacture, or composition of matter?
Yes. Claim 1 is drawn to a process.
Step 2A, Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes. Claim 1 recites the following abstract ideas:
“associating a classification label with the industrial production element of interest, in which the classification label is determined by one or more workers in a course of the one or more workers performing their normal duties in the work setting” - This is an observation, evaluation, judgement, or opinion, i.e. a concept performed in the human mind. See MPEP 2106.04(a)(2), III.
Step 2A, Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application?
No. Claim 1 recites the following additional elements:
“for use with industrial production elements of interest” – This amounts to merely indicating a field of use or technological environment in which to apply the exception, see MPEP 2106.05(h).
“capturing, using one or more sensors configured in a work setting, sensor data comprising one or more values of the industrial production element of interest” – This amounts to insignificant extra-solution activity in the form of mere data gathering, see MPEP 2106.05(g). The limitation merely recites the gathering of data for classification without meaningfully limiting the claim beyond generic data gathering from sensors.
“forming a labelled dataset using the captured sensor data and associated labels from the one or more workers’ classifications for the first plurality of industrial production elements of interest” – This amounts to insignificant extra-solution activity in the form of mere data gathering, see MPEP 2106.05(g). The limitation merely recites the gathering of data for classification without meaningfully limiting the claim beyond generic data aggregation.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
No. Claim 1 recites the following additional elements:
“for use with industrial production elements of interest” – This amounts to merely indicating a field of use or technological environment in which to apply the exception, see MPEP 2106.05(h).
“capturing, using one or more sensors configured in a work setting, sensor data comprising one or more values of the industrial production element of interest” – This amounts to insignificant extra-solution activity in the form of mere data gathering, see MPEP 2106.05(g). The limitation merely recites the gathering of data for classification without meaningfully limiting the claim beyond generic data gathering from sensors.
“forming a labelled dataset using the captured sensor data and associated labels from the one or more workers’ classifications for the first plurality of industrial production elements of interest” – This amounts to insignificant extra-solution activity in the form of mere data gathering, see MPEP 2106.05(g). The limitation merely recites the gathering of data for classification without meaningfully limiting the claim beyond generic data aggregation.
Claim 2
Step 1: Is the claim to a process, machine, manufacture, or composition of matter?
Yes. Claim 2 is drawn to a process
Step 2A, Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes. Claim 2 recites the following abstract ideas:
The abstract ideas of claim 1.
Step 2A, Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application?
No. Claim 2 recites the following additional elements:
“using at least some of the labelled dataset to train a machine learning model to perform classification on industrial production elements of interest” - merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea. See MPEP 2106.05(f).
Step 2B: Does the claim recite additional elements that amount ot significantly more than the judicial exception?
No. Claim 2 recites the following additional elements:
“using at least some of the labelled dataset to train a machine learning model to perform classification on industrial production elements of interest” - merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea. See MPEP 2106.05(f).
Claim 3
Step 1: Is the claim to a process, machine, manufacture, or composition of matter?
Yes. Claim 3 is drawn to a process
Step 2A, Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes. Claim 3 recites the following abstract ideas:
The abstract ideas of claim 1.
Step 2A, Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application?
No. Claim 3 recites the following additional elements:
“deploying the trained machine learning model in a same or similar work setting to automate classification of industrial production elements of interest” - merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea. See MPEP 2106.05(f).
Step 2B: Does the claim recite additional elements that amount ot significantly more than the judicial exception?
No. Claim 3 recites the following additional elements:
“deploying the trained machine learning model in a same or similar work setting to automate classification of industrial production elements of interest” - merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea. See MPEP 2106.05(f).
Claim 5
Claim 5 recites a repetition of claim 1 and therefore the same issues in claim 1 are present in claim 5, rendering claim 5 ineligible.
Claim 6
The analysis with respect to claim 2, mutatis mutandis, applies to claim 6, rendering claim 6 ineligible.
Claim 8
Step 1: Is the claim to a process, machine, manufacture, or composition of matter?
Yes. Claim 8 is drawn to a process.
Step 2A, Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes. Claim 8 recites the following abstract ideas:
The abstract ideas of claim 1.
Step 2A, Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application?
No. Claim 8 recites the following additional elements:
“combining labelled data from at least two work settings” – This amounts to insignificant extra-solution activity in the form of mere data gathering, see MPEP 2106.05(g). The limitation merely recites the gathering of data for classification without meaningfully limiting the claim beyond generic data aggregation.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
No. Claim 8 recites the following additional elements:
“combining labelled data from at least two work settings” – This amounts to insignificant extra-solution activity in the form of mere data gathering, see MPEP 2106.05(g). The limitation merely recites the gathering of data for classification without meaningfully limiting the claim beyond generic data aggregation.
Claims 4 and 7
Claims 4 and 7 are deemed patent eligible under 35 USC 101 because they recite specific, concrete training steps regarding how training is carried out with respect to the accuracy. While broad, the claims practically apply the abstract ideas of claim 1 to the training of a machine learning model which benefits from expert classification, see ¶48 of the as-filed Specification.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-6 and 8 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Consul (US20090319456A1).
Regarding claim 1, Consul teaches a method for use with industrial production elements of interest comprising:
for each industrial production element of a plurality of industrial production elements of interest: capturing, using one or more sensors configured in a work setting, sensor data comprising one or more values of the element of interest (Figure 2: 116, new data is an “element of interest” and the messages of the new data, ¶33, are “captured” by the computer and are recognized by the system and can be considered “sensed” by sensors); and
associating a classification label with the industrial production element of interest, in which the classification label is determined by one or more workers in a course of the one or more workers performing their normal duties in the work setting (¶33, workers tag messages as they come in); and
forming a labelled dataset using the captured sensor data and associated labels from the one or more workers' classifications for the plurality of industrial production elements of interest (Figure 2: 106).
Regarding claim 2, Consul teaches all of the limitations of claim 1, further comprising:
using at least some of the labelled dataset to train a machine learning model to perform classification on industrial production elements of interest (¶33, ¶43).
Regarding claim 3, Consul teaches all of the limitations of claim 2, further comprising:
deploying the trained machine learning model in a same or similar work setting to automate classification of industrial production elements of interest (¶33, ¶43).
Regarding claim 4, Consul teaches all of the limitations of claim 2, further comprising:
responsive to the machine learning model not achieving an accuracy above a threshold value given an existing labelled dataset: repeating the steps of Claim 1 to obtain additional labelled data to validate the machine learning model (¶70, if accuracy is insufficient, further training is conducted, which includes additional data per Figure 2); and performing additional training on the machine learning model using at least some of the additional labelled data (¶70 and Figure 2); and responsive to the machine learning model achieving accuracy above the threshold value, deploying the trained machine learning model in a same or similar work setting to automate classification of industrial production elements of interest (¶33, ¶43).
Regarding claim 5, Consul teaches all of the limitations of claim 1, further comprising:
repeating the steps of Claim 1 at a plurality of work settings, in which workers operate on industrial production elements of interest that are of a same type and perform a same classification operation, to obtain a plurality of labelled datasets using the captured sensor data and associated labels from the one or more worker's classifications (¶25 and ¶70, retraining, i.e. repeating Claim 1, can be performed, and organization-wide user tags can be utilized instead of a single worker’s tags).
Regarding claim 6, Consul teaches all of the limitations of claim 5, further comprising:
for each work setting of a set of work settings selected from the plurality of work settings, using at least some of the labelled dataset associated with the work setting to train a machine learning model to perform classification on industrial production elements of interest (¶25 and ¶70, retraining, i.e. repeating Claim 1, can be performed, and organization-wide user tags can be utilized instead of a single worker’s tags).
Regarding claim 8, Consul teaches all of the limitations of claim 6, further comprising:
combining labelled data from at least two work settings (¶25 and ¶70, retraining, i.e. repeating Claim 1, can be performed, and organization-wide user tags can be utilized instead of a single worker’s tags).
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.
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Consul (US20090319456A1) in view of Fan (US20050131873A1).
Regarding claim 7, Consul teaches all of the limitations of claim 6, but does not teach the method further comprising:
obtaining a plurality of machine learning models formed using different labelled datasets; forming a set of combined models comprising a combination of two or more of the machine learning models; using evaluation data to obtain accuracy measures for each combined model; selecting a combined model with an acceptable accuracy measure; and deploying the combined model at least one of the work settings.
Fan teaches obtaining a plurality of machine learning models formed using different labelled datasets; forming a set of combined models comprising a combination of two or more of the machine learning models; using evaluation data to obtain accuracy measures for each combined model; selecting a combined model with an acceptable accuracy measure; and deploying the combined model at least one of the work settings (¶19-20 – sub-ensembles are created and confidence scores for each are generated and the sub-ensemble with the highest confidence score is deployed).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Consul to include obtaining a plurality of machine learning models formed using different labelled datasets, forming a set of combined models comprising a combination of two or more of the machine learning models, using evaluation data to obtain accuracy measures for each combined model; selecting a combined model with an acceptable accuracy measure, and deploying the combined model at least one of the work setting in order to provide an accurate classification model.
Response to Arguments
Applicant’s arguments filed 07/28/2026 have been fully considered.
Applicant argues that it is impossible to mentally perform scrutiny by a camera of a machine screw. This is not claimed and therefore the argument is moot.
Applicant argues that “industrial production elements” are physical and thereby not abstract. There is nothing in the claim to restrict “industrial production elements” to a physical, non-abstract regime.
Applicant has argued that the claimed invention improves the functioning of a computer and improves other technology or a technical field. In particular, Applicant argues that data labelling improves performance. As noted herein, data labelling is an abstract idea and the judicial exception cannot provide the improvement per MPEP 2106.05(a).
Applicant has argued that a result of captured images is a set of image data with the screws in various positions but with correct labels which improves data robustness. There are no images or screws claimed, therefore the argument is moot.
Applicant argues that claim 1 is directed towards “…scrutiny of physical “elements of interest” by physical “sensors configured in a work setting””. There is nothing in the claims which renders the “elements of interest” or “sensors configured in a work setting” as non-software, non-electronic, or non-digital. Therefore, the argument formed on this basis is moot.
Applicant has argued that Claim 1 is directed to “things you can drop on your foot”. This is not claimed and therefore the argument is moot.
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 SCHYLER S SANKS whose telephone number is (571)272-6125. The examiner can normally be reached 06:30 - 15:30 Central Time, M-F.
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, Michael Huntley can be reached at (303) 297-4307. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SCHYLER S SANKS/ Primary Examiner, Art Unit 2129
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