Detailed Action
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This action is responsive to the communications filed 1/09/2026. As per the claims filed 6/17/2024:
Claims 1-16 are pending.
Claim(s) 1, 10, 12, 14 is/are independent claim(s).
Note Regarding Prior Art
Examiner cites particular columns, paragraphs, figures and line numbers in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner.
Note Regarding AIA Status
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 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.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “a shape measuring unit” in claim 1.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 1-16 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.
The term “determine whether the shape of the weld is good or bad based…” in claim 1 is a relative term which renders the claim indefinite. The term “good or bad” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
Claims 9, 14 are rejected for the same reasons as claim 1 above.
Independent claims 10, 12 include all limitations of claim 1 therefore they are rejected under the same rationale as claim 1 above.
Claims 2-8, 11, 15-16 are rejected based on their dependency on a rejected base claim.
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) 1-3, 7-8, 10-11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ryan S. Kitchen et al (US PG Pub No.US2021/0318673; Published: 10/14/2021; Filed: 4/5/2021)(hereinafter: Kitchen) in view of Manfred Hoffmann et al (US PG Pub No 2008/024765; Published: 08/28/2008)(hereinafter: Hoffmann).
Claim 1:
As per independent claim 1, Kitchen discloses an appearance inspection apparatus for inspecting an appearance of a weld of a workpiece, [[0036] Data collected by the camera devices is communicated to an in-situ inspection server 112 using a communication network 110.] the appearance inspection apparatus comprising at least:
a shape measurement unit that is attached to a robot and configured to measure a three-dimensional shape of the weld along a welding line [[0038] this information is fed to one or more mounted robotic cameras for accurate image capture. The system converts temporal image trends to stationary signals by taking the temporal derivative of the images. The system trains a convolutional neural network on sequential, lagged image batches with 3D convolutions (e.g., pixel position, intensity, and color/spectral band). [0060] Some implementations use one or more optical cameras with a mechanical shutter and a laser to capture images of surface of a weld pool.]; and
a shape data processor and a data processor configured to process shape data acquired by the shape measurement unit [[0037] The in-situ inspection server 112 uses some standard computer vision processing algorithms 114, as well as some machine/deep learning data models 115.] the data processor including at least:
a learning data set generator configured to generate a plurality of learning data sets by performing data augmentation on multiple pieces of sample shape data acquired in advance by the shape measurement unit [[0108] The method includes generating (1004) weld features 1006 by extracting features from the weld images 1002 and integrating one or more weld parameters. The method also includes forming (1008) feature vectors 1010 based on the weld features. The method further includes training (1012) a regression model 1014 (e.g., machine learning models described above), using the feature vectors 1010, to predict or identify weld defects.]
a determination model generator configured to generate a determination model for determining whether the shape of the weld is good or bad using the plurality of learning data sets [[0110] a method is provided for detecting, identifying, and/or visualizing weld defects for in-progress welding process (sometimes called in-situ inspection of weld quality). …The method includes receiving weld images 1022 from one or more cameras. The method also includes generating (1004) a plurality of weld features based on the weld images 1022 and/or weld parameters, as described above in reference to FIG. 10A. The method includes forming (1008) feature vectors 1026 v=[v.sub.1, v.sub.2, . . . , v.sub.n] (e.g., as described above in reference to FIG. 10A) whose components include a plurality of features. [0111] The method further includes predicting or detecting (1028) weld defects 1030 using the trained classifiers (e.g., the classifiers 1014), based on the feature vectors 1026.] and
a first determination unit configured to determine whether the shape of the weld is good or bad based on the shape data corrected by the shape data processor and one or more determination models generated by the determination model generator. [[0110]The method includes receiving weld images 1022 from one or more cameras. The method also includes generating (1004) a plurality of weld features based on the weld images 1022 and/or weld parameters, as described above in reference to FIG. 10A. The method includes forming (1008) feature vectors 1026 v=[v.sub.1, v.sub.2, . . . , v.sub.n] (e.g., as described above in reference to FIG. 10A) whose components include a plurality of features. [0111] The method further includes predicting or detecting (1028) weld defects 1030 using the trained classifiers (e.g., the classifiers 1014), based on the feature vectors 1026. [0038]].
Kitchen discloses a measuring unit but failed to specifically disclose configured to perform at least correction of a resolution of the shape data acquired by the shape measurement unit.
Hoffmann, in the same field of measuring devices discloses this limitation in that [[0025]In order to increase the resolution, the final measured values z.sub.B of the profile (denoted by P in FIGS. 1 and 2) can be obtained by combining the values z.sub.A with correction values Kv, determined in accordance with the speed of movement v of the solid body 1 which are, in particular, vectorial factors and/or summands proportional to the speed of movement v. Here, a correlative combination of the speed of movement v with the frequency f of the detection of the reflected light RL is performed in order to determine the correction values Kv determined in accordance with the speed of movement v.].
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the optical measuring unit of Kitchen to perform at least correction of a resolution of the shape data acquired by the shape measurement unit as disclosed by Hoffmann. The motivation for doing so would have been to more accurately determine the state of the shape being measured resulting in a decrease of errors.
Claim 2:
As per claim 2, which depends on claim 1, it is rejected under the same rationale as claim 1 above. Additionally, Kitchen and Hoffmann disclose wherein the shape data processor corrects the resolution of the shape data acquired by the shape measurement unit based on a measurement resolution, measurement frequency, and scanning speed of the shape measurement unit. Hoffmann, [[0025]In order to increase the resolution, the final measured values z.sub.B of the profile (denoted by P in FIGS. 1 and 2) can be obtained by combining the values z.sub.A with correction values Kv, determined in accordance with the speed of movement v of the solid body 1 which are, in particular, vectorial factors and/or summands proportional to the speed of movement v. Here, a correlative combination of the speed of movement v with the frequency f of the detection of the reflected light RL is performed in order to determine the correction values Kv determined in accordance with the speed of movement v.].
Claim 3:
As per claim 3, which depends on claim 2, it is rejected under the same rationale as claim 2 above. Additionally, Kitchen and Hoffmann disclose wherein the sample shape data is acquired at the measurement resolution, the measurement frequency, and the scanning speed that are determined in advance. Kitchen, [[0072] In some implementations, a 2-D or a 3-D digital data model of a weld digital twin is annotated for quality examination, in advance of ex-situ visual or instrument inspection of the weld. [0073] For machine learning, some implementations use sequencing model to extract unsupervised arc and electrode anomalies. ..Some implementations create a statistical fit based on location of ex-situ inspection of welds. Some implementations train a supervised neural network to classify defect types annotated from the video input, automatically extract engineering features.]] and the shape data processor corrects the resolution of the shape data acquired by the shape measurement unit to the same value as a resolution of the sample shape data. Kitchen [[[0072] In some implementations, a 2-D or a 3-D digital data model of a weld digital twin is annotated for quality examination, in advance of ex-situ visual or instrument inspection of the weld. [0073] Some implementations create a statistical fit based on location of ex-situ inspection of welds. Some implementations train a supervised neural network to classify defect types annotated from the video input, automatically extract engineering features.]] Resolution must be the same between the sample shape data (the ex-situ data) and the gathered in-situ data.
Claim 7:
As per claim 7, which depends on claim 1, Kitchen and Hoffmann disclose wherein the data processor further includes a first storage configured to store at least the sample shape data, and the learning data set generator configured to read the sample shape data stored in the first storage to generate the plurality of learning data sets. Kitchen, [[0052] he memory 214 stores a subset of the modules and data structures identified above. Furthermore, the memory 214 may store additional modules or data structures not described above. See memory, fig 2]
Claim 8:
As per claim 8, which depends on claim 1, Kitchen and Hoffmann disclose wherein the data processor further includes a notification unit configured to notify a result of the determination by the first determination unit. Kitchen, [[0038] the machine/deep learning data models 115 output the probability of an event (either yes/no or type of defect).]
Claim 10:
As per independent claim 10, Kitchen and Hoffmann disclose a welding system, comprising: the appearance inspection apparatus of claim 1 (see claim 1 above) and a welding apparatus configured to weld the workpiece, wherein the welding apparatus includes at least: a welding head configured to apply heat to the workpiece; and an output controller configured to control a welding output of the welding head [[0057] welder having a robotic arm. See figure 3C]. Welding head and controller are implicit parts of the welder having a robotic arm.
Claim 11:
As per claim 11, which depends on claim 10, Kitchen and Hoffman disclose wherein the welding apparatus includes at least: the robot configured to hold the welding head and moves the welding head to a desired position. Kitchen, [[0057] FIG. 3B is an example weld process 302, according to some implementations. The example shows a robotic arm welder 304,] and a robot controller configured to control a motion of the robot. Kitchen, [see welding control module in fig 2] and when the first determination unit determines that the shape of the weld is bad, the output controller stops the welding output of the welding head, and the robot controller stops the motion of the robot or operates the robot so that the welding head moves to a predetermined initial position. Kitchen, [[0084] Some implementations provide early warning and augmentation to inspection, based on detecting in-process or in-situ (as opposed to or in addition to post weld inspection of), weld features, that lead to defects. In some implementations, the weld may be stopped at the time of defect].
Allowable Subject Matter
Claims 12-16 are allowed over the prior art but remain rejected under 35 USC 112.
Claims 4-6, 9 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.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HOWARD CORTES whose telephone number is (571)270-1383. The examiner can normally be reached on M-F, 8:00 am - 5:00 pm EST.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Scott T Baderman can be reached on (571)272-3644. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/HOWARD CORTES/ Primary Examiner, Art Unit 2118
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