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 .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 09/02/2025 has been entered.
Status of Claims
This action is a responsive to the application filed on 09/02/2025.
Claims 2-5, 8-12, 14, 16-19, and 21-24 are pending.
Claims 2, 14, 17, and 24 have been amended.
Claims 1, 6-7, 13, 15, 20 have been canceled.
Response to Arguments
Applicant’s arguments, with respect to the Double Patenting rejection(s) of claim(s) 2-7 and 7-13, have been considered but they are not persuasive. Applicant states that “Applicant submits herewith this correspondence terminal disclaimer(s), in compliance with 37 C.F.R. § 1.321 (c), directed to the '191 Patent, to obviate these double patenting rejections”; however, no Terminal Disclaimer has been recognized as being filed and thus the Double Patenting rejections are maintained.
Applicant’s arguments, with respect to the rejection(s) of claim(s) 2-5, 8-12, 14, 16-19, and 21-24 under 35 U.S.C. 101, have been considered but they are not persuasive. The applicant argues that the rejections are “rendered moot in view of amendments” submitted, and thus overcome previous 101 rejections. The examiner respectfully disagrees.
The amended limitation of pre-processing data with certain methods is deemed claimed at a high level and amounts to insignificant extra-solution activity related to mere data gathering and data manipulation (see MPEP 2106.05(g)).
See 35 U.S.C 101 section for full, updated analysis of claim limitations necessitated by applicant amendments.
Applicant’s arguments, with respect to the rejection(s) of claim(s) 2 under 35 U.S.C. 103, have been considered but they are not persuasive. Applicant argues that no reference teaches the amended limitations of claims 2 that now state “pre-process the first welding data and the second welding data, wherein the pre-processing comprises applying one or more of data staging, cleaning, scaling, linearization, aggregation, filtering, smoothing, compression, integration, feature identification, cataloging and transformation”. The examiner respectfully disagrees.
The combination of Asenjo, Fidali, and Hartman have been found to teach the amended claim language. Asenjo, paragraphs 0073-0074 teach “cloud gateway component 608 or a separate transformation component (e.g., transformation component 314) may perform preprocessing on the gathered data prior to migrating the data to the cloud platform (e.g., time stamping, filtering, formatting, summarizing, compressing, etc.)”.
See 35 U.S.C 103 section for full mapping of claim limitations necessitated by applicant amendments.
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: “remotely situated analytics computing platform” in claims 2, 3, 14, 16-18, 21-24.
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.
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 2-5, 7-8, and 13 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1, 12, 13, and 15 of U.S. Patent No. 11,347,191 (hereinafter ‘191) in view of Fidali et al., “Segmentation of Welding Arc Images for Purposes of Welding Diagnostics” (hereinafter Fidali).
Regarding claim 2, reference patent ‘191 teaches:
A welding analysis system comprising (‘191: claim 1 at col. 36, line 6.):
first processing circuitry to process a first welding input from a first data source to define first welding data, wherein the first data source is associated with a weld, weldment, or weld process (‘191: claim 1 at col. 36, lines 7-15.);
second processing circuitry to process a second welding input from a second data source to define second welding data, wherein the second data source is associated with the weld, weldment, or weld process (‘191: claim 1 at col. 36, lines 16-20.); and
a remotely situated analytics computing platform configured to (‘191: claim 1 at col. 36, lines 30-31.):
receive the first welding data and the second welding data via a communication network communicatively coupled with the first processing circuitry and the second first processing circuitry (‘191: claim 1 at col. 36, lines 28-35 and 40-57.); and ….
.
While the reference patent ‘191 teaches the above limitations of claim 2, it does not explicitly teach: “pre-process the first welding data and the second welding data, wherein the pre-processing comprises applying one or more of data staging, cleaning, scaling, linearization, aggregation, filtering, smoothing, compression, integration, feature identification, cataloging and transformation; process the first welding data and the second welding data to identify anomalies in at least one of the weld, the weldment, or the weld process by using an unsupervised machine learning technique to classify the first welding data and the second welding data.” Fidali teaches: use of an unsupervised learning technique such as k-means clustering algorithm to analyze welding data images at different welding states to determine if/when there are anomalies in the weld or welding process, e.g., instability or gas decay (Fidali Sections 3, 3.3, 4, and 5).
Thus, it would have been obvious to Person Having Ordinary Skill in the Art (PHOSITA) before the effective filing date (EFD) to modify the system in the cited reference to include the k-means clustering in Fidali. Doing so would enable “diagnostics of a welding process. The estimation of the process state is being performed by means of the analysis of infrared images and images recorded within visible range of electromagnetic radiation. To carry out the image analysis it is necessary to cut out the area called region of interests (ROI). In case of welding which is the dynamical process this operation appeared complicated. The most important point of the operation is image segmentation. The author proposed and tested an algorithm of the definition of the ROI as well as verified numerous image segmentation methods.” (Fidali Abstract).
While the reference patent ‘191 teaches the above limitations of claim 2, it does not explicitly teach: “pre-process the first welding data and the second welding data, wherein the pre-processing comprises applying one or more of data staging, cleaning, scaling, linearization, aggregation, filtering, smoothing, compression, integration, feature identification, cataloging and transformation…train a model based on a supervised machine learning technique using the classified data; and detect the presence of the identified anomalies in subsequent welding data based on the model.” Hartman teaches: using supervised learning as part of neural network (NN) training (model) to classify weld data as acceptable or unacceptable welds and “preprocessing” the data including smoothing (Hartman col. 13, lines 53-67 through to col. 14, line 65. Similarly, see also col. 5, lines 5-67; col. 6 lines 63-67 through to col. 7, line 5; col. 8, lines 51-67 through to col. 9, line 67; col. 11, lines 58-67 through to col. 12, line 17; and col. 18, lines 39-63: further describing the various classification definitions and the use of the NN for determining and classifying weld quality.
Thus, it would have been obvious to Person Having Ordinary Skill in the Art (PHOSITA) before the effective filing date (EFD) to modify the system with the k-means clustering in the combined cited references to include the weld quality determination via supervised learning in Hartman. Doing so would enable “[a] method for determining the quality of an examined weld joint comprising the steps of providing acoustical data from the examined weld joint, and performing a neural network operation on the acoustical data determine the quality of the examined weld joint produced by a friction weld process. The neural network may be trained by the steps of providing acoustical data and observable data from at least one test weld joint, and training the neural network based on the acoustical data and observable data to form a trained neural network so that the trained neural network is capable of determining the quality of a examined weld joint based on acoustical data from the examined weld joint. In addition, an apparatus having a housing, acoustical sensors mounted therein, and means for mounting the housing on a friction weld device so that the acoustical sensors do not contact the weld joint. The apparatus may sample the acoustical data necessary for the neural network to determine the quality of a weld joint.” (Hartman Abstract).
Regarding claim 3, the rejection of claim 2 is incorporated. Reference patent ‘191 teaches:
The welding analysis system as defined in claim 2, wherein the remotely situated analytics computing platform is configured to identify the anomalies in at least one of: weld quality; arc time patterns; idle time patterns; equipment duty cycle patterns; input power consumption and fluctuation patterns; welding consumable consumption patterns; or usage patterns on functions available from welding equipment associated with the first welding data or the second welding data (‘191: claim 1 at col. 36, lines 45-67.).
Regarding claim 4, the rejection of claim 2 is incorporated. Reference patent ‘191 teaches:
The welding analysis system as defined in claim 2, wherein the unsupervised learning technique comprises a data clustering technique to identify the anomalies based on the first welding data and the second welding data (‘191: claims 1 and 12. Wherein claim 1 describes the classification of the weldment as either acceptable or unacceptable and claim 12 describes the unsupervised learning comprising data clustering.).
Regarding claim 5, the rejection of claim 4 is incorporated. Reference patent ‘191 teaches:
The welding analysis system as defined in claim 4, wherein the data clustering comprises at least one of k-means, hierarchical, conceptual, probability-based, or Bayesian clustering (‘191: claims 1 and 12. Wherein claim 1 describes the classification of the weldment as either acceptable or unacceptable and claim 12 describes the types of data clustering.).
Regarding claims 8, the rejection of claim 2 is incorporated. Fidali further teaches:
The welding analysis system as defined in claim 2, wherein the identified anomalies comprise at least one of a welding gas anomaly, a welding wire anomaly, a flux anomaly, a contact tip anomaly, a torch nozzle anomaly, or a wire liner anomaly (Fidali Sections 4 and 5: describing anomalies with the welding gas, e.g., decay or instability of the shielding gas.).
Thus, it would have been obvious to Person Having Ordinary Skill in the Art (PHOSITA) before the effective filing date (EFD) to modify the system in the cited reference to include the welding gas anomaly in Fidali. A motivation to combine the cited references with Fidali was previously given.
Claims 9, 10, and 12 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of U.S. Patent No. 11,347,191 (hereinafter ‘191) and Fidali et al., “Segmentation of Welding Arc Images for Purposes of Welding Diagnostics” (hereinafter Fidali) in view of Hartman et al. (U.S. Pat. No. 6,857,553, hereinafter Hartman).
Regarding claim 9, the rejection of claim 2 is incorporated. The cited references in combination do not explicitly teach: “wherein the identified anomalies comprise at least one anomaly in a part being welded.” Hartman teaches: determining anomalies in a part being welded, such as a weld joint, wherein the anomalies are categorized by an unacceptable classification (Hartman col. 6, lines 63-67 through to col. 7, line 5; col. 8, lines 45-63; and col. 9, lines 12-67).
Thus, it would have been obvious to Person Having Ordinary Skill in the Art (PHOSITA) before the effective filing date (EFD) to modify the system with the k-means clustering in the combined cited references to include the weld joint in Hartman. Doing so would enable “[a] method for determining the quality of an examined weld joint comprising the steps of providing acoustical data from the examined weld joint, and performing a neural network operation on the acoustical data determine the quality of the examined weld joint produced by a friction weld process. The neural network may be trained by the steps of providing acoustical data and observable data from at least one test weld joint, and training the neural network based on the acoustical data and observable data to form a trained neural network so that the trained neural network is capable of determining the quality of a examined weld joint based on acoustical data from the examined weld joint. In addition, an apparatus having a housing, acoustical sensors mounted therein, and means for mounting the housing on a friction weld device so that the acoustical sensors do not contact the weld joint. The apparatus may sample the acoustical data necessary for the neural network to determine the quality of a weld joint.” (Hartman Abstract).
Regarding claim 10, the rejection of claim 2 is incorporated. The cited references in combination do not explicitly teach: “wherein the identified anomalies comprise at least one anomaly in a weld fixture being used.” Hartman teaches: determining anomalies in a weld fixture being used, such as a weld joint with its bonding surfaces, wherein the anomalies are categorized by an unacceptable classification (Hartman col. 6, lines 63-67 through to col. 7, line 5; col. 8, lines 45-63; and col. 9, lines 12-67).
Thus, it would have been obvious to Person Having Ordinary Skill in the Art (PHOSITA) before the effective filing date (EFD) to modify the system with the k-means clustering in the combined cited references to include the weld joint in Hartman. A motivation to combine the cited references with Hartman was previously given.
Regarding claim 12, the rejection of claim 2 is incorporated. The cited references in combination do not explicitly teach: “wherein the identified anomalies comprise a deviation from a weld procedure specification.” Hartman teaches: determining anomalies due to deviation from a weld procedure specification, e.g., little to no bonding at the surfaces of weld joints, which is denoted by an unacceptable classification (Hartman col. 6, lines 63-67 through to col. 7, line 5; col. 8, lines 45-63; and col. 9, lines 12-67).
Thus, it would have been obvious to Person Having Ordinary Skill in the Art (PHOSITA) before the effective filing date (EFD) to modify the system with the k-means clustering in the combined cited references to include the weld procedure deviation in Hartman. A motivation to combine the cited references with Hartman was previously given.
Claim 11 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of U.S. Patent No. 11,347,191 (hereinafter ‘191) and Fidali et al., “Segmentation of Welding Arc Images for Purposes of Welding Diagnostics” (hereinafter Fidali) in view of Cribbs (U.S. Pat. App. Pre-Grant Pub. No. 2005/0004696, hereinafter Cribbs).
Regarding claim 11, the rejection of claim 2 is incorporated. The cited references in combination do not explicitly teach: “wherein the identified anomalies comprise at least one batch-to-batch difference in manufacturing.” Cribbs teaches: analyzing batches of products being manufactured and their differences/variations to determine anomalies (Cribbs [0060]-[0064] and [0074]-[0075]).
Thus, it would have been obvious to Person Having Ordinary Skill in the Art (PHOSITA) before the effective filing date (EFD) to modify the system with the k-means clustering in the combined cited references to include the batch determination in Cribbs. Doing so would enable a “technique for analyzing an anomalous condition in a process for producing a product is described, where the process includes plural subprocesses for performing operations on the product. The technique includes: (a) for each of the subprocesses, providing sensor output from at least one sensor used to measure information pertaining to the status of the respective subprocess; (b) for each of the subprocesses, extracting at least one representative value that is characteristic of a pattern expressed in the output, thus generating a plurality of representative values for the process as a whole; (c) retrieving data from a knowledge base, the data including a plurality of representative values, and also including information which maps the representative values to associated anomalous conditions; (d) analyzing the plurality of representative values output from the parameter extracting step with respect to the data stored in the knowledge base, and for generating a diagnostic result which diagnoses an anomalous condition in the process, and also identifies at least one of the subprocesses which has caused the anomalous condition; and (e) using the diagnostic result to affect corrective action to the at least one of the subprocesses which has caused the anomalous condition by adjusting at least one actuator that controls the at least one subprocess.” (Cribbs Abstract).
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 2-5, 8-12, 14, 16-19, and 21-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 for all claims
Under the first part of the analysis, claims 2-5, 8-12, 14, 16-19, and 21-24 recite a system. Accordingly, these claims fall within the four statutory categories and the analysis now proceeds to Step 2A, Prongs 1 and 2 and then Step 2B.
Claim 2
Step 2A, prong 1: the following limitations recite mental processes:
“… define first welding data …;
… define second welding data …; and
…
… identify anomalies in at least one of the weld, the weldment, or the weld process...
and detect the presence of the identified anomalies in subsequent welding data based on the model.”
The above limitations describe mental processes because, under a broadest reasonable interpretation (BRI), they involve: defining first and second welding data and identifying anomalies. Thus, the claim limitations recite mental processes because the limitations are based on observations, evaluations, judgments, or opinions that are performable in the human mind or with the aid of pencil and paper (see MPEP 2106.04(a)(2)(III)). Indeed, one can mentally or with the aid of pencil and paper define first and second welding data and identify anomalies.
As such, these limitations denote mental processes.
Step 2A, prong 2: the following limitations recite additional elements:
“A welding analysis system comprising:
first processing circuitry to process a first welding input from a first data source to …, wherein the first data source is associated with a weld, weldment, or weld process;
second processing circuitry to process a second welding input from a second data source to …, wherein the second data source is associated with the weld, weldment, or weld process;
a remotely situated analytics computing platform configured to:
receive the first welding data and the second welding data via a communication network communicatively coupled with the first processing circuitry and the second first processing circuitry;
pre-process the first welding data and the second welding data, wherein the pre-processing comprises applying one or more of data staging, cleaning, scaling, linearization, aggregation, filtering, smoothing, compression, integration, feature identification, cataloging and transformation;
process the first welding data and the second welding data….by using an unsupervised machine learning technique to classify the first welding data and the second welding data, wherein the identified anomalies comprise at least one of an equipment condition, equipment usage, or imminent equipment failure;
train a model based on a supervised machine learning technique using the classified data...”
The preamble and the limitation describing a remotely situated analytics computing platform recite additional elements related to mere instructions for applying the judicial exception on generic computing devices such as the welding analysis system and a remotely situated analytics computing platform (see MPEP 2106.05(f)), as well as a generic field of use via application to the welding analysis system and remotely situated analytics computing platform (see MPEP 2106.05(h)).
The processing of a first welding input by the first processing circuitry recites additional elements related to mere instructions for applying the judicial exception on a generic computing device such as the first processing circuitry (see MPEP 2106.05(f)), as well as a generic field of use via application to the first processing circuitry (see MPEP 2106.05(h)). Additionally, the limitation describing the composition of the first data source recites an additional element denoting a field of use (see MPEP 2106.05(h)).
The processing of a second welding input by the second processing circuitry recites additional elements related to mere instructions for applying the judicial exception on a generic computing device such as the second processing circuitry (see MPEP 2106.05(f)), as well as a generic field of use via application to the second processing circuitry (see MPEP 2106.05(h)). Additionally, the limitation describing the composition of the second data source recites an additional element denoting a field of use (see MPEP 2106.05(h)).
The receiving limitation recites, at a high level of generality, the additional element of an insignificant extra-solution activity related to mere data gathering and data manipulation (see MPEP 2106.05(g)). Additionally, the limitation describing the coupling of the communication network recites an additional element denoting a field of use (see MPEP 2106.05(h)).
The pre-processing limitation recites, at a high level of generality, the additional element of an insignificant extra-solution activity related to mere data gathering and data manipulation (see MPEP 2106.05(g)).
The processing of the first and second welding data limitation recites additional elements related to mere instructions for applying the judicial exception using a generic computing algorithm such as the unsupervised learning (see MPEP 2106.05(f)), as well as a generic field of use via application to the unsupervised learning (see MPEP 2106.05(h)).
The preamble and the remotely situated analytics computing platform limitation recite additional elements related to mere instructions for applying the judicial exception on generic computing devices and algorithm such as the welding analysis system, remotely situated analytics computing platform, and supervised learning technique (see MPEP 2106.05(f)), as well as a generic field of use via application to the welding analysis system, remotely situated analytics computing platform, and supervised learning technique (see MPEP 2106.05(h)).
As such, the claim limitations do not integrate the judicial exception into a practical application.
Step 2B: the limitations recited above do not amount to significantly more than the judicial exception. As stated above, the preamble and the limitation describing the remotely situated analytics computing platform recite mere instructions to apply the judicial exception on generic computing devices, wherein such application does not amount to significantly more than the judicial exception because the use of generic computing tools to execute the mere instruction for the judicial exception does not denote anything significantly more than the judicial exception (see MPEP 2106.05(f)). Furthermore, specifying that the claim limitation be applied to the welding analysis system and the remotely situated analytics computing platform is an implementation to a generic computer environment that has been held in FairWarning v. Iatric Sys to be merely indicative of a field of use or tech environment and thus not significantly more than the judicial exception (see MPEP 2106.05(h)).
The processing of a first welding input by the first processing circuitry recites mere instructions for applying the judicial exception on a generic computing device such as the first processing circuitry, wherein such application does not amount to significantly more than the judicial exception because the use of generic computing tools to execute the mere instruction for the judicial exception does not denote anything significantly more than the judicial exception (see MPEP 2106.05(f)). Furthermore, specifying that the claim limitation be applied to the first processing circuitry is an implementation to a generic computer environment that has been held in FairWarning v. Iatric Sys to be merely indicative of a field of use or tech environment and thus not significantly more than the judicial exception (see MPEP 2106.05(h)). Additionally, the limitation describing the composition of the first data source recites a field of use (see MPEP 2106.05(h)). Wherein the courts have held that describing a technological environment for the abstract idea is merely limiting the abstract idea to a technological environment indicative of a field use and as such, does not amount to significantly more than the judicial exception (see e.g., Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (limiting use of abstract idea to the Internet); Electric Power, 830 F.3d at 1354, 119 USPQ2d at 1742 (limiting application of abstract idea to electric power grid data); Intellectual Ventures I LLC v. Erie Indem. Co., 850 F.3d 1315, 1328-29, 121 USPQ2d 1928, 1939 (Fed. Cir. 2017) (limiting use of abstract idea to use with XML tags)).
The processing of a second welding input by the second processing circuitry recites mere instructions for applying the judicial exception on a generic computing device such as the second processing circuitry, wherein such application does not amount to significantly more than the judicial exception because the use of generic computing tools to execute the mere instruction for the judicial exception does not denote anything significantly more than the judicial exception (see MPEP 2106.05(f)). Furthermore, specifying that the claim limitation be applied to the second processing circuitry is an implementation to a generic computer environment that has been held in FairWarning v. Iatric Sys to be merely indicative of a field of use or tech environment and thus not significantly more than the judicial exception (see MPEP 2106.05(h)). Additionally, the limitation describing the composition of the second data source recites a field of use (see MPEP 2106.05(h)). Wherein the courts have held that describing a technological environment for the abstract idea is merely limiting the abstract idea to a technological environment indicative of a field use and as such, does not amount to significantly more than the judicial exception (see e.g., Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (limiting use of abstract idea to the Internet); Electric Power, 830 F.3d at 1354, 119 USPQ2d at 1742 (limiting application of abstract idea to electric power grid data); Intellectual Ventures I LLC v. Erie Indem. Co., 850 F.3d 1315, 1328-29, 121 USPQ2d 1928, 1939 (Fed. Cir. 2017) (limiting use of abstract idea to use with XML tags)).
The receiving limitation recites, at a high level of generality, an insignificant extra-solution activity related to mere data gathering (see MPEP 2106.05(g)). Wherein the courts have found that “receiving or transmitting data over a network” or “storing and retrieving information in memory” or “presenting offers and gathering statistics” are known to be well-understood, routine, and conventional activities when recited at a high level of generality (see MPEP 2106.05(d)(II)). Additionally, the limitation describing the coupling of the communication network recites a field of use (see MPEP 2106.05(h)). Wherein the courts have held that describing a technological environment for the abstract idea is merely limiting the abstract idea to a technological environment indicative of a field use and as such, does not amount to significantly more than the judicial exception (see e.g., Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (limiting use of abstract idea to the Internet); Electric Power, 830 F.3d at 1354, 119 USPQ2d at 1742 (limiting application of abstract idea to electric power grid data); Intellectual Ventures I LLC v. Erie Indem. Co., 850 F.3d 1315, 1328-29, 121 USPQ2d 1928, 1939 (Fed. Cir. 2017) (limiting use of abstract idea to use with XML tags)).
The processing of the first and second welding data limitation recites mere instructions for applying the judicial exception using a generic computing algorithm such as the unsupervised learning, wherein such application does not amount to significantly more than the judicial exception because the use of generic computing tools to execute the mere instruction for the judicial exception does not denote anything significantly more than the judicial exception (see MPEP 2106.05(f)). Furthermore, specifying that the claim limitation be applied using the unsupervised learning is an implementation to a generic computer environment that has been held in FairWarning v. Iatric Sys to be merely indicative of a field of use or tech environment and thus not significantly more than the judicial exception (see MPEP 2106.05(h)).
The process of supervised machine learning recites mere instructions to apply the judicial exception on generic computing devices and algorithm, wherein such application does not amount to significantly more than the judicial exception because the use of generic computing tools to execute the mere instruction for the judicial exception does not denote anything significantly more than the judicial exception (see MPEP 2106.05(f)). Furthermore, specifying that the claim limitation be applied to the welding analysis system, remotely situated analytics computing platform, and supervised learning technique is an implementation to a generic computer environment that has been held in FairWarning v. Iatric Sys to be merely indicative of a field of use or tech environment and thus not significantly more than the judicial exception (see MPEP 2106.05(h)).
Thus, the limitations do not amount to significantly more than the judicial exception.
Claim 3
Step 2A, prong 1: the following limitation recites mental processes:
“… identify the anomalies”.
The above claim limitation recites a mental process because identifying anomalies is a process based on observations, evaluations, judgments, or opinions that are performable in the human mind or with the aid of pencil and paper (see MPEP 2106.04(a)(2)(III)). Indeed, one can mentally or with the aid of pencil and paper identify anomalies.
As such, this limitation denotes mental processes.
Step 2A, prong 2: the following limitations recite additional elements:
“The welding analysis system as defined in claim 2, wherein the remotely situated analytics computing platform is configured to … in at least one of:
weld quality; arc time patterns; idle time patterns; equipment duty cycle patterns; input power consumption and fluctuation patterns; welding consumable consumption patterns; or usage patterns on functions available from welding equipment associated with the first welding data or the second welding data.
The preamble and the remotely situated analytics computing platform limitation recite additional elements related to mere instructions for applying the judicial exception on generic computing devices and algorithm such as the welding analysis system, remotely situated analytics computing platform, and supervised learning technique (see MPEP 2106.05(f)), as well as a generic field of use via application to the welding analysis system, remotely situated analytics computing platform, and supervised learning technique (see MPEP 2106.05(h)).
The limitation describing the various data such as weld quality, arc time patterns, etc. recites an additional element denoting a field of use (see MPEP 2106.05(h)).
Thus, the limitations do not integrate the judicial exception into a practical application.
Step 2B: the limitations recited above do not amount to significantly more than the judicial exception. As stated above, the preamble and the remotely situated analytics computing platform limitation recite mere instructions to apply the judicial exception on generic computing devices, wherein such application does not amount to significantly more than the judicial exception because the use of generic computing tools to execute the mere instruction for the judicial exception does not denote anything significantly more than the judicial exception (see MPEP 2106.05(f)). Furthermore, specifying that the claim limitation be applied to the welding analysis system and remotely situated analytics computing platform is an implementation to a generic computer environment that has been held in FairWarning v. Iatric Sys to be merely indicative of a field of use or tech environment and thus not significantly more than the judicial exception (see MPEP 2106.05(h)).
The limitation describing the various data such as weld quality, arc time patterns, etc. recites a field of use (see MPEP 2106.05(h)). Wherein the courts have held that describing a technological environment for the abstract idea is merely limiting the abstract idea to a technological environment indicative of a field use and as such, does not amount to significantly more than the judicial exception (see e.g., Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (limiting use of abstract idea to the Internet); Electric Power, 830 F.3d at 1354, 119 USPQ2d at 1742 (limiting application of abstract idea to electric power grid data); Intellectual Ventures I LLC v. Erie Indem. Co., 850 F.3d 1315, 1328-29, 121 USPQ2d 1928, 1939 (Fed. Cir. 2017) (limiting use of abstract idea to use with XML tags)).
Thus, the limitations do not amount to significantly more than the judicial exception.
Claim 4
Step 2A, prong 1: the following limitations recite mental processes:
“… a data clustering technique to identify the anomalies based on the first welding data and the second welding data.”
The above claim limitation recites a mental process because clustering data to identify anomalies based on the first and second welding data is a process based on observations, evaluations, judgments, or opinions that are performable in the human mind or with the aid of pencil and paper (see MPEP 2106.04(a)(2)(III)). Indeed, one can mentally or with the aid of pencil and paper cluster data to identify anomalies based on the first and second welding data.
As such, these limitations denote mental processes.
Step 2A, prong 2: the following limitations recite additional elements:
“The welding analysis system as defined in claim 2, wherein the unsupervised learning technique comprises ….”
The preamble and unsupervised learning limitation recite additional elements related to mere instructions for applying the judicial exception on a generic computing device and algorithm such as the welding analysis system and unsupervised learning (see MPEP 2106.05(f)), as well as a generic field of use via application to the welding analysis system and unsupervised learning (see MPEP 2106.05(h)).
Thus, the limitations do not integrate the judicial exception into a practical application.
Step 2B: the limitations recited above do not amount to significantly more than the judicial exception. As stated above, the preamble recites mere instructions to apply the judicial exception on generic computing device and algorithm, wherein such application does not amount to significantly more than the judicial exception because the use of generic computing tools to execute the mere instruction for the judicial exception does not denote anything significantly more than the judicial exception (see MPEP 2106.05(f)). Furthermore, specifying that the claim limitation be applied to the welding analysis system and the unsupervised learning is an implementation to a generic computer environment that has been held in FairWarning v. Iatric Sys to be merely indicative of a field of use or tech environment and thus not significantly more than the judicial exception (see MPEP 2106.05(h)).
Claim 5
Step 2A, prong 1: the claim inherits the mental processes from the independent claim. The claim does not recite additional mental processes.
Step 2A, prong 2: the following limitations recite additional elements:
“The welding analysis system as defined in claim 4, wherein the data clustering comprises at least one of k-means, hierarchical, conceptual, probability-based, or Bayesian clustering.”
The preamble recites additional elements related to mere instructions for applying the judicial exception on generic computing devices such as the welding analysis system (see MPEP 2106.05(f)), as well as a generic field of use via application to the welding analysis system (see MPEP 2106.05(h)).
The limitation describing the composition of the data clustering recites an additional element denoting a field of use (see MPEP 2106.05(h)).
Thus, the limitations do not integrate the judicial exception into a practical application.
Step 2B: the limitations recited above do not amount to significantly more than the judicial exception. As stated above, the preamble recites mere instructions to apply the judicial exception on generic computing devices, wherein such application does not amount to significantly more than the judicial exception because the use of generic computing tools to execute the mere instruction for the judicial exception does not denote anything significantly more than the judicial exception (see MPEP 2106.05(f)). Furthermore, specifying that the claim limitation be applied to the welding analysis system is an implementation to a generic computer environment that has been held in FairWarning v. Iatric Sys to be merely indicative of a field of use or tech environment and thus not significantly more than the judicial exception (see MPEP 2106.05(h)).
The limitation describing the composition of the data clustering recites a field of use (see MPEP 2106.05(h)). Wherein the courts have held that describing a technological environment for the abstract idea is merely limiting the abstract idea to a technological environment indicative of a field use and as such, does not amount to significantly more than the judicial exception (see e.g., Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (limiting use of abstract idea to the Internet); Electric Power, 830 F.3d at 1354, 119 USPQ2d at 1742 (limiting application of abstract idea to electric power grid data); Intellectual Ventures I LLC v. Erie Indem. Co., 850 F.3d 1315, 1328-29, 121 USPQ2d 1928, 1939 (Fed. Cir. 2017) (limiting use of abstract idea to use with XML tags)).
Thus, the limitations do not amount to significantly more than the judicial exception.
Claim 8
Step 2A, prong 1: the claim inherits the mental processes from the independent claim. The claim does not recite additional mental processes.
Step 2A, prong 2: the following limitations recite additional elements:
“The welding analysis system as defined in claim 2, wherein the identified anomalies comprise at least one of a welding gas anomaly, a welding wire anomaly, a flux anomaly, a contact tip anomaly, a torch nozzle anomaly, or a wire liner anomaly.”
The preamble recites additional elements related to mere instructions for applying the judicial exception on generic computing devices such as the welding analysis system (see MPEP 2106.05(f)), as well as a generic field of use via application to the welding analysis system (see MPEP 2106.05(h)).
The limitation describing the composition of the identified anomalies recites an additional element denoting a field of use (see MPEP 2106.05(h)).
Thus, the limitations do not integrate the judicial exception into a practical application.
Step 2B: the limitations recited above do not amount to significantly more than the judicial exception. As stated above, the preamble recites mere instructions to apply the judicial exception on generic computing devices, wherein such application does not amount to significantly more than the judicial exception because the use of generic computing tools to execute the mere instruction for the judicial exception does not denote anything significantly more than the judicial exception (see MPEP 2106.05(f)). Furthermore, specifying that the claim limitation be applied to the welding analysis system is an implementation to a generic computer environment that has been held in FairWarning v. Iatric Sys to be merely indicative of a field of use or tech environment and thus not significantly more than the judicial exception (see MPEP 2106.05(h)).
The limitation describing the composition of the identified anomalies recites a field of use (see MPEP 2106.05(h)). Wherein the courts have held that describing a technological environment for the abstract idea is merely limiting the abstract idea to a technological environment indicative of a field use and as such, does not amount to significantly more than the judicial exception (see e.g., Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (limiting use of abstract idea to the Internet); Electric Power, 830 F.3d at 1354, 119 USPQ2d at 1742 (limiting application of abstract idea to electric power grid data); Intellec