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 .
Response to Arguments
Applicant’s arguments, see pages 11-12, filed 04/02/26, with respect to the rejections of claims 1, 6, and 13 under 35 U.S.C. 102 as anticipated by Law et al. US 2023/0229148 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 Therefore, the rejection has been withdrawn.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 Law et al. in view of Tamaki et al. US 2025/0029006 (“Tamaki”).
Applicant's arguments, see pages 12-13, filed 04/02/26, with respect to the rejection(s) of claims 14 and 19 under 35 U.S.C. 102 as anticipated by Melikian US 2010/0201803 have been fully considered but they are not persuasive. Applicant argues that Melikian does not disclose “identifying, based on analyzing the sensor data, a process definition” as recited in amended claim 14, and similarly recited in amended claim 19. However, examiner notes that Melikian discloses a process of learning an object in Fig. 15. The “learned object” of Melikian corresponds to the claimed “process definition”. Specifically, Melikian discloses creating a descriptor for each icon of a sensed image of a production process. In addition or alternatively, each icon may also be tagged or otherwise associated with a learned object name (e.g., Fig. 15, [0065]). This learned object or process definition is stored in database 50 for future reference (e.g., [0045], [0079]).
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.
Claims 14-17 and 19-22 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Melikian US 2010/0201803.
14. A method of visualizing a process definition for an industrial process to create a product in an industrial plant, the method comprising:
analyzing sensor data including one or more of: images of an individual, videos of the individual, audio of the individual, or location data of the individual, captured as the individual performs a set of process operations to a set of process materials to make a product (e.g., [0004]-[0005], [0030]-[0045]);
identifying, based on analyzing the sensor data, a process definition including one or more of: the set of process materials for making the product, one or more equipment used to make the product, the set of process operations applied to the material to make the product, a sequence of the process operations, a timing of the process operations, or quantity information regarding the materials used in the process (e.g., Fig. 15 #308, [0065]: “At block 308, a descriptor each icon is created. In addition or in the alternative, each icon may also be tagged or otherwise associated with a learned object name.”, [0045], [0079]);
generating, based on analyzing the sensor data associated with the individual performing the set of process operations to the set of process materials to make the product, a visualization of the set of process operations being performed to the set of process materials to make the product, wherein the visualization illustrates one or more of the set of process materials for making the product, the one or more equipment used to make the product, the set of process operations applied to the materials to make the product, the sequence of the process operations, the timing of the process operations, or the quantity information regarding the materials used in the process (e.g., [0004]-[0005], [0030]-[0045]); and
providing, via a user interface, the visualization of the individual performing the set of process operations to the set of process materials to make the product (e.g., [0004]-[0005], [0030]-[0045]).
15. The method of claim 14, wherein providing the visualization of the individual performing the set of process operations to the set of process materials to make the product includes providing an augmented reality (AR) visualization of the individual performing the set of process operations to the set of process materials to make the product (e.g., [0071]-[0074]).
16. The method of claim 15, wherein providing the AR visualization of the individual performing the set of process operations to the set of process materials to make the product includes providing the AR visualization of the individual performing the set of process operations to the set of process materials to make the product, overlaid upon a process environment in which the sensor data associated with the individual performing the set of process operations to the set of process materials to make the product was captured (e.g., [0071]-[0074]).
17. The method of claim 14, further comprising:
receiving input from a user requesting a particular process operation of the set of process operations (e.g., [0078]-[0080]); and
providing, via the user interface, the visualization of the particular process operation of the set of process operations, isolated from the set of process operations, based on the input from the user (e.g., [0078]-[0080]).
19. A system for visualizing a process definition for an industrial process to create a product in an industrial plant, the system comprising:
a user interface (e.g., [0037]-[0040]);
one or more processors (e.g., [0037]-[0040]);
a memory storing computer-readable instructions that, when executed by the one or more processors (e.g., [0037]-[0040]), cause the one or more processors to:
analyze sensor data including one or more of: images of an individual, videos of the individual, audio of the individual, or location data of the individual, captured as the individual performs a set of process operations to a set of process materials to make a product (e.g., [0004]-[0005], [0030]-[0045]);
identify, based on analyzing the sensor data, a process definition including one or more of: the set of process materials for making the product, one or more equipment used to make the product, the set of process operations applied to the material to make the product, a sequence of the process operations, a timing of the process operations, or quantity information regarding the materials used in the process (e.g., Fig. 15 #308, [0065]: “At block 308, a descriptor each icon is created. In addition or in the alternative, each icon may also be tagged or otherwise associated with a learned object name.”, [0045], [0079]);
generate, based on analyzing the sensor data associated with the individual performing the set of process operations to the set of process materials to make the product, a visualization of the set of process operations being performed to the set of process materials to make the product, wherein the visualization illustrates one or more of the set of process materials for making the product, the one or more equipment used to make the product, the set of process operations applied to the materials to make the product, the sequence of the process operations, the timing of the process operations, or the quantity information regarding the materials used in the process (e.g., [0004]-[0005], [0030]-[0045]); and
provide, via the user interface, the visualization of the individual performing the set of process operations to the set of process materials to make the product (e.g., [0004]-[0005], [0030]-[0045]).
20. The system of claim 19, wherein providing the visualization of the individual performing the set of process operations to the set of process materials to make the product includes providing an augmented reality (AR) visualization of the individual performing the set of process operations to the set of process materials to make the product (e.g., [0071]-[0074]).
21. The system of claim 20, wherein providing the AR visualization of the individual performing the set of process operations to the set of process materials to make the product includes providing the AR visualization of the individual performing the set of process operations to the set of process materials to make the product, overlaid upon a process environment in which the sensor data associated with the individual performing the set of process operations to the set of process materials to make the product was captured (e.g., [0071]-[0074]).
22. The system of claim 19, wherein the instructions, when executed by the one or more processors, further cause the one or more processors to:
receive input from a user requesting a particular process operation of the set of process operations (e.g., [0078]-[0080]); and
provide, via the user interface, the visualization of the particular process operation of the set of process operations, isolated from the set of process operations, based on the input from the user (e.g., [0078]-[0080]).
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.
Claims 1, 3, 4, 6-9, 11-13, and 24 are rejected under 35 U.S.C. 103 as being unpatentable over Law et al. US 2023/0229148 (“Law”) in view of Tamaki et al. US 2025/0029006 (“Tamaki”).
Law discloses:
1. A method of automatically generating a process definition for an industrial process to create a product in an industrial plant (e.g., Fig. 5J, [0124]: See creation of the universal process definition UPD via reverse transform module 450 from a small scale development plant.), the method comprising:
capturing sensor data including one or more of: including one or more of: images of an individual, videos of the individual, or location data of the individual(e.g., [0079], [0127]: The data on which the reverse transform is applied comprises measurement equipment data, i.e. captured sensor data, [0053], [0064]-[0065]: Said measurement data comprises sensor data for processes resulting from actions of personnel/operators/engineers running equipment at the site to implement the process. Hence, said measurement data can be considered as associated to personnel/operators/engineers running said equipment.);
analyzing the captured sensor data (e.g., [0079], [0127], [0053], [0064]-[0065]); and
identifying, based on analyzing the captured sensor data, a process definition including one or more of: the set of process materials for making the product, one or more equipment used to make the product, the set of process operations applied to the materials to make the product, a sequence of the process operations, a timing of the process operations, or quantity information regarding the materials used in the process (e.g., Fig. 5J, [0124]: See creation of the universal process definition UPD via reverse transform module 450 from a small scale development plant, Fig. 4: See UPD which comprises the set of materials, equipment, sequence of operations, etc.).
3. The method of claim 1, wherein the sensor data includes data from sensors associated with one or more equipment involved in the set of process operations (e.g., [0127]).
4. The method of claim 1, wherein the sensor data includes location sensor data associated with one or more process materials of the set of process materials, or one or more equipment involved in the set of process operations (e.g., [0059], [0102], [0170], [0179]).
6. A system for automatically generating a process definition for an industrial process to create a product in an industrial plant, the system comprising:
one or more sensors configured to capture sensor data including one or more of: images of an individual, videos of the individual, audio of the individual, or location data of the individual(e.g., [0079], [0127]: The data on which the reverse transform is applied comprises measurement equipment data, i.e. captured sensor data, [0053], [0064]-[0065]: Said measurement data comprises sensor data for processes resulting from actions of personnel/operators/engineers running equipment at the site to implement the process. Hence, said measurement data can be considered as associated to personnel/operators/engineers running said equipment.);
one or more processors (e.g., [0138]);
a memory storing computer-readable instructions that, when executed by the one or more processors (e.g., [0138]), cause the one or more processors to:
analyze the captured sensor data (e.g., [0079], [0127], [0053], [0064]-[0065]); and
identify, based on analyzing the captured sensor data, a process definition including one or more of: the set of process materials for making the product, one or more equipment used to make the product, the set of process operations applied to the materials to make the product, a sequence of the process operations, a timing of the process operations, or quantity information regarding the materials used in the process (e.g., Fig. 5J, [0124]: See creation of the universal process definition UPD via reverse transform module 450 from a small scale development plant, Fig. 4: See UPD which comprises the set of materials, equipment, sequence of operations, etc.).
7. The system of claim 6, wherein the sensor data includes audio data, associated with an individual, captured as the individual performs one or more process operations of the set of process operations (e.g., [0140]).
8. The system of claim 6, wherein the sensor data includes data from sensors associated with one or more equipment involved in the set of process operations (e.g., [0127]).
9. The system of claim 6, wherein the sensor data includes location sensor data associated with one or more process materials of the set of process materials, one or more equipment involved in the set of process operations (e.g., [0059], [0102], [0170], [0179]).
11. The system of claim 6, further comprising a user interface, and wherein the computer-readable instructions, when executed by the one or more processors, further cause the one or more processors to:
provide the identified process definition via the user interface;
receive, via the user interface, an adjustment of one or more of: the set of process materials for making the product, the one or more equipment used to make the product, the set of process operations applied to the materials to make the product, the sequence of the process operations, the timing of the process operations, or the quantity information regarding the materials used in the process; and
update the process definition based on the adjustment received via the user interface (e.g., [0049], [0128]).
12. A method of automatically generating a configuration hierarchy for a process definition for an industrial process to create a product in an industrial plant, the method comprising:
analyzing sensor data including one or more of: images of an individual, videos of the individual, audio of the individual, or location data of the individual(e.g., [0079], [0127], [0053], [0064]-[0065]);
identifying, based on analyzing the sensor data, the set of process operations applied to the materials to make the product and one or more equipment used in each of the process operations (e.g., Fig. 5J, [0124]: See creation of the universal process definition UPD via reverse transform module 450 from a small scale development plant, Fig. 4: See UPD which comprises the set of materials, equipment, sequence of operations, etc.); and
determining, based on the set of process operations applied to the materials to make the product and the one or more equipment used in each of the process operations, a hierarchy level of the industrial plant associated with each of the process operations (e.g., [0043]: “logical or physical grouping of plant equipment”, [0100]: “data defining the logical and/or physical configuration of the process control system”).
13. A system for automatically generating a configuration hierarchy for a process definition for an industrial process to create a product in an industrial plant, the system comprising:
one or more processors (e.g., [0138]);
a memory storing computer-readable instructions that, when executed by the one or more processors (e.g., [0138]), cause the one or more processors to:
analyze sensor data including one or more of: images of an individual, videos of the individual, audio of the individual, or location data of the individual(e.g., [0079], [0127], [0053], [0064]-[0065]);
identify, based on analyzing the sensor data, the set of process operations applied to the materials to make the product and one or more equipment used in each of the process operations (e.g., Fig. 5J, [0124]: See creation of the universal process definition UPD via reverse transform module 450 from a small scale development plant, Fig. 4: See UPD which comprises the set of materials, equipment, sequence of operations, etc.); and
determine, based on the set of process operations applied to the materials to make the product and the one or more equipment used in each of the process operations, a hierarchy level of the industrial plant associated with each of the process operations (e.g., [0043]: “logical or physical grouping of plant equipment”, [0100]: “data defining the logical and/or physical configuration of the process control system”).
24. The method of claim 1, further comprising:
providing, via a user interface, the identified process definition;
receiving, via the user interface, an adjustment of one or more of:
the set of process materials for making the product, the one or more equipment used to make the product, the set of process operations applied to the materials to make the product, the sequence of the process operations, the timing of the process operations, or the quantity information regarding the materials used in the process; and
updating the process definition based on the adjustment received via the user interface (e.g., [0049], [0128]).
Law discloses capturing sensor data including process data generated by the execution of the industrial process at the site, including operator or personnel generated photographs/images (e.g., [0140]).
However, Law does not explicitly disclose capturing sensor data including one or more of: including one or more of: images of an individual, videos of the individual, or location data of the individual, captured as the individual performs a set of process operations to a set of process materials to make a product, as recited in claims 1, 6, 12, and 13.
Tamaki discloses an operation learning system comprising capturing sensor data including one or more of: including one or more of: images of an individual, videos of the individual, or location data of the individual, captured as the individual performs a set of process operations to a set of process materials to make a product (e.g., [0007]).
Law and Tamaki are analogous art since both pertain to creating process definitions or learned model from data collected in a production plant while an operator performs a set of process operations to make a product.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Law with Tamaki in order to readily obtain location information indicating the operation type of the operation being performed by the operator of Law at this location, as taught by Tamaki (e.g., [0008]).
Claims 2, 5, and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Law as modified by Tamaki as applied to claims 1 and 6 above, and further in view of Ishikawa et al. US 2020/0135195 (“Ishikawa”).
Law does not disclose the feature of claims 5 and 10.
Ishikawa (in combination with Law) discloses:
2. The method of claim 1, wherein the sensor data includes audio data, associated with an individual, captured as the individual performs one or more process operations of the set of process operations (e.g., [0007]-[0019]).
5. The method of claim 1, wherein analyzing the sensor data includes analyzing audio data to identify words or phrases spoken by the individual as the individual performs one or more process operations of the set of process operations (e.g., [0007]-[0019]).
10. The system of claim 6, wherein analyzing the sensor data includes analyzing audio data to identify words or phrases spoken by the individual as the individual performs one or more process operations of the set of process operations (e.g., [0007]-[0019]).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Law and Tamaki with Ishikawa in order to analyze correlations between conversation data, action data, and task status data in an industrial plant environment.
Claims 18 and 23 are rejected under 35 U.S.C. 103 as being unpatentable over Melikian in view of Mehrotra et al. US 2021/0150438 (“Mehrotra”).
Melikian does not explicitly disclose the features of claims 18 and 23.
Mehrotra (in combination with Melikian) discloses:
18. The method of claim 14, further comprising:
receiving input from a user indicating a request to increase or decrease a speed associated with the visualization of one or more process operations of the set of process operations (e.g., Fig. 12, claim 15, claim 19: “receiving an input at the computing device, wherein the input is indicative of an instruction to continue to a second instruction”); and
providing, via the user interface, a slowed-down or sped-up visualization of the one or more process operations of the set of process operations based on the input from the user (e.g., Fig. 12, claim 15, claim 19: “receiving an input at the computing device, wherein the input is indicative of an instruction to continue to a second instruction”).
23. The system of claim 19, wherein the instructions, when executed by the one or more processors, further cause the one or more processors to:
receive input from a user indicating a request to increase or decrease a speed associated with the visualization of one or more process operations of the set of process operations (e.g., Fig. 12, claim 15, claim 19: “receiving an input at the computing device, wherein the input is indicative of an instruction to continue to a second instruction”); and
provide, via the user interface, a slowed-down or sped-up visualization of the one or more process operations of the set of process operations based on the input from the user (e.g., Fig. 12, claim 15, claim 19: “receiving an input at the computing device, wherein the input is indicative of an instruction to continue to a second instruction”).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Melikian with Mehrotra in order to allow someone to view the instructional welding sequence of Melikian at a faster pace in order to get to the portion of the tutorial sequence they are concerned with. This prevents them from wasting time viewing instructions they are already familiar with.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Baier et al. US 2009/0089709 discloses a visualization system that generates customized visualizations in an industrial automation environment includes an interface component that receives input concerning displayed objects and information, a context component that can detect, infer or determine context information regarding an entity, and a visualization component that dynamically generates a visualization from a set of display object to present to the entity that is a function of the received information and inferred or determined entity context.
Reichard et al. US 2008/0294275 discloses an industrial control monitoring system provides visualization of historical data acquired from an industrial process in a manner that mimic real-time visualization of real-time data acquired from the industrial process. The monitoring system provides an operator interface that allows the operator to direct playback interactively, such as rewinding and forwarding of the playback.
Yoshida et al. US 2025/0148830 discloses an action evaluation method for evaluating efficiency of a series of operations performed by a worker. An action evaluation system can include an action detection unit that detects a plurality of unit actions included in a series of operations performed by a worker from image data, according to a stored unit action pattern, and a time measurement unit that measures a time taken for the series of operations. The time measurement unit can also measure a time of each detected unit action and a time between the unit actions.
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 RYAN A JARRETT whose telephone number is (571)272-3742. The examiner can normally be reached M-F 9:00-5:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kenneth Lo can be reached at 571-272-9774. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RYAN A JARRETT/ Primary Examiner, Art Unit 2116
06/05/26
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