Prosecution Insights
Last updated: April 18, 2026
Application No. 18/375,727

Automated Recipe Generation

Non-Final OA §102§103
Filed
Oct 02, 2023
Examiner
JARRETT, RYAN A
Art Unit
2116
Tech Center
2100 — Computer Architecture & Software
Assignee
Fisher-Rosemount Systems Inc.
OA Round
1 (Non-Final)
81%
Grant Probability
Favorable
1-2
OA Rounds
2y 10m
To Grant
88%
With Interview

Examiner Intelligence

Grants 81% — above average
81%
Career Allow Rate
695 granted / 861 resolved
+25.7% vs TC avg
Moderate +8% lift
Without
With
+7.7%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
20 currently pending
Career history
881
Total Applications
across all art units

Statute-Specific Performance

§101
8.2%
-31.8% vs TC avg
§103
29.9%
-10.1% vs TC avg
§102
34.3%
-5.7% vs TC avg
§112
20.0%
-20.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 861 resolved cases

Office Action

§102 §103
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 . 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 1-4, 6-9, and 11-13 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Law et al. US 2023/0229148 (“Law”). 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 associated with an individual performing a set of process operations to a set of process materials to make a product (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 sensor data associated with the individual performing the set of process operations to the set of process materials to make the product (e.g., [0079], [0127], [0053], [0064]-[0065]); and identifying, 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 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.). 2. The method of claim 1, wherein the sensor data includes one or more of: image data, video data, or 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]). 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, one or more equipment involved in the set of process operations, or the individual involved in the set of process operations (e.g., [0059], [0102], [0170], [0179]). 6. 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]). 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 associated with an individual performing a set of process operations to a set of process materials to make a product (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 sensor data associated with the individual performing the set of process operations to the set of process materials to make the product (e.g., [0079], [0127], [0053], [0064]-[0065]); and identify, 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 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 one or more of: image data, video data, or 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, or the individual 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 associated with an individual performing a set of process operations to a set of process materials to make a product (e.g., [0079], [0127], [0053], [0064]-[0065]); identifying, 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, 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 associated with an individual performing a set of process operations to a set of process materials to make a product (e.g., [0079], [0127], [0053], [0064]-[0065]); identify, 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, 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”). 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 associated with an individual performing a set of process operations to a set of process materials to make a product (e.g., [0004]-[0005], [0030]-[0045]); 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, 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., [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 associated with an individual performing a set of process operations to a set of process materials to make a product (e.g., [0004]-[0005], [0030]-[0045]); 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, 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., [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 5 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Law 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: 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 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. 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. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kamini Shah can be reached at 571-272-2279. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /RYAN A JARRETT/Primary Examiner, Art Unit 2116 11/28/25
Read full office action

Prosecution Timeline

Oct 02, 2023
Application Filed
Nov 28, 2025
Non-Final Rejection — §102, §103
Mar 31, 2026
Applicant Interview (Telephonic)
Mar 31, 2026
Examiner Interview Summary
Apr 02, 2026
Response Filed

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
81%
Grant Probability
88%
With Interview (+7.7%)
2y 10m
Median Time to Grant
Low
PTA Risk
Based on 861 resolved cases by this examiner. Grant probability derived from career allow rate.

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