Prosecution Insights
Last updated: April 19, 2026
Application No. 17/607,489

CONTROL SYSTEM, SUPPORT DEVICE, AND SUPPORT PROGRAM

Non-Final OA §101§103§112
Filed
Oct 29, 2021
Examiner
TRUONG, LOAN
Art Unit
2114
Tech Center
2100 — Computer Architecture & Software
Assignee
Omron Corporation
OA Round
3 (Non-Final)
77%
Grant Probability
Favorable
3-4
OA Rounds
3y 4m
To Grant
90%
With Interview

Examiner Intelligence

Grants 77% — above average
77%
Career Allow Rate
458 granted / 594 resolved
+22.1% vs TC avg
Moderate +13% lift
Without
With
+12.8%
Interview Lift
resolved cases with interview
Typical timeline
3y 4m
Avg Prosecution
32 currently pending
Career history
626
Total Applications
across all art units

Statute-Specific Performance

§101
10.5%
-29.5% vs TC avg
§103
44.9%
+4.9% vs TC avg
§102
25.0%
-15.0% vs TC avg
§112
10.5%
-29.5% vs TC avg
Black line = Tech Center average estimate • Based on career data from 594 resolved cases

Office Action

§101 §103 §112
DETAILED ACTION This office action is in response applicant’s remarks filed on November 14, 2024 in application 17/607,489. Certified copy of foreign priority application from Japan on May 29, 2019 is acknowledged. Claims 1-16 are presented for examination. Claims 1-16 are amended. 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 . Information Disclosure Statement The information disclosure statements (IDS) submitted on 10/19/21, 8/10/23, 10/16/23 and 3/6/24 were in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements were considered by the Examiner. Response to Arguments Applicant's arguments filed November 14, 2024 in regard to the 35 USC 112 and 35 USC 101 have been fully considered but they are not persuasive. The claims recited plurality of processing resources for execution where the processing resources does not recite sufficient structure, material, or acts to perform that function. The plurality of processing resources could be implements in other embodiments such as (software, VM, ect.,) and therefore lacks sufficient structure. In regard to the 35 USC 101 rejection, the claims are interpreted as software per se. Correction is advised. Applicant’s arguments with respect to claim(s) 1-16, the claims have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Claim Rejections - 35 USC § 112 Claim limitation “industrial control system, support device and non-transitory storage medium” invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. Claims 1-8 recited an industrial control system comprising a plurality of processing resources where the plurality of resources perform state value collection processing and anomaly detection processing. Claims 9, 11-13 recited a support device to perform state value collection processing and anomaly detection processing. Claims 10, 14-16 recited a non-transitory storage medium storing a support program to perform state value collection processing and anomaly detection processing. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph. Applicant may: (a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph; (b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or (c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)). If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either: (a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or (b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181. Claim limitation 1-16 has been evaluated under the three-prong test set forth in MPEP § 2181, subsection I, but the result is inconclusive. Thus, it is unclear whether this limitation should be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the control system, support device and non-transitory storage medium as claimed lack sufficient structures. The boundaries of this claim limitation are ambiguous; therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph. In response to this rejection, applicant must clarify whether this limitation should be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. Mere assertion regarding applicant’s intent to invoke or not invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph is insufficient. Applicant may: (a) Amend the claim to clearly invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, by reciting “means” or a generic placeholder for means, or by reciting “step.” The “means,” generic placeholder, or “step” must be modified by functional language, and must not be modified by sufficient structure, material, or acts for performing the claimed function; (b) Present a sufficient showing that 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, should apply because the claim limitation recites a function to be performed and does not recite sufficient structure, material, or acts to perform that function; (c) Amend the claim to clearly avoid invoking 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, by deleting the function or by reciting sufficient structure, material or acts to perform the recited function; or (d) Present a sufficient showing that 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, does not apply because the limitation does not recite a function or does recite a function along with sufficient structure, material or acts to perform that function. 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. As per claims 1-8, the claimed system has been read in view of applicant’s specification (see paragraph 62). The claimed “An industrial control system" comprising a plurality of processing resources wherein the plurality of resources perform a state value collection processing and anomaly detection processing, where the processing resources is not defined in the specification except “a function provided by support device 300 is realized by using a part of modules provide by the OS,” para. 62, and appears to include elements which could be interpreted as including only software. As per claims 9, 11-13, the claimed support device has been read in view of applicant’s specification (see paragraph 62). The claimed “support device" used in a control system wherein the control system comprising of a plurality of processing resources wherein the plurality of resources comprise (collection and detection processing), where the processing resources is not defined in the specification except “a function provided by support device 300 is realized by using a part of modules provide by the OS,” para. 62, and appears to include elements which could be interpreted as including only software. As per claims 10, 14-16, the claimed non-transitory storage medium has been read in view of applicant’s specification (see paragraph 61-62). The claimed “non-transitory storage medium" storing thereon a support program, when executed to provide a user interface appears to include elements which could be interpreted as including only software. Software is not one of the four categories of invention and therefore these claims are not statutory. Software is not a series of steps or acts and thus is not a process. Software is not a physical article or object and as such is not a machine or manufacture. Software is not a combination of substances and therefore not a composition of matter. See MPEP § 2106. The Examiner suggests amending the claims to explicitly include physical hardware in the system. 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 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. The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. Claims 1-2, and 6-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Arscott et al. (US 2012/0167078) in further view of Hartman (US 2006/0236374). In regard to claim 1, Arscott et al. teach an industrial control system configured to control a control target, the industrial control system comprising: a plurality of processing resources available for execution of arithmetic processing (plurality of virtual instances, para. 20), each of the plurality of processing resources comprising a memory storing a program and a processor configured to access the memory and execute the program (CPU load and memory usage of the virtual instance, para. 40-42, data division and service manager module provides a process for interfacing the virtual instances to management station, para. 22, 31-32), wherein the plurality of processing resources are configured to perform at least: state value collection processing that collects one or more state values in the industrial control system (data division can be used as a cache to store test result, fig. 3, para. 32-38, 50), and anomaly detection processing that calculates a value indicating a possibility that an anomaly has occurred in a detection target included in the control targets based on a feature value calculated from the one or more state values having been collected (service manager, fig. 3, para. 21-22, 66). Arscott et al. does not explicitly teach but Hartman teaches state values as control targets of a manufacturing device and a production line (industrial control devices are arrange in a manufacturing facility or the like to perform some industrial process, para. 32), and wherein the state value collection processing and the anomaly detection processing are capable of being arranged both in the program of a processing resource among the plurality of processing resources and in the programs of different processing resources among the plurality of processing resources (each source may include any type of component that may be used to access (refer to the ability to monitor, control, configured and/or obtain information, para. 37). It would have been obvious to modify the system of Arscott et al. by adding Hartman industrial dynamic anomaly detection. A person of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to make the modification because it would aid in facilitating control, monitoring and configuration of various industrial control devices arranged in a manufacturing facility or the like to perform some industrial process (para. 32-33). In regard to claim 2, Arscott et al. teach the industrial control system according to claim 1, wherein the anomaly detection processing generates a determination result indicating whether an anomaly has occurred in the detection target based on the value indicating the possibility that an anomaly has occurred in the detection target (built in diagnostic self-test sites inside each virtual instance, para. 72-73). In regard to claim 6, Arscott et al. teach the industrial control system according to claim1, further comprising a support device including a memory storing a support program and a computer that accesses the memory and execute the support program (CPU load and memory usage of the virtual instance, para. 40-42, data division and service manager module provides a process for interfacing the virtual instances to management station, para. 22, 31-32) to cause the computer to determine a processing resource of the plurality of processing resources to be an arrangement destination of each of the state value collection processing and the anomaly detect processing (web server operating as the control interface can be configured to require each tenant for credentials to manage the virtual instances through the control interfaces 302, 306, para. 38-40). In regard to claim 7, Arscott et al. teach the industrial control system according to claim 6, wherein the computer executes the support program to determine the arrangement destination of each of the state value collection processing and the anomaly detection processing based on at least one of a number of state values to be collected by the state value collection processing, a collection destination of the state values, a specification of the plurality of processing resources, a load factor of an internal bus, or a load factor of a network (test division of the instance interface 306 can be configured to query the virtualization software for certain parameters related to a specific instance … CPU load and memory usage, para. 42-43). In regard to claim 8, Arscott et al. teach the industrial control system according to claim 6, wherein the computer executes the support program to transmit necessary data to a processing resource among the plurality of processing resources in which the state value collection processing and the anomaly detection processing are to be arranged (the external controller can be configured to send certain queries and instructions to the virtualization software, para. 41-42). In regard to claim 9, Arscott et al. teach a support device in an industrial control system configured to control a manufacturing device and a production line as control targets in the industrial control system, the industrial control system comprising: the plurality of processing resources available for execution of arithmetic processing (plurality of virtual instances, para. 20), each of the plurality of processing resources comprising a memory storing a program and a processor configured to access the memory and execute the program (CPU load and memory usage of the virtual instance, para. 40-42, data division and service manager module provides a process for interfacing the virtual instances to management station, para. 22, 31-32), the plurality of processing resources being configured to perform at least: state value collection processing that collects one or more state values in the industrial control system (data division can be used as a cache to store test result, fig. 3, para. 32-38, 50), and anomaly detection processing that calculates a value indicating a possibility that an anomaly has occurred in a detection target included in the control targets based on a feature value calculated from the one or more state values having been collected (service manager, fig. 3, para. 21-22, 66), and wherein the support device includes a memory storing a support program and a computer that accesses the memory and executes the support program (CPU load and memory usage of the virtual instance, para. 40-42, data division and service manager module provides a process for interfacing the virtual instances to management station, para. 22, 31-32) to cause the computer to provide a user interface configured to support determination of a processing resource among the plurality of resources to be an arrangement destination of each of the state value collection processing and the anomaly detection processing (web server operating as the control interface can be configured to require each tenant for credentials to manage the virtual instances through the control interfaces 302, 306, para. 38-40 The external controller may include a graphical user interface that can be used to monitor test data in real-time, para. 50, 66-70). Arscott et al. does not explicitly teach but Hartman teaches state values of a manufacturing device and a production line as control targets (industrial control devices are arrange in a manufacturing facility or the like to perform some industrial process, para. 32), and wherein the state value collection processing and the anomaly detection processing are capable of being arranged both in the program of a processing resource among the plurality of processing resources and in the programs of different processing resources among the plurality of processing resources (each source may include any type of component that may be used to access (refer to the ability to monitor, control, configured and/or obtain information, para. 37). Refer to claim 1 for motivation statement. In regard to claim 10, Arscott et al. teach a non-transitory storage medium storing thereon a support program used in an industrial control system configured to control a manufacturing device and a production line as control targets in the industrial control system, wherein: the control system comprises a plurality of processing resources available for execution of arithmetic processing (plurality of virtual instances, para. 20), each of the plurality of processing resources comprising a memory storing a program and a processor configured to access the memory and execute the program (CPU load and memory usage of the virtual instance, para. 40-42, data division and service manager module provides a process for interfacing the virtual instances to management station, para. 22, 31-32), and the plurality of processing resources are configured to perform at least: state value collection processing that collects one or more state values in the industrial control system (data division can be used as a cache to store test result, fig. 3, para. 32-38, 50), and anomaly detection processing that calculates a value indicating a possibility that an anomaly has occurred in a detection target included in the control targets based on a feature value calculated from the one or more state values having been collected (service manager, fig. 3, para. 21-22, 66), and wherein the support program when executed by a computer of a support device (CPU load and memory usage of the virtual instance, para. 40-42, data division and service manager module provides a process for interfacing the virtual instances to management station, para. 22, 31-32), causes the computer, to provide a user interface configured to support determination of a processing resource among the plurality of resources to be an arrangement destination of each of the state value collection processing and the anomaly detection processing (web server operating as the control interface can be configured to require each tenant for credentials to manage the virtual instances through the control interfaces 302, 306, para. 38-40 The external controller may include a graphical user interface that can be used to monitor test data in real-time, para. 50, 66-70). Arscott et al. does not explicitly teach but Hartman teaches state values of a manufacturing device and a production line as control targets (industrial control devices are arrange in a manufacturing facility or the like to perform some industrial process, para. 32), and wherein the state value collection processing and the anomaly detection processing are capable of being arranged both in the program of a processing resource among the plurality of processing resources and in the programs of different processing resources among the plurality of processing resources (each source may include any type of component that may be used to access (refer to the ability to monitor, control, configured and/or obtain information, para. 37). Refer to claim 1 for motivation statement. In regard to claim 11, Arscott et al. teach the support device according to claim 9, wherein the computer executes the support program to cause the computer to determine the arrangement destination of each of the state value collection processing and the anomaly detection processing based on at least one of a number of state values to be collected by the state value collection processing, a collection destination of the state values, a specification of the plurality of processing resources, a load factor of an internal bus, or a load factor of a network (test division of the instance interface 306 can be configured to query the virtualization software for certain parameters related to a specific instance … CPU load and memory usage, para. 42-43). In regard to claim 12, Arscott et al. teach the support device according to claim 11, wherein the computer executes the support program to cause the computer to transmit necessary data to a processing resource among the plurality of processing resources in which the state value collection processing and the anomaly detection processing are to be arranged (the external controller can be configured to send certain queries and instructions to the virtualization software, para. 41-42). In regard to claim 13, Arscott et al. teach the support device according to claim 11, wherein the anomaly detection processing generates a determination result indicating whether an anomaly has occurred in the detection target based on the value indicating the possibility that an anomaly has occurred in the detection target (built in diagnostic self-test sites inside each virtual instance, para. 72-73). In regard to claim 14, Arscott et al. teach the non-transitory storage medium according to claim 10, wherein the support program when executed by the computer further causes the computer to determine the arrangement destination of each of the collection processing and the anomaly detection processing based on at least one of a number of state values to be collected by the state value collection processing, a collection destination of the state values, a specification of the plurality of processing resources, a load factor of an internal bus, or a load factor of a network (test division of the instance interface 306 can be configured to query the virtualization software for certain parameters related to a specific instance … CPU load and memory usage, para. 42-43). In regard to claim 15, Arscott et al. teach the non-transitory storage medium according to claim 14, wherein the support program when executed by the computer further causes the computer to transmit necessary data to a processing resource among the plurality of processing resources in which the state value collection processing and the anomaly detection processing are to be arranged (the external controller can be configured to send certain queries and instructions to the virtualization software, para. 41-42). In regard to claim 16, Arscott et al. teach the non-transitory storage medium according to claim 14, wherein the anomaly detection processing generates a determination result indicating whether an anomaly has occurred in the detection target based on the value indicating the possibility that an anomaly has occurred in the detection target (built in diagnostic self-test sites inside each virtual instance, para. 72-73). ************************** Claims 3-5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Arscott et al. (US 2012/0167078) in further view of Hartman (US 2006/0236374) in further view of Boyle et al. (US 9,204,329). In regard to claim 3, Arscott et al. and Hartman does not explicitly teach the industrial control system according to claim 2, wherein the state value collection processing and the anomaly detection processing are arranged in different processing resources, and the anomaly detection processing transmits the determination result having been generated to the processing resource in which the state value collection processing is arranged. Boyle et al. teach of a configuration of nodes where the data nodes (DN) collect data from the RAN transparently. These devices may be deployed as monitoring devices in a physical tap mode or as monitoring devices on mirrored ports (col. 6 lines 33-45). The Analytics and Report Node (ARN) (col. 8 lines 1-53). The current invention identifies the possible causes for such anomalies by running regression analysis on a recent time window of collected data, predicting the onset of such anomalies when similar conditions and controlling the specific causes, or propagating a consolidated set of actions to an extern device in the operator network (col. 9 lines 40-67). The current invention identifies storing the correlated data from multiple protocols in unstructured form to retain the majority of the information that is envisioned to be needed, running reduction methods on portions of distributed data (inter-related protocol data from different network elements), and running additional reduction methods supplied by Analysis and Reporting Node (ARN) on a demand basis at the data collection points (DNs) (col. 2 lines 63-67 and col. 3 lines 1-6). It would have been obvious to modify the system of Arscott et al. and Hartman by adding Boyle et al. distributed RAN information collection, consolidation and analytics. A person of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to make the modification because it would aid in identifies the possible causes for such anomalies by running regression analysis on a recent time window of collected data, predicting the onset of such anomalies when similar conditions and controlling the specific causes, or propagating a consolidated set of actions to an extern device in the operator network (col. 9 lines 40-67). In regard to claim 4, Arscott et al. and Hartman does not explicitly teach the industrial control system according to claim1, wherein the state value collection processing and the anomaly detection processing are arranged in different processing resources, and the state value collection processing transmits the one or more state values having been collected to the processing resource in which the anomaly detection processing is arranged. Boyle et al. teach of a configuration of nodes where the data nodes (DN) collect data from the RAN transparently. These devices may be deployed as monitoring devices in a physical tap mode or as monitoring devices on mirrored ports (col. 6 lines 33-45). The Analytics and Report Node (ARN) (col. 8 lines 1-53). The current invention identifies the possible causes for such anomalies by running regression analysis on a recent time window of collected data, predicting the onset of such anomalies when similar conditions and controlling the specific causes, or propagating a consolidated set of actions to an extern device in the operator network (col. 9 lines 40-67). The current invention identifies storing the correlated data from multiple protocols in unstructured form to retain the majority of the information that is envisioned to be needed, running reduction methods on portions of distributed data (inter-related protocol data from different network elements), and running additional reduction methods supplied by Analysis and Reporting Node (ARN) on a demand basis at the data collection points (DNs) (col. 2 lines 63-67 and col. 3 lines 1-6). Refer to claim 3 for motivational statement. In regard to claim 5, Arscott et al. and Hartman does not explicitly teach the industrial control system according to claim1, wherein the state value collection processing and the anomaly detection processing are arranged in different processing resources, and the anomaly detection processing transmits the value having been calculated and indicating the possibility that an anomaly has occurred in the detection target to the processing resource in which the state value collection processing is arranged. Boyle et al. teach of a configuration of nodes where the data nodes (DN) collect data from the RAN transparently. These devices may be deployed as monitoring devices in a physical tap mode or as monitoring devices on mirrored ports (col. 6 lines 33-45). The Analytics and Report Node (ARN) (col. 8 lines 1-53). The current invention identifies the possible causes for such anomalies by running regression analysis on a recent time window of collected data, predicting the onset of such anomalies when similar conditions and controlling the specific causes, or propagating a consolidated set of actions to an extern device in the operator network (col. 9 lines 40-67). The current invention identifies storing the correlated data from multiple protocols in unstructured form to retain the majority of the information that is envisioned to be needed, running reduction methods on portions of distributed data (inter-related protocol data from different network elements), and running additional reduction methods supplied by Analysis and Reporting Node (ARN) on a demand basis at the data collection points (DNs) (col. 2 lines 63-67 and col. 3 lines 1-6). Refer to claim 3 for motivational statement. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See PTO 892. Brankner (US 2005/0198602) anomalies detection for the planning and control of manufacturing operations Scherrer et al. (US 2003/0236652) anomaly detection Lin et al (US 6,091,846) anomalies detection on manufacturing device Ramle et al. (US 12,181,444) detection of a position anomaly of the test object Kawai et al. (US 11,783,063) control device ********* Boyle et al. (US 9,204,329) information collection and analytics Bisht et al. (US 11,457,031) collect information associated with anomaly in computer network Hedger (US 8,194,238) distribution system with monitoring sensors and determining locations of anomalies Gnanasambandam et al. (US 2009/0300215) monitoring the data to detects anomaly Bajpay et al. (US 2009/0182812) UI display collected data Kube et al. (US 2012/0173931) detect anomalies Leung et al. (US 2014/0040174) anomalies detection in cloud Bouta et al. (US 2016/0026520) detecting data anomalies from streaming data source Rawat et al. (US 2016/0092288) nodes reports each other’s health and report anomalies 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 extension fee 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 date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to LOAN TRUONG whose telephone number is 408-918-7552. The examiner can normally be reached on 10AM-6PM PST M-F. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, Applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matt Kim can be reached on 571-272-4182. 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. /Loan L.T. Truong/Primary Examiner, Art Unit 2114 Loan.truong@uspto.gov
Read full office action

Prosecution Timeline

Oct 29, 2021
Application Filed
Aug 25, 2024
Non-Final Rejection — §101, §103, §112
Oct 18, 2024
Interview Requested
Nov 06, 2024
Applicant Interview (Telephonic)
Nov 07, 2024
Examiner Interview Summary
Nov 14, 2024
Response Filed
Feb 22, 2025
Final Rejection — §101, §103, §112
May 12, 2025
Interview Requested
May 19, 2025
Examiner Interview Summary
May 19, 2025
Applicant Interview (Telephonic)
May 27, 2025
Request for Continued Examination
May 29, 2025
Response after Non-Final Action
Dec 17, 2025
Non-Final Rejection — §101, §103, §112 (current)

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Prosecution Projections

3-4
Expected OA Rounds
77%
Grant Probability
90%
With Interview (+12.8%)
3y 4m
Median Time to Grant
High
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