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 .
This communication is in response to Applicant’s Arguments/Remarks filed 6/30/2026 regarding application 19/143,767 filed on 6/26/2025. Claims 1, 5, and 7 are amended and hereby entered. Claims 8-14 are added and hereby entered. No claims are allowed.
Response to Arguments
Applicant's arguments filed 6/30/2026 are fully considered but they are not persuasive.
Regarding 35 USC 101:
The applicant submits the amended limitations overcome the rejection under 35 USC 101 by reciting integration into practical application. However, the circuitry collecting operational data of a diagnostic target device does not describe a practical application. The additional element of circuitry describes a general-purpose computer that performs collecting, acquiring, or storing operational data which falls under MPEP 2106.05(f). The additional element merely acts as a tool to perform the abstract idea. Therefore, the examiner respectfully disagrees and the rejection is maintained.
Regarding 35 USC 102/103:
The applicant’s amendments necessitate new grounds for rejection, rendering applicant’s arguments regarding 35 USC 102 moot.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-14 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 1 and 7 recite “circuitry that causes operation of a diagnostic target device” and “circuitry that causes operation of the diagnostic target device after maintenance”. This limitation can be interpreted as a computer that operates a piece of equipment being diagnosed for maintenance. Nowhere does the specification describe a computer or circuitry that controls the actual operation of the equipment itself. Rather the specification describes a computer that controls the collection/acquisition and storage of operation information of a device/equipment being diagnosed for maintenance, (i.e. the instant application specification describes a computer acquiring and storing operation data, not a computer that operates a machine being inspected for maintenance). Therefore, the specification fails to comply with the written description requirement. For the purposes of compact prosecution, the claim is interpreted to mean the circuitry or computer responsible for collecting/acquiring or storing the operation data.
Claims 2-6 and 8-14 are rejected due to their dependency on Claims 1 and 7.
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 1-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) with no practical application and without significantly more.
The claimed invention is directed to an abstract idea in that the instant application is directed to a mental process (See MPEP 2106.04(a)(2)(III)). The independent claims (1 and 7) recite a method and systems to evaluate maintenance data to make maintenance recommendations and estimate defective components. These claim elements are being interpreted as concepts performed in the human mind (including observation, evaluation, judgement, and opinion). Using past data evaluate maintenance needs can equivalently be achieved by human observation and evaluation of the information. The claims recite an abstract idea consistent with the “mental process” grouping set forth in the MPEP 2106.04(a)(2)(III).
The instant application fails to integrate the judicial exception into a practical application because the instant application merely recites an “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea. The instant application is directed towards a method and systems to implement the identified abstract idea of receiving information, processing information, and displaying the result of the analysis (i.e. processing maintenance records and historical information to estimate defective components and the like) in a general computer environment. The claims do not include additional elements that amount to significantly more than the judicial exception. The independent claims recite the additional elements “circuitry”. These claim elements are recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a general computer environment. The machines merely act as a modality to implement the abstract idea and are not indicative of integration into a practical application (i.e., the additional elements are simply used as a tool to perform the abstract idea), see MPEP 2106.05(f).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed in Step 2A Prong Two analysis, the additional elements in the claims amount to no more than mere instructions to apply the exception using generic computer components. The same analysis applies here in 2B and does not provide an inventive concept.
In regards to the dependent claims
Regarding Claim 2 and 9, the additional element “a defective component detection model” is introduced. However, the model is recited at a high level of generality and acts as a modality to implement the abstract idea. It is not indicative of integration into practical application or significantly more (i.e. the additional element is simply used as a tool to perform the abstract idea), see MPEP 2106.05(f).
Regarding Claim 4 and 11, the additional element “maintenance terminal” is introduced. However, the claim element is recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a general computer environment. The machine merely acts as a modality to implement the abstract idea and is not indicative of integration into a practical application or significantly more (i.e., the additional elements are simply used as a tool to perform the abstract idea), see MPEP 2106.05(f).
Regarding Claims 3 and 5-6, 8, 10, 12-14 the claims introduce no new additional elements or new abstract ideas and do not impact analysis under 35 USC 101.
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 1-2, 5-9, and 12-14 are rejected under 35 U.S.C. 103 as being unpatentable over Katahata (US 20210326600 A1) in view of Procter (US 20160148172 A1)
Regarding Claims 1 and 7, (substantially similar in scope and language), Katahata teaches:
A maintenance assistance system comprising: circuitry that causes operation of a diagnostic target device and collects operation data of the diagnostic target device from the operation of the diagnostic target device [see at least Katahata: (Para 0059) “The information management device 10 is connected to the control device 3, the imaging device 4, and the operation terminal 5 provided in the manufacturing equipment 1 in a wired or wireless manner, and may acquire data from each device”, (Para 0065) “The equipment data acquisition unit 21 acquires data regarding equipment configuring the manufacturing line 2 from the control device 3 during an operation of the manufacturing line 2, and stores the data into the equipment data storage unit 41. The equipment data acquisition unit 21 acquires data regarding the equipment configuring the manufacturing line 2 from the control device 3 during maintenance work for the manufacturing line 2, and stores the data into the equipment data storage unit 41”]
maintenance record information storage circuitry configured to store maintenance record information obtained by diagnosing a diagnostic target device in a past, the maintenance record information including data of a plurality of data items, and defective component information; [see at least Katahata: (Para 0019) “According to the information management device (5), the history data and each piece of the maintenance work process data corresponding to the history data are stored as the second data in the second data storage unit in association with each other”, (Para 0022) “the second data includes history data of at least one of setting data and measured data for the equipment encompassing before and after the maintenance work as the data regarding the equipment, and includes operation transition data for an operation part operated by a maintenance person as the maintenance behavior data. The history data and the operation transition data corresponding to the history data are stored in the second data storage unit in association with each other”, (Para 0068) “The first data storage unit 44 stores equipment data up to the occurrence of an event, acquired from the control device 3 during the operation of the manufacturing line 2 among the pieces of equipment data stored in the equipment data storage unit 41. The event refers to an event such as an error or a defect occurring during the operation of the manufacturing line 2, requiring subsequent maintenance work such as an inspection or repair”]
importance degree learning circuitry configured to divide the maintenance record information stored in the maintenance record information storage circuitry according to a division condition of a plurality of predetermined division conditions predetermined based on a data item of the plurality of data items, [see at least Katahata: (Para 0074) “The event information generation unit 24 classifies the event on the basis of the first data stored in the first data storage unit 44, and generates event information in which the classified event (i.e., an event which has been classified) is associated with the first data”, (Para 0075) “Regarding the setting of the first label, the maintenance person 7 may set an identification label for a classified event via the operation part 50, or an identification label may be automatically set for a classified event.”]
to learn a relationship between the data item and a defective component in the maintenance record information for each division condition of the plurality of predetermined division conditions, [see at least Katahata: (Para 0015) “Therefore, it is possible to classify the event finely in accordance with a relationship between the operation behavior of the worker and the change in the data regarding the equipment up to the occurrence of the event”]
and to generate a degree of importance of the data item for each division condition using both the operation data collected from the diagnostic target device in the past maintenance record information; [see at least Katahata: (Para 0099) “The degree of abnormality may be a determination value (that is, a determination value for the presence or absence of abnormality) indicating whether or not an operation behavior different from the normal operation behavior has been detected, may be calculated on the basis of a weight of a detected operation behavior by adding the weight to a content of an operation behavior different from the normal operation behavior in advance, may be calculated on the basis of the number of operation behaviors different from the normal operation behavior, or may be calculated on the basis of a time at which an operation behavior different from the normal operation behavior is performed”, (Figures 6-8), (Para 0022) “According to the information management device (7) related to the present disclosure, in any one of the information management devices (1) to (4), the second data includes history data of at least one of setting data and measured data for the equipment encompassing before and after the maintenance work as the data regarding the equipment, and includes operation transition data for an operation part operated by a maintenance person as the maintenance behavior data. The history data and the operation transition data corresponding to the history data are stored in the second data storage unit in association with each other”]
similar case extraction circuitry configured to classify, in a classification, diagnostic data for diagnosing the diagnostic target device to be diagnosed according to the division condition and to extract a similar case similar to the diagnostic data from the maintenance record information storage circuitry based on a degree of importance of the data item corresponding to the classification; [see at least Katahata: (Para 0148) “The control unit 20 may compare the degree of abnormality of a work behavior of the worker 6 and a change in equipment data before and after the occurrence of the detected event with the degree of abnormality of a work behavior and a change in the equipment data in each classified event of the event information, extract a classified event indicating the same or approximate degree of abnormality and the same or approximate change from the pieces of event information, and estimate the extracted classified event as the similar event. The control unit 20 performs the similar event estimation process, and then causes the process to proceed to step S44”]
defective component estimation circuitry configured to estimate a defective component of the diagnostic target device based on the similar case extracted by the similar case extraction circuitry; and [see at least Katahata: (Para 0026), “a maintenance candidate selection unit that selects a maintenance work candidate corresponding to the similar event estimated by the similar event estimation unit from among pieces of the maintenance information stored in the maintenance information storage unit”, (Para 0054) “ The event in the present embodiment is an event requiring maintenance of equipment, such as an error or a defect that may influence an operation of the equipment”, (Para 0063) “a similar event estimation unit 32, a maintenance candidate selection unit 33, and a maintenance information output unit”]
circuitry that causes operation of the diagnostic target device after maintenance according to the estimated defective component and collects the operation data of the diagnostic target device after the maintenance [see at least Katahata: (Para 0059) “The information management device 10 is connected to the control device 3, the imaging device 4, and the operation terminal 5 provided in the manufacturing equipment 1 in a wired or wireless manner, and may acquire data from each device”, (Para 0065) “The equipment data acquisition unit 21 acquires data regarding equipment configuring the manufacturing line 2 from the control device 3 during an operation of the manufacturing line 2, and stores the data into the equipment data storage unit 41. The equipment data acquisition unit 21 acquires data regarding the equipment configuring the manufacturing line 2 from the control device 3 during maintenance work for the manufacturing line 2, and stores the data into the equipment data storage unit 41”]
However, Katahata does not teach but Procter does teach:
the division condition being one regionality of a plurality of different regionalities that have respective different regional failure tendencies, [see at least Procter: (Para 0009) “Lifecycle information, for the purposes of this specification, is taken to include deployment information for an AtoN asset, as well as maintenance records for the AtoN asset. By way of example, the lifecycle information may include: [0010] (i) a current location of the AtoN asset”, (Para 0109) “Such information may include average product lifespans and/or failure rates, costs associated with maintenance and spare parts, possible correlations between geographic location (temperature, weather conditions, etc.) and product performance or cost of ownership”]
Further, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the maintenance assistance system/method (Katahata) with the incorporation of regional considerations in maintenance (Procter). One of ordinary skill in the art would have recognized the benefits of taking into account location when analyzing maintenance of equipment to account for regional differences. See at least paragraphs 108-109 of Procter, “Owners/operators of marine AtoN systems, will have a single source of truth for all AtoN-related asset information and lifecycle data (service histories, parts replacement, lifetime cost, etc.). This will allow detailed information and reporting on key asset metrics; in particular, this will support budgeting and operational forecasts for servicing, maintenance, spare parts and device replacement. Such information may include average product lifespans and/or failure rates, costs associated with maintenance and spare parts, possible correlations between geographic location (temperature, weather conditions, etc.) and product performance or cost of ownership”. Applying a known technique to known device ready for improvement would have yielded predictable results to one of ordinary skill.
Regarding Claim 2 and 9, the combination of Katahata and Procter teach the limitations of claim 1, Katahata further teaches:
The maintenance assistance system according to Claim 1, further comprising: model learning circuitry configured to learn the maintenance record information as learning data and to generate a defective component detection model that estimates the defective component from the similar case, wherein the defective component estimation circuitry estimates the defective component from the similar case, using the defective component detection model. [see at least Katahata: (Para 0079) “In a case where the similar event corresponding to the detected event has not been able to be estimated among the pieces of event information by the similar event estimation unit 32, the present detected event and the first data up to the occurrence of the detected event may be stored into the first data storage unit 44, and new event information may be generated”, (Para 0080) “The maintenance candidate selection unit 33 selects a maintenance work candidate corresponding to the similar event estimated by the similar event estimation unit 32 from among the pieces of maintenance information stored in the maintenance information storage unit 46”, (Para 0027) “According to the information management device (9), in a case where the event is detected, the similar event that is similar to the detected event is estimated among the pieces of event information (that is, among the classified events) generated by the event information generation unit, and thus it is possible to estimate the detected event with high accuracy. The maintenance work candidate corresponding to the similar event is selected from among the pieces of maintenance information stored in the maintenance information storage unit, and information regarding the maintenance work candidate is output”]
Regarding Claim 5 and 12, The combination of Katahata and Procter teach the limitations of claim 2, Katahata further teaches:
The maintenance assistance system according to Claim 2, wherein the importance degree learning circuitry generates the degree of importance of the data item for each division condition, [see at least Katahata: (Figures 4, 5, 7), (Para 0099) “The degree of abnormality may be a determination value (that is, a determination value for the presence or absence of abnormality) indicating whether or not an operation behavior different from the normal operation behavior has been detected, may be calculated on the basis of a weight of a detected operation behavior by adding the weight to a content of an operation behavior different from the normal operation behavior in advance, may be calculated on the basis of the number of operation behaviors different from the normal operation behavior, or may be calculated on the basis of a time at which an operation behavior different from the normal operation behavior is performed.”]
using the learning data including both the operation data of the diagnostic target device collected from the diagnostic target device in the past and the maintenance record information, and [see at least Katahata: (Figure 8), (Para 107) “FIG. 8 illustrates an example of an example of a relationship between histories of setting data and measured data for the equipment and a maintenance work process until the manufacturing line 2 returns to a recovery state after the defect F3 as an event occurs in the manufacturing line 2 and then maintenance work is performed”]
the model learning circuitry generates the defective component detection model, using the learning data including both the operation data of the diagnostic target device and the maintenance record information. [see at least Katahata: (Para 0078) “The event detection unit 31 detects that an event has occurred in the manufacturing line 2 on the basis of, for example, equipment data acquired from the control device 3 during the operation of the manufacturing line 2. In a case where the event has been detected by the event detection unit 31, the similar event estimation unit 32 estimates a similar event that is similar to (that is, the same as or most similar to) the detected event from among pieces of event information generated by the event information generation unit”, (Para 0080) “The maintenance candidate selection unit 33 selects a maintenance work candidate corresponding to the similar event estimated by the similar event estimation unit 32 from among the pieces of maintenance information stored in the maintenance information storage unit 46”]
Regarding Claim 6 and 13, the combination of Katahata and Procter teach the limitations of Claim 1, Katahata further teaches:
The maintenance assistance system according to Claim 1, wherein the importance degree learning circuitry divides the maintenance record information according to an area in which the diagnostic target device is installed and generates the degree of importance of the data item for each area, and [see at least Katahata: (Figure 7)]
the similar case extraction circuitry classifies the diagnostic data according to the area and extracts the similar case based on the degree of importance of the data item corresponding to the classified area. [see at least Katahata: (Para 0148) “The control unit 20 may compare the degree of abnormality of a work behavior of the worker 6 and a change in equipment data before and after the occurrence of the detected event with the degree of abnormality of a work behavior and a change in the equipment data in each classified event of the event information, extract a classified event indicating the same or approximate degree of abnormality and the same or approximate change from the pieces of event information, and estimate the extracted classified event as the similar event. The control unit 20 performs the similar event estimation process, and then causes the process to proceed to step S44”]
Regarding Claim 8 and 14, the combination of Katahata and Procter teach the limitations of claim 1. Katahata further teaches:
The maintenance assistance system according to Claim 1, wherein the diagnostic target device is an air conditioner configured to communicate the operation data via a network. [The diagnostic target device being an air conditioner recites nonfunctional descriptive material that does not carry patentable weight in the claims.]
Claims 3-4 and 10-11 are rejected under 35 U.S.C. 103 as being unpatentable over Katahata (US 20210326600 A1), in view of Procter (US 20160148172 A1), in further view of Ueki (US 12406190 B2).
Regarding Claim 3 and 10, the combination of Katahata and Procter teaches the limitations of claim 2, Katahata further teaches:
The maintenance assistance system according to Claim 2, further comprising: output information generation circuitry configured to generate output information based on an estimation result estimated by the defective component estimation circuitry [see at least Katahata: (Para 0081) “The maintenance information output unit 34 outputs information regarding the maintenance work candidate selected by the maintenance candidate selection unit 33 to the display device 51, and thus information regarding maintenance work corresponding to the detected event is displayed on a screen of the display device 51”]
wherein the similar case extraction circuitry extracts a plurality of the similar cases, [(Para 0080) “The maintenance candidate selection unit 33 selects a maintenance work candidate corresponding to the similar event estimated by the similar event estimation unit 32 from among the pieces of maintenance information stored in the maintenance information storage unit 46.”]
While the combination of Katahata and Procter teach a maintenance assistance system, it does not teach but Ueki does teach:
the defective component estimation circuitry estimates the defective component and a failure probability for each of the plurality of the similar cases, using the defective component detection model, and [see at least Ueki: (Column 2, Lines 25-31) “In order to solve the above-mentioned problem, in the invention, “a failure probability evaluation system, which evaluates a failure of a component of each mechanical system in a mechanical system group including a plurality of mechanical systems, includes a failure history database for accumulating past failure history data about the mechanical system”, (Column 2, Lines 42-48) “The invention also relates to a “failure probability evaluation method, which evaluates a failure of a component of each mechanical system for a mechanical system group including a plurality of mechanical systems, includes calculating a failure rate function of the mechanical system by statistical processing based on past failure history data for the mechanical system” ]
the output information generation circuitry calculates an average value of the failure probabilities for the defective components in the plurality of the similar cases, [see at least Ueki: (Column 10, Lines 48-57) “The invention does not impose any limitation on the specific prediction method, but at least it is necessary to individually predict each individual. Specifically, the estimated value of the time-series operation data D2 for each individual until an arbitrary time has elapsed is acquired by some method. The simplest method is to make an assumption that the average value of the time-series operation data D2 recorded up to the present time will continue in the future, which is equivalent to simply extrapolating the trend of cumulative damage amount up to the present time.”]
selects a specific number of candidates for the defective components in descending order of the average value of the failure probabilities, and generates the output information including the selected candidates for the defective components. [see at least Ueki: (Figure 9) (Column 12, lines 17-25) “Next, in the single machine view of FIG. 9, when an arbitrary wind power generator 1 is selected from a map 30 illustrating the installation location of the wind power generator or the wind power generator list 31, the failure probability F after the present and arbitrary period is displayed as a graph 32 with respect to a component for evaluation. This can be expected to have the effect of easily confirming a component with a high risk of failure in the target machine”]
Further, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the maintenance assistance system (Katahata and Procter) with a defective component failure probability (Ueki). One of ordinary skill would have recognized the benefits of determining a quantifiable failure probability in a maintenance assistance system to better predict when and what components need maintenance. The combination of the maintenance system and failure probability would have yielded predictable results to one of ordinary skill in the art.
Regarding Claim 4 and 11, the combination of Katahata, Procter, and Ueki teaches the limitations of claim 3, Katahata further teaches:
The maintenance assistance system according Claim 3, wherein the similar case extraction circuitry extracts the similar case similar to the diagnostic data received from a maintenance terminal, and [(Para 0080) “The maintenance candidate selection unit 33 selects a maintenance work candidate corresponding to the similar event estimated by the similar event estimation unit 32 from among the pieces of maintenance information stored in the maintenance information storage unit 46.”]
the output information generation circuitry generates the output information including the selected candidates for the defective components [see at least Katahata: (Para 0081) “The maintenance information output unit 34 outputs information regarding the maintenance work candidate selected by the maintenance candidate selection unit 33 to the display device 51, and thus information regarding maintenance work corresponding to the detected event is displayed on a screen of the display device 51”]
While the combination of Katahata and Procter teaches a maintenance assistance system, it does not teach but Ueki does teach:
and the average value of the failure probabilities and transmits the generated output information to the maintenance terminal. [see at least Ueki: (Column 10, Lines 48-57) “The invention does not impose any limitation on the specific prediction method, but at least it is necessary to individually predict each individual. Specifically, the estimated value of the time-series operation data D2 for each individual until an arbitrary time has elapsed is acquired by some method. The simplest method is to make an assumption that the average value of the time-series operation data D2 recorded up to the present time will continue in the future, which is equivalent to simply extrapolating the trend of cumulative damage amount up to the present time”, (Figure 9), (Column 12, lines 17-25) “Next, in the single machine view of FIG. 9, when an arbitrary wind power generator 1 is selected from a map 30 illustrating the installation location of the wind power generator or the wind power generator list 31, the failure probability F after the present and arbitrary period is displayed as a graph 32 with respect to a component for evaluation. This can be expected to have the effect of easily confirming a component with a high risk of failure in the target machine”]
Further, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the maintenance assistance system (Katahata and Procter) with an average failure probability (Ueki). One of ordinary skill would have recognized the benefits of determining an average failure probability in a maintenance assistance system to better predict future values of when and what components need maintenance. See Ueki Column 10, Lines 53-56, “The simplest method is to make an assumption that the average value of the time-series operation data D2 recorded up to the present time will continue in the future”. Applying a known technique to a known device ready for improvement would have yielded predictable results to one of ordinary skill.
Conclusion
Pertinent art not relied upon:
Davenport (US 9299046 B2), Infrastructure Asset Management: Discusses the use of maintenance prediction data with geographical considerations regarding preventative maintenance
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 Examiner Benjamin Truong, whose telephone number is 703-756-5883. The examiner can normally be reached on Monday-Friday from 9 am to 5 pm (EST).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Nathan Uber SPE can be reached on 571-270-3923. 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.
/B.L.T. /Examiner, Art Unit 3687
/NATHAN C UBER/Supervisory Patent Examiner, Art Unit 3626
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