Prosecution Insights
Last updated: April 19, 2026
Application No. 18/545,158

SHOVEL MANAGEMENT SYSTEM AND SHOVEL MANAGEMENT APPARATUS

Final Rejection §103§112
Filed
Dec 19, 2023
Examiner
KWIATKOWSKA, LIDIA
Art Unit
3666
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Sumitomo Heavy Industries, Ltd.
OA Round
2 (Final)
70%
Grant Probability
Favorable
3-4
OA Rounds
3y 4m
To Grant
86%
With Interview

Examiner Intelligence

Grants 70% — above average
70%
Career Allow Rate
40 granted / 57 resolved
+18.2% vs TC avg
Strong +16% interview lift
Without
With
+15.5%
Interview Lift
resolved cases with interview
Typical timeline
3y 4m
Avg Prosecution
33 currently pending
Career history
90
Total Applications
across all art units

Statute-Specific Performance

§101
16.9%
-23.1% vs TC avg
§103
60.2%
+20.2% vs TC avg
§102
14.8%
-25.2% vs TC avg
§112
5.9%
-34.1% vs TC avg
Black line = Tech Center average estimate • Based on career data from 57 resolved cases

Office Action

§103 §112
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 . Drawings The drawings were received on January 16th 2024. These drawings are accepted. Priority Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed on January 26th 2024. Status of the Claims This Final action is in response to the applicant’s filing on November 10th 2025. Claims 1-11 are pending and examined below. Response to Arguments Applicant’s amendments with respect to the rejection of claims under 35 USC § 112(f) have been fully considered and are persuasive. Therefore, the rejection of claims under 35 USC § 112(f) has been withdrawn. Applicant’s amendments with respect to the rejection of claims under 35 USC § 103 have been fully considered but are moot. While the Examiner notes that the applicant is arguing the claim limitations recite " … together with the text data converted from the speech data, at least a portion of the extracted failure information including a method of handling the failure… “. Therefore, the rejection has been withdrawn; However, upon further consideration a new ground(s) of rejection is made for Claims 1 and 10 over Iimuro (Patent No. US20230315080A1) in view of Nishi (Patent No. WO2019035427A1) and Koga (Patent No. JP2019007308A). Claim Rejections - 35 USC § 112 The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. Claims 1-9 and 11 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. The limitation in claim 1; “…and cause a display device of the shovel to, together with the text data…at least a portion of the extracted failure…” the examiner believes that the limitation is missing a phrase “display”. Claim must particularly point out and distinctly define the meats and bounds of the subject matter. (MPEP&2171) All claims dependent on independent claim would be rejected under the same reason as above. For the purpose of examination claims 1-9 and 11 are interpreted based on examiner’s best understanding. Appropriate correction is required. 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. The factual inquiries 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 1-11 are rejected under 35 U.S.C. 103 as being unpatentable over Iimuro (Patent No. US20230315080A1) in view of Nishi (Patent No. WO2019035427A1) and Koga (Patent No. JP2019007308A). Regarding claim 1 Iimuro teaches a shovel management system for managing a shovel comprising: the shovel; (See Iimuro paragraph 0044 and 0039; “…The work machine 10 of Example 1 is a hydraulic shove…FIG. 2 illustrates a configuration example of a work machine management system according to Example 1…”); and a memory configured to store one or more pieces of failure information about a failure; (See Iimuro paragraph 0051; “The management server 90 stores failure risk information 91 of the work machines 10 operating at the work site (such as all relevant work machines 10)…”); and a hardware processor coupled to the memory; (See Iimuro paragraph 0047; “The management server 90 may be constructed using a known computer, and comprises, for example, a computing means, a storage means, an input means, and an output means. The computing means includes a processor…”); Iimuro does not teach but Nishi teaches, and configured to convert speech data acquired from the shovel into text data; (See Nishi paragraph 0059; “The voice recognition unit 505 recognizes the voice emitted by the operator of the shovel PS. In the example of FIG. 3A, a speech recognition engine is used to convert speech input through the speech input device 44 into text…”); extract, from the memory …information whose content is similar to the text data; (See Nishi paragraph 0059; “The voice recognition unit 505 recognizes the voice emitted by the operator of the shovel PS. In the example of FIG. 3A, a speech recognition engine is used to convert speech input through the speech input device 44 into text. The speech recognition unit 505 may cause the display device 40 to display a character string representing the recognized speech. This is to make the operator confirm whether the voice emitted by the operator matches the voice recognized by the machine guidance device 50 or not. The speech recognition engine utilizes one or more speech recognition dictionaries to convert input speech into text. The speech recognition dictionary is stored, for example, in the storage device 47. The speech recognition dictionary may be prepared for each dialect such as Kansai dialect, Tohoku dialect or Kyushu dialect. In this case, the voice recognition unit 505 may switch the voice recognition dictionary to be used based on, for example, the current position of the shovel PS detected based on the output of the GPS device D1. For example, when it is determined that the shovel PS is located in the Tohoku region, the speech recognition unit 505 may use a speech recognition dictionary suitable for the Tohoku valve. In addition, the voice recognition unit 505 may be configured to identify a dialect used by the operator based on features (such as accent and intonation) of the input voice. In this case, the speech recognition unit 505 may switch the speech recognition dictionary in accordance with the dialect used by the operator.”). Iimuro and Nishi are in the same field of endeavor of work machine management system and apparatus for. It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to modify Iimuro a shovel management system with Nishi speech to text conversion. No new functionality would arise from the combination and the combination would improve usability of Iimuro by adding a function of speech to text it allows better management of the shovel. Further, finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable. Iimuro does not teach but Koga teaches, and cause a display device of the shovel to together with the text data converted from the speech data, at least a portion of the extracted failure information including a method of handling the failure; (See Koga paragraph 0005, 0075- 0076, 0041, 0046-0048 and 0052; “The state of the excavator when the operator feels uncomfortable may be a sign of failure of the shovel… The controller 30 that executes the audio / text conversion process receives from the speaker attached to the display device 40 a voice such as "which motion feels uncomfortable?", "Voice that is affected by boom"? A message may be output. This is to allow the operator of the shovel to input comments in an interactive manner. The controller 30 that executes the audio / text conversion process receives from the speaker attached to the display device 40 a voice such as "which motion feels uncomfortable?", "Voice that is affected by boom"? A message may be output. This is to allow the operator of the shovel to input comments in an interactive manner… In the case where the voice recognition unit 30 a estimates that the operator feels uncomfortable about the movement of the excavator, the data storage unit 30 b stores the data stored in the volatile memory device 52 during the predetermined period including the estimated time as the reference time Data may be stored in the nonvolatile storage device 53. The same applies to the case where the voice recognition unit 30 a estimates that the operator is satisfied with the movement of the excavator… When it is determined that the predetermined condition concerning speech recognition is satisfied (YES in step ST 1), the controller 30 specifies the range of data to be stored in the nonvolatile storage device 53 (step ST 2). For example, when a negative word is recognized by the voice recognition unit 30 a, the data storage unit 30 b determines that a predetermined condition related to voice recognition has been satisfied. Then, based on the speech point of the negative word, the range of data to be stored in the nonvolatile storage device 53 is specified. For example, the range of data stored in the volatile memory device 52 during the period starting from the point of a predetermined time from the point of utterance as the start point and the point after a predetermined time from the point of utterance as the end point is stored in the nonvolatile storage device 53 As the range of data to be stored. Thereafter, the data storage unit 30 b stores data (hereinafter referred to as "data set") within the specified range in the nonvolatile storage device 53 (step ST 3). For example, the data stored in the volatile storage device 52 is copied to the nonvolatile storage device 53. The data storage unit 30 b may delete the copied data from the data stored in the volatile storage device 52 or overwrite it. Thereafter, the controller 30 determines whether or not a predetermined transmission condition is satisfied (step ST 4). The predetermined transmission condition is a condition to be satisfied when the data stored in the nonvolatile storage device 53 is transmitted to the outside. For example, it is determined that the current time has reached the predetermined time, the elapsed time since the previous transmission time Has reached a predetermined time, that a transmission instruction by manual operation by an operator has been received, and the like… Through the above-described data transmission processing, the controller 30 can transmit the data stored in the volatile storage device 52 to the management device 90 during a predetermined period including a time point at which a negative word is issued, for example. The management device 90 can display the received data on the display unit, thereby presenting the received data to the administrator. By looking at the displayed data, the administrator can analyze the cause of the negative word being generated by the operator of the excavator. The same is true when transmitting data to the support device 94.”). Iimuro and Koga are in the same field of endeavor of work machine management system and apparatus for. It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to modify Iimuro a shovel management system with Koga failure information including a method of handling it. No new functionality would arise from the combination and the combination would improve usability of Iimuro by adding a function of failure information including a method of handling it allows better management of the shovel. Further, finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable. Regarding claim 2 Iimuro in view of Nishi teaches the shovel management system according to claim 1, Iimuro further teaches, wherein the hardware processor is configured to use operation data acquired from the shovel to calculate a degree of abnormality of the shovel;(See Iimuro paragraph 0113;”… the operation information of a work machine having a greater failure risk is given priority over a work machine having a smaller failure risk, so that the operation information can reach the management server 90 more reliably. As a result, the manager can know abnormality in a work machine having a greater failure risk early and take measures.”); and cause the display device of the shovel to display the calculated degree of abnormality together with the information indicating the met od of handling the failure (See Iimuro Figure 3). PNG media_image1.png 784 564 media_image1.png Greyscale Regarding claim 3 Iimuro in view of Nishi teaches the shovel management system according to claim 1, Iimuro further teaches, wherein the hardware processor is configured to cause the display device of the shovel to display information indicating cause of the failure together with the information indicating the method of handling the failure; (See Iimuro Figure 3 and 6-8) PNG media_image2.png 820 554 media_image2.png Greyscale Regarding claim 4 Iimuro in view of Nishi teaches the shovel management system according to claim 2, Iimuro further teaches, wherein the hardware processor is configured to estimate a part in the shovel where the failure has occurred, and cause the display device of the shovel to display information indicating the part where the failure has occurred, together with the information indicating the method of handling the failure; (See Iimuro paragraph 0061;” The vehicle body priority level may be indicated not as a simple order but as a deviation value taking the distribution of the risk evaluation values into consideration. Further, when the vehicle body priority level is determined, it is not necessary to refer to all of the information shown in FIG. 3(a). For example, the management server 90 may determine the vehicle body priority level based on at least one of the failure probability, work importance level, or the availability of replacement machine. In this case, the input interface screen of FIG. 3(b) is used for inputting at least one of the failure probability, work importance level, or the availability of replacement machine.”). Regarding claim 5 Iimuro in view of Nishi teaches the shovel management system according to claim 2, Iimuro further teaches, in a case where the calculated degree of abnormality is greater than or equal to a predetermined threshold value and the speech data is not acquired; (See Iimuro paragraph 0127; “…the work machine 10 itself can function as a relay to expand the range of communication. In this case, too, because the operation information of a work machine having a greater failure risk is given priority over a work machine having a smaller failure risk, the operation information can reach the management server 90 more reliably. As a result, the manager can know abnormality in a work machine having a greater failure risk early, and take measures.”). Iimure does not teach but Nishi teaches, wherein the hardware processor configured to cause the display device of the shovel to display information prompting an input of the speech data; (See Nishi paragraph 0021 and 0059; “The display device 40 displays an image including various work information in accordance with an instruction from the controller 30 or the machine guidance device 50. The display device 40 is, for example, a liquid crystal display connected to the machine guidance device 50… FIG. 3A, a speech recognition engine is used to convert speech input through the speech input device 44 into text. The speech recognition unit 505 may cause the display device 40 to display a character string representing the recognized speech….”). Iimuro and Nishi are in the same field of endeavor of work machine management system and apparatus for. It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to modify Iimuro a shovel management system with Nishi speech to text conversion. No new functionality would arise from the combination and the combination would improve usability of Iimuro by adding a function of speech to text it allows better management of the shovel. Further, finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable. Regarding claim 6 Iimuro in view of Nishi teaches the shovel management system according to claim 2, Iimuro further teaches, in a case where the calculated degree of abnormality is greater than or equal to a predetermined threshold value and the speech data is not acquired a predetermined period of time; (See Iimuro paragraph 0127; “…the work machine 10 itself can function as a relay to expand the range of communication. In this case, too, because the operation information of a work machine having a greater failure risk is given priority over a work machine having a smaller failure risk, the operation information can reach the management server 90 more reliably. As a result, the manager can know abnormality in a work machine having a greater failure risk early, and take measures.”). Iimure does not teach but Nishi teaches, wherein the hardware processor is configured to cause the display device of the shovel to display a questionnaire screen about a state of the shovel; (See Nishi paragraph 00103; “…the setting item by asking a question such as “△?” The machine guidance device 50 can be requested to explain the contents of the above. When such a question is recognized by the voice recognition unit 505, the machine guidance device 50 may display a screen for explaining the content of the setting item, and the voice message regarding the content of the setting item is displayed as the voice output device 43. You may output from.”). Iimuro and Nishi are in the same field of endeavor of work machine management system and apparatus for. It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to modify Iimuro a shovel management system with Nishi speech to text conversion. No new functionality would arise from the combination and the combination would improve usability of Iimuro by adding a function of speech to text it allows better management of the shovel. Further, finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable. Regarding claim 7 Iimuro in view of Nishi teaches the shovel management system according to claim 1, Iimuro does not teach but Nishi teaches, wherein the hardware processor is configured to search the memory, and extract the failure information from the memory based on a similarity between a content of the text data and each of contents of the one or more pieces of failure information stored in the memory; (See Nishi paragraph 0059; “…The speech recognition engine utilizes one or more speech recognition dictionaries to convert input speech into text. The speech recognition dictionary is stored, for example, in the storage device 47. The speech recognition dictionary may be prepared for each dialect such as Kansai dialect, Tohoku dialect or Kyushu dialect. In this case, the voice recognition unit 505 may switch the voice recognition dictionary to be used based on, for example, the current position of the shovel PS detected based on the output of the GPS device D1. For example, when it is determined that the shovel PS is located in the Tohoku region, the speech recognition unit 505 may use a speech recognition dictionary suitable for the Tohoku valve. In addition, the voice recognition unit 505 may be configured to identify a dialect used by the operator based on features (such as accent and intonation) of the input voice. In this case, the speech recognition unit 505 may switch the speech recognition dictionary in accordance with the dialect used by the operator.”). Iimuro and Nishi are in the same field of endeavor of work machine management system and apparatus for. It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to modify Iimuro a shovel management system with Nishi speech to text conversion. No new functionality would arise from the combination and the combination would improve usability of Iimuro by adding a function of speech to text it allows better management of the failure data of the shovel. Further, finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable. Regarding claim 8 Iimuro in view of Nishi teaches the shovel management system according to claim 7, Iimuro further teaches, wherein the hardware processor is configured to send a notification of occurrence of the failure to a terminal associated with a service technician, in a case where an instruction to notify the service technician of the occurrence of the failure is received from the shoves; (See Iimuro paragraph 0110; “In step 905, the retransmission condition of the acquired operation information is confirmed. If the retransmission condition is not satisfied (step 905: YES; for example, when the predetermined number of retransmissions is exceeded, or the predetermined retransmission time-out time is passed), transmission failure is recognized, and the process proceeds to step 906. In step 906, the operation information (more strictly, a corresponding packet) is deleted from the buffer, and a notice of transmission failure is transmitted as a transmission result in step 907 to the relay-requesting work machine 10.”). Regarding claim 9 Iimuro in view of Nishi teaches the shovel management system according to claim 7, Iimuro does not teach but Nishi teaches, wherein the hardware processor causes the display device of the shovel to display an image indicating that a search is in progress while the hardware processor of the management apparatus is searching the memory with the text data; (See Nishi paragraph 00139; “The machine guidance apparatus 50 may display in the status display window 41W whether or not the voice recognition function is operating as shown in FIG. In FIG. 14, the operator is notified that the speech recognition function is operating by displaying a text message of "The speech of the operator can be recognized." When the machine guidance apparatus 50 can not recognize the words issued by the operator, it may display that in the status display window 41W. The machine guidance device 50 may display an icon, an animation or the like in addition to the text message.”). Iimuro and Nishi are in the same field of endeavor of work machine management system and apparatus for. It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to modify Iimuro a shovel management system with Nishi speech to text conversion. No new functionality would arise from the combination and the combination would improve usability of Iimuro by adding a function of speech to text it allows better management of the failure data of the shovel. Further, finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable. Regarding claim 10 Iimuro teaches a shovel management apparatus for management of a shovel, the shovel management apparatus comprising: a memory configured to store one or more pieces of failure information about a failure in a past; (See Iimuro paragraph 0045, 0044 and 0039; “…The management server 90 is a computer provided outside the work machines 10, and may be installed in a management center… The work machine 10 of Example 1 is a hydraulic shove…FIG. 2 illustrates a configuration example of a work machine management system according to Example 1…”); and a hardware processor coupled to the memory; (See Iimuro paragraph 0047; “The management server 90 may be constructed using a known computer, and comprises, for example, a computing means, a storage means, an input means, and an output means. The computing means includes a processor…”). Iimuro does not teach but Nishi teaches, and configured to convert speech data acquired from the shovel into text data; (See Nishi paragraph 0059; “The voice recognition unit 505 recognizes the voice emitted by the operator of the shovel PS. In the example of FIG. 3A, a speech recognition engine is used to convert speech input through the speech input device 44 into text…”); extract, from the memory …information whose content is similar to the text data; (See Nishi paragraph 0059; “…The speech recognition engine utilizes one or more speech recognition dictionaries to convert input speech into text. The speech recognition dictionary is stored, for example, in the storage device 47…”). Iimuro and Nishi are in the same field of endeavor of work machine management system and apparatus for. It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to modify Iimuro a shovel management system with Nishi speech to text conversion. No new functionality would arise from the combination and the combination would improve usability of Iimuro by adding a function of speech to text it allows better management of the failure data of the shovel. Further, finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable. Iimuro does not teach but Koga teaches, and cause a display device of the shovel to together with the text data converted from the speech data, at least a portion of the extracted failure information including a method of handling the failure; (See Koga paragraph 0005, 0075- 0076, 0041, 0046-0048 and 0052; “The state of the excavator when the operator feels uncomfortable may be a sign of failure of the shovel… The controller 30 that executes the audio / text conversion process receives from the speaker attached to the display device 40 a voice such as "which motion feels uncomfortable?", "Voice that is affected by boom"? A message may be output. This is to allow the operator of the shovel to input comments in an interactive manner. The controller 30 that executes the audio / text conversion process receives from the speaker attached to the display device 40 a voice such as "which motion feels uncomfortable?", "Voice that is affected by boom"? A message may be output. This is to allow the operator of the shovel to input comments in an interactive manner… In the case where the voice recognition unit 30 a estimates that the operator feels uncomfortable about the movement of the excavator, the data storage unit 30 b stores the data stored in the volatile memory device 52 during the predetermined period including the estimated time as the reference time Data may be stored in the nonvolatile storage device 53. The same applies to the case where the voice recognition unit 30 a estimates that the operator is satisfied with the movement of the excavator… When it is determined that the predetermined condition concerning speech recognition is satisfied (YES in step ST 1), the controller 30 specifies the range of data to be stored in the nonvolatile storage device 53 (step ST 2). For example, when a negative word is recognized by the voice recognition unit 30 a, the data storage unit 30 b determines that a predetermined condition related to voice recognition has been satisfied. Then, based on the speech point of the negative word, the range of data to be stored in the nonvolatile storage device 53 is specified. For example, the range of data stored in the volatile memory device 52 during the period starting from the point of a predetermined time from the point of utterance as the start point and the point after a predetermined time from the point of utterance as the end point is stored in the nonvolatile storage device 53 As the range of data to be stored. Thereafter, the data storage unit 30 b stores data (hereinafter referred to as "data set") within the specified range in the nonvolatile storage device 53 (step ST 3). For example, the data stored in the volatile storage device 52 is copied to the nonvolatile storage device 53. The data storage unit 30 b may delete the copied data from the data stored in the volatile storage device 52 or overwrite it. Thereafter, the controller 30 determines whether or not a predetermined transmission condition is satisfied (step ST 4). The predetermined transmission condition is a condition to be satisfied when the data stored in the nonvolatile storage device 53 is transmitted to the outside. For example, it is determined that the current time has reached the predetermined time, the elapsed time since the previous transmission time Has reached a predetermined time, that a transmission instruction by manual operation by an operator has been received, and the like… Through the above-described data transmission processing, the controller 30 can transmit the data stored in the volatile storage device 52 to the management device 90 during a predetermined period including a time point at which a negative word is issued, for example. The management device 90 can display the received data on the display unit, thereby presenting the received data to the administrator. By looking at the displayed data, the administrator can analyze the cause of the negative word being generated by the operator of the excavator. The same is true when transmitting data to the support device 94.”). Iimuro and Koga are in the same field of endeavor of work machine management system and apparatus for. It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to modify Iimuro a shovel management system with Koga failure information including a method of handling it. No new functionality would arise from the combination and the combination would improve usability of Iimuro by adding a function of failure information including a method of handling it allows better management of the shovel. Further, finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable. Regarding claim 11 Iimuro teaches shovel management system according to claim 1, Iimuro further teaches, wherein the hardware processor is configured to cause the display device of the shovel to display a screen including the text data converted from the speech data and the extracted failure information retrieved from the memory; (See Iimuro paragraph 0061;” The vehicle body priority level may be indicated not as a simple order but as a deviation value taking the distribution of the risk evaluation values into consideration. Further, when the vehicle body priority level is determined, it is not necessary to refer to all of the information shown in FIG. 3(a). For example, the management server 90 may determine the vehicle body priority level based on at least one of the failure probability, work importance level, or the availability of replacement machine. In this case, the input interface screen of FIG. 3(b) is used for inputting at least one of the failure probability, work importance level, or the availability of replacement machine.”). Iimuro does not explicitly teach but Koga teaches, the extracted failure information including the method of handling the failure corresponding to the content of the speech data; (See Koga paragraph 0005, 0075- 0076, 0041, 0046-0048 and 0052; “The state of the excavator when the operator feels uncomfortable may be a sign of failure of the shovel… The controller 30 that executes the audio / text conversion process receives from the speaker attached to the display device 40 a voice such as "which motion feels uncomfortable?", "Voice that is affected by boom"? A message may be output. This is to allow the operator of the shovel to input comments in an interactive manner. The controller 30 that executes the audio / text conversion process receives from the speaker attached to the display device 40 a voice such as "which motion feels uncomfortable?", "Voice that is affected by boom"? A message may be output. This is to allow the operator of the shovel to input comments in an interactive manner… In the case where the voice recognition unit 30 a estimates that the operator feels uncomfortable about the movement of the excavator, the data storage unit 30 b stores the data stored in the volatile memory device 52 during the predetermined period including the estimated time as the reference time Data may be stored in the nonvolatile storage device 53. The same applies to the case where the voice recognition unit 30 a estimates that the operator is satisfied with the movement of the excavator… When it is determined that the predetermined condition concerning speech recognition is satisfied (YES in step ST 1), the controller 30 specifies the range of data to be stored in the nonvolatile storage device 53 (step ST 2). For example, when a negative word is recognized by the voice recognition unit 30 a, the data storage unit 30 b determines that a predetermined condition related to voice recognition has been satisfied. Then, based on the speech point of the negative word, the range of data to be stored in the nonvolatile storage device 53 is specified. For example, the range of data stored in the volatile memory device 52 during the period starting from the point of a predetermined time from the point of utterance as the start point and the point after a predetermined time from the point of utterance as the end point is stored in the nonvolatile storage device 53 As the range of data to be stored. Thereafter, the data storage unit 30 b stores data (hereinafter referred to as "data set") within the specified range in the nonvolatile storage device 53 (step ST 3). For example, the data stored in the volatile storage device 52 is copied to the nonvolatile storage device 53. The data storage unit 30 b may delete the copied data from the data stored in the volatile storage device 52 or overwrite it. Thereafter, the controller 30 determines whether or not a predetermined transmission condition is satisfied (step ST 4). The predetermined transmission condition is a condition to be satisfied when the data stored in the nonvolatile storage device 53 is transmitted to the outside. For example, it is determined that the current time has reached the predetermined time, the elapsed time since the previous transmission time Has reached a predetermined time, that a transmission instruction by manual operation by an operator has been received, and the like… Through the above-described data transmission processing, the controller 30 can transmit the data stored in the volatile storage device 52 to the management device 90 during a predetermined period including a time point at which a negative word is issued, for example. The management device 90 can display the received data on the display unit, thereby presenting the received data to the administrator. By looking at the displayed data, the administrator can analyze the cause of the negative word being generated by the operator of the excavator. The same is true when transmitting data to the support device 94.”). Iimuro and Koga are in the same field of endeavor of work machine management system and apparatus for. It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to modify Iimuro a shovel management system with Koga failure information including a method of handling it. No new functionality would arise from the combination and the combination would improve usability of Iimuro by adding a function of failure information including a method of handling it allows better management of the shovel. Further, finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable. Conclusion THIS ACTION IS MADE FINAL. 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 LIDIA KWIATKOWSKA whose telephone number is (571)272-5161. The examiner can normally be reached Monday-Friday 8:00-5:00. 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, Scott A. Browne can be reached at (571) 270-0151. 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. /L.K./Examiner, Art Unit 3666 /SCOTT A BROWNE/Supervisory Patent Examiner, Art Unit 3666
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Prosecution Timeline

Dec 19, 2023
Application Filed
Aug 06, 2025
Non-Final Rejection — §103, §112
Nov 10, 2025
Response Filed
Feb 27, 2026
Final Rejection — §103, §112 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

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

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Prosecution Projections

3-4
Expected OA Rounds
70%
Grant Probability
86%
With Interview (+15.5%)
3y 4m
Median Time to Grant
Moderate
PTA Risk
Based on 57 resolved cases by this examiner. Grant probability derived from career allow rate.

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