DETAILED ACTION
This action is filed in response to the application filed on 9/19/2023.
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
Acknowledgement is made of Applicant’s Information Disclosure Statements (IDS) form PTO-1149 filed on 9/19/2023. This IDS has been considered.
Specification
The title of the invention is not descriptive. A new title is required that is clearly
indicative of the invention to which the claims are directed.
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 1-12 are rejected under 35 U.S.C. 101. The claimed invention is directed to the abstract concept of performing mental steps without significantly more. Claim 1, and similarly Claim 7 recite the following abstract concepts in BOLD of:
A monitoring apparatus for monitoring equipment which is a monitoring object, the monitoring apparatus comprising:
an input unit that accepts designation of equipment identifying information for identifying object equipment that is the equipment which is an analysis object, and an analysis item to be analyzed regarding the object equipment;
an equipment status decision unit that acquires data of a data type which is required to analyze the analysis item accepted by the input unit and decides a current equipment status or statuses of the object equipment based on the acquired data;
a diagnosis result decision unit that calculates a diagnosis score for evaluating a current status of the object equipment as a score based on the equipment status of the object equipment as decided by the equipment status decision unit, and decides a diagnosis result of the object equipment on the basis of the calculated diagnosis score; and
a visualization unit that visualizes and presents the diagnosis result of the object equipment decided by the diagnosis result decision unit.
Under Step 1 of the eligibility analysis, we determine whether the claims are to a statutory category by considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: process, machine, manufacture, or composition of matter. The above claims are considered to be in a statutory category as Claim 1 recites an apparatus and Claim 7 teaches a method.
Under Step 2A, Prong One, we consider whether the claim recites a judicial exception (abstract idea). In the above claim, the highlighted portion constitutes an abstract idea because, under a broadest reasonable interpretation, it recites limitations that fall into/recite abstract idea exceptions. Specifically, under the 2019 Revised Patent Subject Matter Eligibility Guidance, it falls into the grouping of subject matter that, when recited as such in a claim limitation, covers performing mathematics or mental steps. The step of a diagnosis unit calculating a diagnosis score can be interpreted as performing mathematics. Furthermore, the diagnostic unit deciding a diagnosis result can be interpreted as a mental process that can be performed in the human mind.
Next, under Step 2A, Prong Two, we consider whether the claim that recites a judicial exception is integrated into a practical application. In this step, we evaluate whether the claim recites additional elements that integrate the exception into a practical application of that exception.
This judicial exception is not integrated into a practical application because there is no improvement to another technology or technical field; improvements to the functioning of the computer itself; a particular machine; effecting a transformation or reduction of a particular article to a different state or thing. Examiner notes that the claimed methods and system are not tied to a particular machine or apparatus, and they do not represent an improvement to another technology or technical field.
Regarding the device of Claim- 1, the elements including an input unit, an equipment status unit, a diagnosis unit, and a visualization unit describe a composition of the device but do not detail a “particular machine” as discussed in 2106.05(b). Similarly there are no other meaningful limitations linking the use to a particular technological environment. Furthermore, the limitations describing the elements composing the device merely indicate a field of use as it imposes no meaningful limitation of the claim. As recited in the MPEP 2106.05(b), merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2359-60, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94. Finally, there is nothing in the claims that indicates an improvement to the functioning of the computer itself or transform a particular article to a new state.
Step 2B, we consider whether the additional elements are sufficient to amount to significantly more than the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the input unit is a generic computer element and not considered significantly more than the abstract idea. As recited in the MPEP, 2106.05(b), merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2359-60, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94.
Additionally, the limitations regarding the equipment status decision unit recites necessary data gathering and does not integrate the abstract idea into a practical application. The limitation amounts to necessary data gathering and outputting. See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering).
Finally the last limitation regarding the visualization unit recites outputting data which does not integrate the abstract idea into a practical application. As recited in MPEP section 2106.05(g), displaying analysis/results is considered extra solution activity. See MPEP 2106.05(g) “Printing or downloading generated menus, Ameranth, 842 F.3d at 1241-42, 120 USPQ2d at 1854-55”, see also MPEP 2106.05(h), As a whole the claim itself is analogous to the Electric Power Group decision in which it was determined that “ Limiting the abstract idea of collecting information, analyzing it, and displaying certain results of the collection and analysis to data related to the electric power grid, because limiting application of the abstract idea to power-grid monitoring is simply an attempt to limit the use of the abstract idea to a particular technological environment, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016).”
Claims 2-6 and 8-12 further limit the abstract ideas without integrating the abstract concept into a practical application or including additional limitations that can be considered significantly more than the abstract idea:
Claims 2 and 8 teach data manipulation and classification which is extra solution activity which does not integrate the abstract ideas. See MPEP 2106.05(d) “Below are examples of other types of activity that the courts have found to be well-understood, routine, conventional activity when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity…vi. Arranging a hierarchy of groups, sorting information, eliminating less restrictive pricing information and determining the price, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1331, 115 USPQ2d 1681, 1699 (Fed. Cir. 2015).”
Claims 3 and 9 teach storing data which is well understood conventional activity that does not integrate the abstract ideas. See MPEP 2106.05(d)(II)(iv) “The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity… iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93.” The claims also disclose an additional abstract idea of performing mathematics by calculating a total score.
Claims 4 and 10 further limit the abstract idea of performing mathematics by further defining the relationship between calculation elements. This embodiment does not provide a practical application to integrate the abstract ideas found in the independent claims.
Claims 5 and 11 further limit the abstract idea of a mental process by teaching additional mental processes of making a decision based on observing data and estimating a cause. These embodiments do not provide a practical application to integrate the abstract ideas found in the independent claims.
Claims 6 and 12 teaches an additional abstract idea of performing mathematics by calculating a deterioration score, and also teaches outputting results which is insignificant extra solution activity. These embodiments do not provide a practical application to integrate the abstract ideas found in the independent claims.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1 and 7 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Takeda (US20200099598A1).
Regarding Claims 1 and 7, Takeda discloses a monitoring apparatus and method for monitoring equipment which is a monitoring object, the monitoring apparatus (e.g. see [0008] “According to a first aspect of the present invention, a monitoring system performs monitoring using a monitoring device connected to a facility to be monitored through the Internet via communication, wherein the facility to be monitored includes: a facility body; and a data processing unit configured to process acquired data acquired from the facility body,” and [0078] “Further, although the plant 100 composed of a plurality of machines and the like has been described as a facility to be monitored in the above-described embodiment, the present invention is not limited thereto. For example, a single machinery installed in a factory or a whole facility such as a building itself can be applied as an object to be monitored”) comprising:
an input unit that accepts designation of equipment identifying information for identifying object equipment that is the equipment which is an analysis object (e.g. see [0074] “a user of the monitoring device 3 manually inputs an operation for requesting detailed data to the input unit 350 in response to the warning. When the input unit 350 has received the input of the operation for requesting the detailed data, the processing unit 310 of the monitoring device 3 transmits the detailed data request to the edge device 2 through the communication unit 320. In that case, the user may designate a data type, a period in which data is acquired, a data format, and the like included in the detailed data request,” and [0024] “The plant 100 includes a facility body and an edge device 2 that processes acquired data acquired from the facility body…When the plant 100 is a thermal power generation plant, for example, the facility body includes a plurality of facilities involved in thermal power generation and installed in the plant, such as a gas turbine, a compressor, a fuel gas supply facility, and an exhaust gas processing facility”), and
an analysis item to be analyzed regarding the object equipment (e.g. see [0044] “Then, the data conversion unit 213 determines that there is no abnormality when the calculated abnormality degree is equal to or less than a predetermined threshold value a set in advance. In addition, the data conversion unit 213 determines that there is an abnormality and analyzes the cause of the abnormality when the abnormality degree is greater than the threshold value” Examiner notes the state of the equipment, i.e. whether there is or is not an abnormality, is the analysis item. Examiner further notes previously cited [0078] teaches this determination can be applied to a single piece of equipment);
an equipment status decision unit that acquires data of a data type which is required to analyze the analysis item accepted by the input unit and decides a current equipment status or statuses of the object equipment based on the acquired data (e.g. see [0043] “In addition, the data conversion unit 213 diagnoses an abnormality of the plant 100 on the basis of the low-density data acquired by the low-density data acquisition unit 211 and the converted feature quantity data and outputs abnormality diagnostic result data indicating a diagnostic result, the low-density data and the feature quantity data to the transmission unit 214,” and [0078] “Further, although the plant 100 composed of a plurality of machines and the like has been described as a facility to be monitored in the above-described embodiment, the present invention is not limited thereto. For example, a single machinery installed in a factory or a whole facility such as a building itself can be applied as an object to be monitored”);
a diagnosis result decision unit that calculates a diagnosis score for evaluating a current status of the object equipment as a score based on the equipment status of the object equipment as decided by the equipment status decision unit (e.g. see [0043] “the data conversion unit 213 calculates an abnormality degree according to a K-nearest neighbors algorithm in which a point is determined as an abnormal value when a distance from certain data to other nearest data ( a nearest point) exceeds a certain threshold value, the point as an abnormal value,”) and decides a diagnosis result of the object equipment on the basis of the calculated diagnosis score (e.g. see [0044] “the data conversion unit 213 determines that there is an abnormality and analyzes the cause of the abnormality when the abnormality degree is greater than the threshold value α”); and
a visualization unit that visualizes and presents the diagnosis result of the object equipment decided by the diagnosis result decision unit (e.g. see [0046] “The monitoring device 3 monitors the plant 100 by displaying the received monitoring data ( e.g., a graph showing MD values, abnormality degree scores, abnormality factor ranking and the like”).
Claim Rejections - 35 USC § 103
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 2 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Takeda (US20200099598) in view of Komaki (WO2017159501A1).
Regarding Claims 2 and 8, Takeda teaches the limitations of Claims 1 and 7. Takeda does not explicitly disclose wherein the diagnosis result decision unit ranks the current status of the object equipment in a specified classification group configured from the equipment which is a plurality of monitoring objects on the basis of the calculated diagnosis score of the object equipment; and wherein the visualization unit visualizes a rank of the object equipment in the classification group as ranked by the diagnosis result decision unit.
In the same field of endeavor, Komaki teaches wherein the diagnosis result decision unit ranks the current status of the object equipment in a specified classification group configured from the equipment which is a plurality of monitoring objects on the basis of the calculated diagnosis score of the object equipment (e.g. see [pg. 4 paragraph 7] “Moreover, the rank of the state of the plant equipment (hereinafter also referred to as “state rank”) is set from a plurality of ranks for each detection unit 12 based on the detection value detected by the detection unit 12 of the detection apparatus 10”); and
wherein the visualization unit visualizes a rank of the object equipment in the classification group as ranked by the diagnosis result decision unit (e.g. see [pg. 7 paragraph 7] “The top screen 60 </ b> A includes an abnormal rank display unit 601, a group display unit 602, a group type selection unit 603, and an all equipment list selection unit 604”).
It would have been obvious to one of ordinary skill in the art to combine the diagnosis result decision unit of Takeda with the ranking embodiment of Komaki for the purpose of locating faults in factory equipment with the advantage of organizing the fault data in order to ensure the most critical errors are handled timely to ensure the factories continued operation.
Claims 3-5, and 9-11 are rejected under 35 U.S.C. 103 as being unpatentable over Takeda (US20200099598) in view of Oku (US20160378584A1) and in further view of Hayashi (US20190226943 A1).
Regarding Claims 3 and 9, Takeda and Hayashi teach the limitations of Claims 1 and 7. Takeda further discloses wherein a score is set to each of the causes (e.g. see [0045] “In addition, FIG. 4(8) shows an abnormality degree score and abnormality factor ranking of each factor (cause of abnormality). The abnormality factor ranking is ranking of a factor with a high abnormality degree score”),
wherein the equipment status decision unit decides all the equipment statuses, which the object equipment falls under, as the equipment statuses of the object equipment (e.g. see [0043] “the data conversion unit 213 calculates an abnormality degree according to a K-nearest neighbors algorithm in which a point is determined as an abnormal value when a distance from certain data to other nearest data ( a nearest point) exceeds a certain threshold value, the point as an abnormal value,” Examiner notes the cited portion teaches that the determination of whether or not an abnormality is present is based off of a numerical value, therefore every time that numerical value is exceeded the abnormality will be determined).
While Takeda teaches storing abnormality diagnostic result data (e.g. see [0036]), Takeda does not explicitly disclose a database in which a correspondence relationship between the equipment statuses and causes for the equipment statuses is stored.
Furthermore, Takeda does not explicitly disclose wherein the diagnosis result decision unit calculates a total score with respect to each of the causes by multiplying a quantity of the equipment statuses of the object equipment associated with the cause by the score that is set to the cause, and calculates the diagnosis score of the object equipment by adding up the calculated total score of each cause.
In the same field of endeavor, Oku teaches a database in which a correspondence relationship between the equipment statuses and causes for the equipment statuses is stored (e.g. see [0014] “According to one embodiment of the present invention, an information processing system is provided that includes a storage unit that stores and associates a cause of a failure that has occurred in an electronic device, state information of the electronic device at the time the failure has occurred in the electronic device due to the cause of the failure, and a measure to be implemented in response to the cause of the failure.”).
It would have been obvious to one of ordinary skill in the art before the effective filling date to combine the diagnostic result data storage of Takeda with the status and cause relationship data of Oku for the purpose of monitoring the operation of factory equipment with the advantage of a quicker diagnosis of maintenance issue through the use of a stored database.
Also in the same field of endeavor, Hayashi teaches wherein the diagnosis result decision unit calculates a total score with respect to each of the causes by multiplying a quantity of the equipment statuses of the object equipment associated with the cause by the score that is set to the cause (e.g. see [0071] “The abnormality cause identification part 6 calculates the score for each abnormality cause by collating features F having top N contribution rates C which largely contribute to the abnormality degree Q obtained by the abnormality-contribution-rate calculation part 5”), and calculates the diagnosis score of the object equipment by adding up the calculated total score of each cause (e.g. see [0068] “The abnormality-contribution-rate calculation part 5 estimates a contribution rate C of each of the features F constituting the monitoring feature group Ft used for calculating the abnormality degree Q determined as abnormal by the determination part 4, with respect to the abnormality degree,” Examiner notes the contribution rates of the causes are utilized to calculate the overall abnormality degree which is the total score).
It would have been obvious to one of ordinary skill in the art before the effective filling date to combine the diagnosis results of Takeda with total score embodiments of Hayashi for the purpose of monitoring the operation of factory equipment with the advantage of accurately determining the degree of any abnormalities in order to most efficiently locate the largest problems in the equipment.
Regarding Claims 4 and 10, Takeda, Oku, and Hayashi teach the limitations of Claims 3 and 9. Takeda further discloses wherein the score according to seriousness of the equipment status associated with the cause is set to each cause (e.g. see [0045] “In addition, FIG. 4(8) shows an abnormality degree score and abnormality factor ranking of each factor (cause of abnormality). The abnormality factor ranking is ranking of a factor with a high abnormality degree score”).
Regarding Claims 5 and 11, Takeda, Oku, and Hayashi teach the limitations of Claims 3 and 9. Takeda does not explicitly disclose wherein when the equipment status decision unit decides the equipment status which is not registered in the database to be the equipment status of the object equipment the equipment status decision unit estimates the cause for the equipment status on the basis of the correspondence relationship between the equipment status and the cause, which is registered in the database.
In the same field of endeavor, Oku teaches wherein when the equipment status decision unit decides the equipment status which is not registered in the database to be the equipment status of the object equipment the equipment status decision unit estimates the cause for the equipment status on the basis of the correspondence relationship between the equipment status and the cause, which is registered in the database (e.g. see [0088] “The failure diagnosis model development unit 23 develops a failure diagnosis model that associates the data pattern of state information to be used to identify the cause of failure, the necessary measure, and the necessary part with each of the causes of failure analyzed, and stores the failure diagnosis model that has been developed in the failure diagnosis model storage unit 33. Note that in some embodiments, the failure diagnosis model development unit 23 may simply store each of the causes of failure analyzed in association with the data pattern of state information to be used to identify the cause of failure, the necessary measures, and the necessary parts in the failure diagnosis model storage unit 33”).
It would have been obvious to one of ordinary skill in the art before the effective filling date to combine the diagnostic result data storage of Takeda with the status and cause relationship data of Oku for the purpose of monitoring the operation of factory equipment with the advantage of a quicker diagnosis of maintenance issue through the use of a stored database.
Claims 6 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Takeda (US20200099598 A1) in view of Daitou (US20190004507 A1).
Regarding Claims 6 and 12, Takeda teaches the limitations of Claims 1 and 7. Takeda does not explicitly disclose wherein the diagnosis result decision unit calculates a degree of deterioration over time of the object equipment as deterioration over time on the basis of the diagnosis score, which evaluates the current status of the object equipment as a score, and the diagnosis score which evaluates a past status of the object equipment as a score; and wherein the visualization unit visualizes the deterioration over time of the object equipment which is calculated by the diagnosis result decision unit.
In the same field of endeavor, Daitou teaches wherein the diagnosis result decision unit calculates a degree of deterioration over time of the object equipment as deterioration over time on the basis of the diagnosis score, which evaluates the current status of the object equipment as a score, and the diagnosis score which evaluates a past status of the object equipment as a score (e.g. see [0133] “For example, the maintenance plan generating unit 41 may diagnose the degree of deterioration of the equipment 110, at timing when a regular report is output by the equipment monitoring system 3, referring to the diagnosis information stored in the equipment database 30 and the inspection result stored in the maintenance database 40”); and
wherein the visualization unit visualizes the deterioration over time of the object equipment which is calculated by the diagnosis result decision unit (e.g. see [0135] “The display control unit 42 outputs a maintenance state of each piece of equipment 110 to a display apparatus (not shown). Thereby, the client can know the maintenance state of the equipment 110. The display control unit 42 may output the maintenance history. Also, the display control unit 42 may output the equipment ledger stored in the maintenance database 40, or the maintenance plan generated by the maintenance plan generating unit 41,” and [0132] “For example, the maintenance plan generating unit 41 may generate a maintenance plan so that the maintenance plan generating unit 41 diagnoses the degree of deterioration of the equipment 110 based on results of the regular inspections”).
It would have been obvious to one of ordinary skill in the art before the effective filling date to combine the diagnosis results and display of Takeda with the deterioration degree and display of Daitou for the purpose of monitoring factory equipment with the advantage of long term upkeep.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NYLA GAVIA whose telephone number is (703)756-1592. The examiner can normally be reached M-F 8:30-5:30pm.
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/NYLA GAVIA/ Examiner, Art Unit 2863
/Catherine T. Rastovski/ Supervisory Primary Examiner, Art Unit 2863