DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Claims 13-14 and 20 have been canceled.
Claims 15-19 and 21-24 are pending.
Claims 15-19 and 21-24 are rejected, grounds follow.
THIS OFFICE ACTION IS FINAL, see additional information at the conclusion of this action.
Priority
Application’s status as a 35 USC 371 national stage application of PCT application PCT/EP2022/052941 is acknowledged.
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Response to Arguments
Applicant’s arguments, see Remarks page 4, filed 23 December 2025, with respect to the Claim Objection to Claim 21 have been fully considered and are persuasive. Examiner agrees the amendment obviates the objection. The objection to Claim 21 has been withdrawn.
Applicant’s arguments with respect to the 35 USC 102 rejection of Claims 13, 14, and 20 are acknowledged but have been mooted by their cancellation.
Applicant's arguments, see remarks Pages 5 et seq. regarding the rejection of (now independent) Claims 15 and 24, have been fully considered and they are persuasive in part.
As to the persuasive part: 1) Examiner agrees that Curlett in view of Henry does not appear to teach or fairly suggest all of the limitations of the claim, particularly the limitations from previously presented claim 14 (nb. rejected over Curlett in view of Moore) Accordingly the rejection has been withdrawn and a new rejection has been made over Curlett in view of Moore in view of Henry. 2) Examiner agrees that the amendments to the claim adding additional subject matter do modify the scope of the claim such that the switches of the claim are no longer exactly the same improvement as made in Henry, and accordingly the motivation to combine has been adjusted accordingly.
As to the unpersuasive part, examiner maintains that the overall disclosure of Henry teaches or fairly suggests the amended features, inter alia, of “switchable logic elements configured to connect or disconnect the pairs of individual models for data exchange between the pairs of individual models”. In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., apparently that the claim must exclusively cover only 1 to 1 connections between modules and not one to several or several to several or several to one as e.g. depicted in instant application fig. 6) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). while the preferred embodiment of Henry discloses multi-port switches, only one input is selected to be output, thereby connecting one individual model to another model. Further, Henry contemplates that configurations including a different number of inputs may also be suitable (See Henry [0055] “While five separate steady-state estimations are illustrated in control diagram, it is to be understood that the diagram is illustrative in nature and not limiting, and thus other switch configurations are possible.” ). Finally, Curlett suggests reconfiguration between connections of multiple types of components (see Curlett page 16, table 1 and the discussion in Curlett of connectors, generally) but is silent as to whether they may be switched. Henry teaches that switchable connectors can be used to connect subcomponents of a simulation model. For these reasons examiner finds the amended claim to nevertheless be taught or fairly suggested by the references of record, and accordingly a new grounds of rejection, necessitated by the amendment, is made in view of Curlett, Moore, and Henry. Please see below for detailed rejection.
Examiner notes for clarity of the record that the arguments for the other dependent claims rely on the alleged allowability of the independent claims.
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.
Claim(s) 15-18, 21, and 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Curlett in view of Moore et al., US Pg-Pub 2019/0005005 and in view of Henry et al., US Pg-Pub 2016/0084181.
Regarding Claims 15 and 24, Curlett teaches:
(Claim 15 representative) An integrating model (see Page 1, “The aerothermodynamic simulation of the engine plays a pivotal role in the entire life cycle of turbine engines”) for a technical system (i.e. turbine engine) composed of at least one of a machine, a component of a machine, and a technical process,(see e.g. fig. 3, page 11) the integrating model comprising:
a machine-machine interface; (see fig. 6, page 17 and page 16 “the source, model data, and the customer deck API can be compiled into a customer deck for distribution. It is our intent to automate, as much as possible, the process of moving from the generalized NASA model to the customer model.”)
and a plurality of individual models (see fig. 3, page 11, and page 10 “A component is defined as a code module (or object) that takes inputs and produces outputs and has little other interaction with the system.” having each assigned a raw model (see Page 12 “A component may be as simple as multiplying a number on an input port by two and writing it to an output port; or it may be as complex as a 3D Navier-Stokes code with ports containing large grids of data.”) and a data pre-processing, (see page 15, section 11.3 Table Interpolation Classes: A set of classes was developed that makes handling of component maps and other tabular data much easier. These classes decouple the data, file parser, interpolation routines, and scaling relations for flexibility and efficiency while maintaining a single, simple, consistent interface.”)
wherein different individual models model different parts of the technical system (e.g. “shaft”, “Compressor” etc.) and have different raw models (the models are different object oriented classes, see e.g. fig. 2 depicting the inheritance tree) and a different data pre-processing, (see appendix A, describing the ways that data is pre-processed when transferred between components, particularly Page 20, section A.3 “This variation has a smart connector between two components. The connector is referred to as "smart" because it can connect two different types of data if it has a suitable translation function to go from one type to the other.”)
and wherein at least one of the individual models is interchangeable for a part of the technical system; (See Page 12 “For example, suppose a new compressor component was needed with a different surge margin calculation. The class PsNewCompressor could be derived from the PsCompressor class (see Appendix C). Only the surge-margin( ) method would need to be re-implemented in PsNewCompressor; everything else would be inherited from PsCompressor”)
[…] and modeling a part of the technical system using the changed configuration of the individual models. (see Page 16, table 1 heading “one general executable” particularly features for “More Dynamic (configuration can be changed on-the-fly from the user interface)” and “Better suited for conceptual/preliminary design (configuration changing)” and “Optimizer (AI) can modify configuration”)
Curlett differs from the claimed invention in that:
Curlett does not clearly articulate: with the different raw models programmed in different programming languages
Nor: switchable logic elements disposed between pairs of the individual models, with the switchable logic elements configured to connect or disconnect the pairs of the individual models for data exchange between the pairs of the individual models
However, Moore teaches a component model for a drive (e.g. wind turbine, see fig. 2 and Moore [0040] “In this example, the virtual model 200 is a digital representation of a wind turbine.”) where components may be switched out freely ([0024] “Accordingly, as long as the components maintain the common data frame as an input and an output, the components can simply be removed and replaced without affecting the remaining components of the algorithm ensemble.”) which includes programming in different programming languages ([0024] “a user such as a data scientist, programmer can use any of multiple programming languages (e.g., Java, Python, R) to design an algorithm without worrying about how it affects the other algorithms included in the algorithm ensemble.”)
Moore and Curlett are analogous art because they are from the same field of endeavor of component based simulation of operational plants, and contain overlapping structural and functional similarities; each reference represents a drive system with a plurality of programmatic models which cooperate to estimate operational performance of a larger system.
One of ordinary skill in the art before the effective filing date of the application could have modified the teachings of Curlett to use a pluggable framework including diverse programming languages for the interior raw models of the various components of Curlett, as suggested by Moore.
One of ordinary skill in the art could have been motivated to make this modification in order to permit efficient optimization of the components and permitting seamlessly switching between different algorithms, as suggested by Moore ([0063] “the pluggable framework provided herein permits the efficient optimization of which components within an algorithm ensemble should be applied to various problems by permitting a mechanism to seamlessly switch between different component algorithms.”)
And, Henry teaches a complex model (see fig. 4 and Henry [0054] “plurality of fresh intake air flow estimations, determined according the estimation models described above, that are input into multiple switches and a complex model to determine a final fresh intake air flow.”) of a drive ([0014] “The approach described herein may be employed in a variety of engine types, and a variety of engine-driven systems.”) which disposes switchable logic elements between individual models (fig. 4, Switch 402, 406, disposed between the estimation models 404, and 410; see [0056]) with the switchable logic elements configured to connect or disconnect the pairs of the individual models ([0055] “While five separate steady-state estimations are illustrated in control diagram, it is to be understood that the diagram is illustrative in nature and not limiting, and thus other switch configurations are possible.” ) for data exchange between the pairs of the individual models (see e.g. [0056] “The output from switch 406 (which may be referred to as the steady-state estimation) is fed into the complex predictor/corrector model 410.”)
Henry and Curlett are analogous art because they are from the same field of endeavor of component based simulation of operational plants, and contain overlapping structural and functional similarities; each reference represents a drive system with a plurality of programmatic models which cooperate to estimate operational performance of a larger system.
One of ordinary skill in the art could have modified the teachings of Curlett to incorporate switches between models, as suggested by Henry, for connecting and disconnecting pairs of components with one another, such as selecting between PsCompressor and PsNewCompressor of Curlett to realize the exhortation of Curlett to permit reconfiguration of the model in the general purpose executable.
One of ordinary skill in the art could have motivated to make this modification in order to permit easier reconfiguration as suggested by Curlett More Dynamic (configuration can be changed on-the-fly from the user interface)” and “Better suited for conceptual/preliminary design (configuration changing)” and because Henry suggests that switches are suitable for connecting outputs of components to inputs of other components based a predetermined configuration ([0055] “The multi-port switch selects one estimation, based on a predetermined switch configuration… The estimation output from the multi-port switch may be selected based on operating conditions, based on a minimum value, or other configuration.”)
Claim 24 recites substantively the same subject matter, except embodied as a method. mutatis mutandis, this claim is likewise anticipated by the disclosure of Curlett for the same reasons articulated with respect to claim 1, above.
Regarding Claim 16, Curlett in view of Moore and in view of Henry teaches all of the limitations of parent claim 15,
Curlett further discloses:
wherein the technical system comprises at least part of a drive. (e.g. page 1 “turbine engine” “aircraft engine design”)
Regarding Claim 17, Curlett in view of Moore and in view of Henry teaches all of the limitations of parent claim 15,
Moore further teaches:
wherein the integrating model is cloud based. (see fig. 1 and e.g. [0031] “FIG. 1 illustrates a cloud computing environment associated with industrial systems in accordance with an example embodiment. FIG. 1 illustrates generally an example of portions of an asset management platform (AMP) 100. As further described herein, one or more portions of an AMP can reside in a cloud computing system 120, in a local or sandboxed environment, or can be distributed across multiple locations or devices.”)
Moore and Curlett are analogous art because they are from the same field of endeavor of component based simulation of operational plants, and contain overlapping structural and functional similarities; each reference represents a drive system with a plurality of programmatic models which cooperate to estimate operational performance of a larger system.
One of ordinary skill in the art before the effective filing date of the application could have modified the teachings of Curlett to include deploying at least part of the integrating model taught by Curlett to the cloud, as suggested by Moore.
One of ordinary skill in the art before the effective filing date of the application could have been motivated to make this modification in order to facilitate increased efficiency and enhanced software as suggested by Moore ([0027] “By bringing such data into a cloud-based computing environment, new software applications informed by industrial process, tools and know-how can be constructed, and new analytics specific to an industrial environment can be created. Insights gained through analysis of such data can lead to enhanced asset designs, enhanced software algorithms for operating the same or similar assets, better operating efficiency, and the like.”)
Regarding Claim 18, Curlett in view of Moore and in view of Henry teaches all of the limitations of parent claim 13,
Curlett further discloses:
wherein the data pre-processing is provided for communication between the individual models. (see e.g. Page 20, particular A.3 and A.4 “This variation has a smart connector between two components. The connector is referred to as "smart" because it can connect two different types of data if it has a suitable translation function to go from one type to the other.”)
Regarding Claim 21, Curlett in view of Moore and in view of Henry teaches all of the limitations of parent claim 24,
Curlett further discloses
wherein changing the data pre-processing when exchanging an individual model of the integrating model. (see page 25, components store information describing their required data sources (e.g. “//maps used by compressor” see page 15 section 11.3 for more information) to the extent that components are interchangeable, see page 12 cited supra. and that smart connectors may handle translating between different types of data as necessary when connecting two components, Curlett therefore also discloses the changing of the pre-processing component as necessary, e.g. Page 20 section A.3 “in this model the system must know when to and when not to call the translation function in the station”)
Claim(s) 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Curlett in view of Moore and Henry, further in view of Citriniti et al., US 2018/0174057.
Regarding Claim 19, Curlett in view of Moore and Henry teaches all of the limitations of parent claim 13,
Curlett in view of Moore and Henry differs from the claimed invention in that:
The references do not appear to clearly articulate wherein the machine-machine interface model is a REST API interface.
However, Citriniti teaches a modeling system (see fig. 1 “Predictive models”) which may be for a drive (see [0001] “wind turbine”) where the machine-to-machine interface ([0047] “The data lenses provide endpoints that are accessible to the predictive models 122 such that the predictive models can call an API or otherwise access the endpoint to retrieve particular data stored within the logically organized data 118.”) is a REST API ([0086] “The accessed data is exposed through the data lenses as one or more endpoints, such as Representational State Transfer (REST) API endpoints. External predictive models may query these endpoints to extract the data from the underlying logical model”)
Curlett and Citriniti are analogous art because they are from the same field of endeavor of component based simulation of operational plants, and contain overlapping structural and functional similarities; each reference represents a drive system with a plurality of programmatic models which cooperate to estimate operational performance of a larger system.
One of ordinary skill in the art before the effective filing date of the application could have modified the teachings of Curlett to include a machine-machine interface which is a REST API, as suggested by Citriniti.
One of ordinary skill in the art before the effective filing date of the application could have been motivated to make this modification in order to enable the predictive model to retrieve data from the underlying asset without understanding how the data is extracted and/or stored, as suggested by Citriniti ([0047] “In this manner, embodiments provide the ability for the predictive models 122 to retrieve data derived from and/or related to the underlying assets 102 without requiring a full understanding the manner in which the intermediate data 108 is stored or extracted from the assets 102.”)
Claim(s) 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Curlett in view Moore and Henry, further in view of Kohn et al., US Pg-Pub 2013/0321167.
Regarding Claim 22, Curlett in view of Moore and Henry teaches all of the limitations of parent claim 24,
Curlett in view of Moore and Henry differs from the claimed invention in that:
The references do not appear to clearly articulate recording continuous measurement signals and transmitting the recorded continuous measurement signals in blocks for use in the integrating model.
However, Kohn teaches recording sensor data measurements (fig. 2a and [0023] “Data elements 100, 103, 106, 109 contain bits 0 . . . 7 of the MSB (most significant byte), which contains the measured sensor data. First data subelements 101, 104, 107, 110 contain bits 8 . . . 11 of the LSB (least significant byte), which contains the measured sensor data.”) that may be transferred in blocks to the destination application. ([0024] “Instead of the constant reading out of sensor data, application unit 201 periodically receives data blocks with data stored in sensor module 200.”)
Kohn is analogous art because it is reasonably pertinent to the same problem confronted by applicant of how to supply measured data to a data-ingesting application.
One of ordinary skill in the art before the effective filing date of the application could have modified the teachings of Curlett to include recording and transmitting measurement data in blocks, as suggested by Kohn.
One of ordinary skill in the art before the effective filing date of the application could have been motivated to make this modification in order to reduce energy consumption by the data transfer, as suggested by Kohn. ([0024] “This results in a reduction of energy consumption, because application unit 201 can e.g. change over into sleep mode between the block-by-block reading of the sensor data.”)
Claim(s) 23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Curlett in view Moore, Henry, and Kohn, further in view of Kothare et al., US Pg-Pub 2004/0064202.
Regarding Claim 23, Curlett in view of Moore, Henry, and Kohn teaches all of the limitations of parent claim 22,
The combination differs from the claimed invention in that:
the references do not appear to clearly articulate further comprising changing a sampling rate or a block size depending on the individual model used.
However, Kothare teaches that sample rate may be selected to match the rate at which a model is designed to operate ([0142] “Re-sampling and interpolation are other pre-processing possibilities for data that may have been sampled too fast (re-sampling) or too slowly (interpolation). Generally the sample rate may be selected to match the rate at which the model-based controller is designed to operate, so these pre-processing steps may not be necessary in most cases.”)
Kothare is analogous art because it is reasonably pertinent to the same problem confronted by applicant of how to supply measured data to a data-ingesting application.
One of ordinary skill in the art before the effective filing date of the application could have modified the teachings of Curlett in view of Kohn to include changing the sampling rate of the data sources to match the ingestion rate of the models, as suggested by Kohn.
One of ordinary skill in the art before the effective filing date of the application could have been motivated to make this modification in order to reduce the amount of re-sampling and/or interpolation required prior to providing the data to the model, as suggested by Kothare ([0142] “Re-sampling and interpolation are other pre-processing possibilities for data that may have been sampled too fast (re-sampling) or too slowly (interpolation). Generally the sample rate may be selected to match the rate at which the model-based controller is designed to operate, so these pre-processing steps may not be necessary in most cases.”)
Conclusion
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.
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/J.T.S./Examiner, Art Unit 2119
/MOHAMMAD ALI/Supervisory Patent Examiner, Art Unit 2119