Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This office action is in response to an amendment filed on 2/17/26. Claims 1, and 3-21 are pending.
Response to Amendments
Amendments filed on 2/17/26 are under consideration. Claims 1, 5, 10-11, 13, 16 and 18 are amended. Claim 21 is added.
Continued Examination under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous office action has been withdrawn pursuant to 37 CFR 1.114. Applicant’s submission filed on 1/2/2026 has been entered.
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, and 3-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
101 Analysis – Step 1
Claims 1, 3-12, and 21 are directed to an apparatus, (i.e., a machine). Therefore, claims 1, and 3-12 are within at least one of the four statutory categories.
Claims 13-17 is directed to non-transitory computer readable medium (i.e., a manufacture). Therefore, claims 13-17 are within at least one of the four statutory categories.
Claim 18-20 is directed to a method (i.e., a process). Therefore, claims 18-20 are within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong I
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent claim 1 includes limitations that recite an abstract idea (mental process) and will be used as a representative claim for the remainder of the 101 rejections. Independent claim 1, 13, and 18 recite:
interface circuitry to receive input for a query and provide a result of the query as output; memory circuitry to store a plurality of snapshots, each snapshot including a plurality of digital twin models interconnected by a plurality of connections to form a network of digital twins, the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset, the plurality of connections including a first connection between the first digital twin model and the second digital twin model, the first connection representing a relationship between the first digital twin model and the second digital twin model at a specified point in time, each snapshot representing a state of the digital twin models at the specified point in time, the memory circuitry arranged to enable identification and processing of one or more snapshots in response to the query; and processing circuitry to model, track, analyze, and adjust aircraft assets, the processing circuitry to process the query to search the memory circuitry, the processing circuitry to identify, in response to the query, at least a first snapshot representing the plurality of digital twin models and interconnections at a first point in time and a second snapshot representing the plurality of digital twin models and interconnections at a second point in time, the processing circuitry to determine a correlation between the first snapshot and the second snapshot and generate the result with an actionable output based on the correlation. the processing circuitry to output the result to an external device for execution with respect to the actionable output to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset.
The examiner submits that the foregoing bolded limitation constitutes a “mental process” because under its broadest reasonable interpretation, the claim covers a mental process . For example, “store a plurality of snapshots”, “enable identification and processing of one or more snapshots in response to the query”, “to process the query to search”, “identify, in response to the query, at least a first snapshot … and a second snapshot”, and “determine a correlation between the first snapshot and the second snapshot and generate the result with an actionable output based on the correlation”. In the context of this claim these limitations merely show the human mind’s capability of creating and storing memories, identification based on being prompted to do something by the external environmental and time stamping, searching through memory, and determining a correlation between stored data in the memory as all can be done by human mind. The additional limitation of “provide a result of the query as output” in the context of this claim is just taking in information and outputting information accordingly, which again is something the human mind is capable of and can do with the aid of pen and paper. Finally the limitation “model, track, analyze, and adjust aircraft assets” and “to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset”. In the context of this claim the limitation is adjusting an asset in a way that is not specified and thus the adjustment of the asset may be a mental process that can be done with the aid of pen and paper. Essentially, this process is collecting data about a digital twins of aircrafts and responding to a query from someone based on the digital twins and subsequently prompting the user from where the query originated with a plan of action. Accordingly, the claim recites at least one abstract idea.
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (Where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”):
interface circuitry to receive input for a query and provide a result of the query as output; memory circuitry to store a plurality of snapshots, each snapshot including a plurality of digital twin models interconnected by a plurality of connections form a network of digital twins, the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset, the plurality of connections including a first connection between the first digital twin model and the second digital twin model, the first connection representing a relationship between the first digital twin model and the second digital twin model at a specified point in time, each snapshot representing a state of the digital twin models at the specified point in time, the memory circuitry arranged to enable identification and processing of one or more snapshots in response to the query; and processing circuitry to model, track, analyze, and adjust aircraft assets, the processing circuitry process the query to search the memory circuitry, the processing circuitry identify, in response to the query, at least a first snapshot representing the plurality of digital twin models and interconnections at a first point in time and a second snapshot representing the plurality of digital twin models and interconnections at a second point in time, the processing circuitry to determine a correlation between the first snapshot and the second snapshot and generate the result with an actionable output based on the correlation the processing circuitry to output the result to an external device for execution with respect to the actionable output to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset.
For the following reasons, the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitations of “receive input for a query”, and “each snapshot including a plurality of digital twin models interconnected by a plurality of connections, the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset, the plurality of connections including a first connection between the first digital twin model and the second digital twin model, the first connection representing a relationship between the first digital twin model and the second digital twin model at a specified point in time, each snapshot representing a state of the digital twin models at the specified point in time”, and “output the result to an external device for execution with respect to the actionable output.” These limitations merely are insignificant extra-solution activities that merely use a generic computer and or generic computer components (“interface circuitry” & “processing circuitry”) to execute the apparatus’s configuration. In particular, the step of receiving an input, or outputting a result (i.e., as a general means of gathering and sending aircraft data for use in the mental process step), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. For the additional limitations these are merely stating the type of data that is sored within the generic computer component (“memory circuitry”) (i.e., as a general means of gathering and sending aircraft data for use in the mental process step), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. Similarly the additional limitations “representing the plurality of digital twin models and interconnections at a first point in time”, and “representing the plurality of digital twin models and interconnections at a second point in time” are using generic computer components, (memory), to further specify the type of data that is being used within the mental processing steps and thus amount to mere data gathering. Regarding the limitation of a “processing circuitry“, “memory circuitry”, and “interface circuitry” . This limitation merely is applying the use of a generic computer and or generic computer components to execute the apparatus’s configuration, and amounts to implementing an abstract idea on a computer. The system is recited at a high level of generality and merely automates the aircraft maintenance check.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitations as an ordered combination or as a whole, the limitations add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitations do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B
Regarding Step 2B of the 2019 PEG, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of “receive” to perform the aircraft maintenance check amounts to nothing more than applying the exception using a generic computer component. Generally applying an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the additional limitations of “receive”, and electronic the examiner submits that these limitations are insignificant extra-solution activities.
Further, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B to determine if they are more than what is well-understood, routine, conventional activity in the field. The additional limitation of “processing circuitry“, “memory circuitry”, and “interface circuitry” is well-understood, routine, and conventional activities because the specification does not provide any indication that the circuitry is anything other than a conventional computer. The additional limitations of “receive” and “output” are well-understood, routine, and conventional activities because the background recites that the components are all conventional computers and the data transferring over a network is done through well understood and routine communication pathways. MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere collection or receipt of data over a network, as well as, transmitting data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner.
Dependent claims 3-12, 14-17 and 19-21 do not recite any further limitations that cause the claims to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception and/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application. Claim 3 mentions “… correlation includes at least one …” which would fail under Step 2A prong 1 for being a continuation of the mental process and thus would not allow claim 3 to be considered eligible subject matter. Claim 4 mentions “…wherein the commonality includes at least one. …” which would fail under Step 2A prong 2 for being an insignificant extra solution activity of mere data gathering or would fail under step 2a prong 1 as a continuation of the mental process as it’s further defining the determining step and would not allow claim 4 to be considered eligible subject matter. Claim 5 mentions “…wherein the change includes at least one…” which would fail under Step 2A prong 1 for being a continuation of the mental process and thus would not allow claim 5 to be considered eligible subject matter. Claims 6 mentions “…plurality of digital twin models includes at least one …” which would fail under Step 2A prong 2 for being a continuation of mere data gathering and would not allow claim 6 to be considered eligible subject matter. Claim 7 and 8 mention “…wherein the aircraft digital twin model …” which would fail under Step 2A prong 2 for being insignificant extra solution activity within data gathering and would not allow claim 7 or 8 to be considered eligible subject matter. Claim 9 mentions “…memory circuitry includes …” which would fail under Step 2A prong 2 for being a generic computer component that merely automates the abstract idea and does not allow claim 9 to be considered eligible subject matter. Claim 10 and 16 mentions “…wherein the actionable output includes …” which would fail under Step 2A prong 1 for being a continuation of the aforementioned mental process and would not allow claim 10 or 16 to be considered eligible subject matter. Claim 11 and 12 mentions “…processing circuitry…” which would fail under Step 2A prong 2 for being a generic computer component that merely automates the abstract idea and does not allow claim 11 or 12 to be considered eligible subject matter. Claim 14 and 19 mentions “…first snapshot…” which would fail under Step 2A prong 2 for being insignificant extra solution activity within data gathering and would not allow claim 14 to be considered eligible subject matter. Claim 15 and 17 mentions “…the processor…” which would fail under Step 2A prong 2 for being a generic computer component that merely automates the abstract idea and does not allow claim 15 or 17 to be considered eligible subject matter. Claim 20 mentions “…store a snapshot…” which would fail under Step 2A prong 1 for being a mental process and thus would not allow claim 20 to be considered eligible subject matter. Claim 21 mentions “…aircraft controller…” which would fail under Step 2A prong 2 for being a generic computer component that merely automates the abstract idea and does not allow claim 21 to be considered eligible subject matter
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 1, 3, 6-11, and 13-20 are rejected under 35 U.S.C. 103 as being unpatentable over Furlong (US 12,287,714 B2) in view of Cleaver (US 11,283,863 Bl) and in further view of Sturlaugson (US 2024/0086595 Al).
Regarding Claim 1 Furlong teaches An apparatus (Pg. 1 – Abstract – “Techniques for management of virtual representations (e.g., digital twins) of infrastructure are disclosed.” & See Also Pg. 10 – col. 1 – lines 54-55 – “an apparatus with a processor and a memory configured to 55 perform the above steps.”) comprising: interface circuitry to receive input for a query and provide a result of the query as output; (Pg. 12 – col. 5 – lines 46-50 – “That is, when user 240 wishes to simulate changes to a given device 222, user 240 can request digital twin management engine 210 to create/construct (spin up or instantiate) a digital twin of the given device 222 using one or more corresponding images” (equates to interface circuitry to receive input for a query and provide a result of the query as output as the quote shows the user being able to prompt the device 222 with requests regarding the status of the digital twin.) ) memory circuitry to store a plurality of snapshots, (Pg. 6 – Fig. 3B & See Also Pg. 11 – Col. 4 – lines 50-54 – “As shown, a digital twin management engine 210 is operatively coupled to a computing infrastructure network 220, itself comprising a plurality of devices 222-1, 222-2, 222-3, 222-4, ... , 222-N (referred to herein collectively as devices 222 and individually as device 222).” & See Also Pg. 10 – Col. 2 lines 23-24 – “least a portion of an information processing system with digital twin management functionality”& See Also Pg. 15 – Col. 11 – lines 18-20 - “As indicated previously, components of an information processing system as disclosed herein can be implemented at least in part in the form of one or more software programs stored in memory” & See Also Pg. 13 – Col. 7 – lines 9-16 – “FIG. 3A illustrates an exemplary process 300 of artificially aging a digital twin according to an illustrative embodiment. By way of example, process 300 can be executed in accordance with computing environment 200 of FIG. 2. As shown, process 300 involves digital twin management engine 210 and device digital twin 232 at a first 10 time Tl corresponding to a first state of device 222, and at an nth (e.g., second) time Tn corresponding to an nth (e.g., second) state of device 222 (equates to memory circuitry to store a plurality of snapshots as the memory is shown to store software that runs that infrastructure processing system in which the art discloses the system to include a plurality of snapshots of the devices at different time intervals,)) each snapshot including a plurality of digital twin models interconnected by a plurality of connections to form a network of digital twins, (pg. 4 – Fig. 2 & See Also Pg. 6 – Fig. 3B & See Also Pg. 13 – col. 8 – lines 28-33 – “devices 222-1, 222-2, and 222-(individually referred to in the context of FIG. 3B as device 222), and at an nth (e.g., second) time Tn corresponding to an nth ( e.g., second) state of device 222. Note that a counter 302 in device digital twin 232 can be used to maintain the time instance associated with each state of device 222 that device digital twin 232 is virtually representing” & See Also Pg. 12 – Col. 5 – lines 8-22 – “Device digital twins 232 respectively correspond to devices 222 in 10 computing infrastructure network 220, i.e., there is a device digital twin 232 that virtually represents a device 222 (e.g., device digital twin 232-1 virtually represents device 222-1, ... , device digital twin 232-N virtually represents device 222-N). Note, however, that while FIG. 2 illustrates 15 a one-to-one correspondence between devices 222-1, 222-2, 222-3, 222-4, ... , 222-N and device digital twins 232-1, 232-2, 232-3, 232-4, ... , 232-N, alternative embodiments may comprise alternative correspondences, e.g., a single device digital twin 232 can represent more than one of 20 devices 222, more than one of device digital twins 232 can represent a single device 222, etc.” (equates to each snapshot including a plurality of digital twin models interconnected by a plurality of connections to form a network of digital twins as the quote shows the counter keeping track of the time change between the device at two instances and thus a snapshot is formed between the digital twin models and the last quote shows how this can be scaled for up to n devices that can undergo the same time change for each of the plurality of snapshots. A network of digital twins is formed as the fig. 2 included shows the digital twin network of up to N devices. )) each snapshot representing a state of the digital twin models at the specified point in time, (Pg. 14 – Col. 9 – lines 10-17 – “FIG. 4, a methodology 400 is illustrate for artificially aging a digital twin to facilitate debugging of an infrastructure according to an illustrative embodiment. It is to be understood that, in illustrative embodiments, methodology 400 is performed by computing environment 200 of FIG. 2. As shown, step 402 obtains at least one virtual representation of an infrastructure, wherein the virtual representation represents the infrastructure in a first state.” & See Also Pg. 14 – Col. 9 – lines 17-20 – “Step 404 applies at least one dataset to the virtual representation to artificially advance the virtual representation to represent the infrastructure in a second state” & See Also Pg. 7 – Fig. 4 (equates to each snapshot representing a state of the digital twin models at the specified point in time as the quote show the infrastructure being converted into a digital twin that undergoes aging in the computer processing environment wherein the infrastructure is represented by snapshots of its condition at points in time as seen from the quotes and figures.)) the memory circuitry arranged to enable identification and processing of one or more snapshots in response to the query; (Pg. 12 – Col. 5 – lines 44-50 – “In one or more illustrative embodiments, by way of example only, assume that a given device digital twin 232 is needed/desired for on-demand simulations. That is, when user 240 wishes to simulate changes to a given device 222, user 240 can request digital twin management engine 210 to create/construct (spin up or instantiate) a digital twin of the given device 222 using one or more corresponding image” & See Also Pg. 15 – Col. 11 – lines 18-20 - “As indicated previously, components of an information processing system as disclosed herein can be implemented at least in part in the form of one or more software programs stored in memory” & See Also Pg. 10 – Col. 1 – lines 65-67 – “Based on results generated in accordance with the digital twin, one or more debugging actions can be initiated with respect to the infrastructure” (equates to the memory circuitry arranged to enable identification and processing of one or more snapshots in response to the query as the first and third quotes show a request being processed by the computing system from a user and thus a query is formed wherein the system can then identify issues and output an action for the user to take based on the requested aging process for the digital twin component and thus identification is had based on the ability to output an action. The Second quote shows the memory of this art being able to execute the components of the processing system as previously mentioned.) ) the processing circuitry to process the query to search the memory circuitry, (Pg. 9 – Fig. 6 & See Also Pg. 14 – Col. 10 lines 39-40 – “The processing device 602-1 in the processing platform 600 comprises a processor 610 coupled to a memory 612.”) the processing circuitry to identify, in response to the query, at least a first snapshot representing the plurality of digital twin models and interconnections at a first point in time and a second snapshot representing the plurality of digital twin models and interconnections at a second point in time (Pg. 12 – Col. 5 – lines 46- 52 – “That is, when user 240 wishes to simulate changes to a given device 222, user 240 can request digital twin management engine 210 to create/construct (spin up or instantiate) a digital twin of the given device 222 using one or more corresponding images (e.g., snapshots or the like) from a device image datastore” & See Also Pg. 12 – Col. 5 – lines 59- 63 - “Digital twin management engine 210 matches the specifications of the given device 222 and load the one or more corresponding images to create a virtual representation ( device digital twin 232) for a specific fidelity (resolution) of the given device 222.” & See Also Pg. 14 – Col.10 lines – 27-28 – “The processing platform 600 in this embodiment comprises a portion of computing environment 200” & See Also Pg. 14 – Col.10 – lines 39- 40 – “The processing device 602-1 in the processing platform 600 comprises a processor 610” & See Also Pg. 11 – Col. 4 – lines 47-51 – “a computing environment 200 is depicted within which illustrative embodiments described herein are implemented. As shown, a digital twin management engine 210 is operatively coupled to a computing infrastructure network 220” & See Also Pg. 11 – Col. 4 – lines 50-53 – “Referring now to FIG. 2, a computing environment 200 is depicted within which illustrative embodiments described herein are implemented. As shown, a digital twin management engine 210 is operatively coupled to a computing infrastructure network 220, itself comprising a plurality of devices 222-1, 222-2, 222-3, 222-4, ... , 222-N” & See Also Pg. 13 – Col. 7 – lines 9-16 – “FIG. 3A illustrates an exemplary process 300 of artificially aging a digital twin according to an illustrative embodiment. By way of example, process 300 can be executed in accordance with computing environment 200 of FIG. 2. As shown, process 300 involves digital twin management engine 210 and device digital twin 232 at a first 10 time Tl corresponding to a first state of device 222, and at an nth (e.g., second) time Tn corresponding to an nth (e.g., second) state of device 222. Note that a counter 302 in device digital twin 232 can be used to maintain the time instance associated with each state of device 222 that device 15 digital twin 232 is virtually representing” & See Also Pg. 4 – Fig.2 & See Also Pg. 5 – Fig. 3A (equates to the processing circuitry to identify, in response to the query, at least a first snapshot representing the plurality of digital twin models and interconnections at a first point in time and a second snapshot representing the plurality of digital twin models and interconnections at a second point in time as the first quote shows a request to construct the digital twin and thus a query is formed wherein the one or more corresponding images or snapshots is identified by the digital twin management engine, and all is done by the processing circuitry as the processor is an integral part of the computing environment which stores the digital twin management engine. The last quote shows the change being generated within the digital twin is done via a time change as a first state or first snapshot and a nth state or second snapshot is seen within. )) the processing circuitry to determine a correlation between the first snapshot and the second snapshot and generate the result with an actionable output based on the correlation. (Pg. 12 – Col. 6 – lines – 51-63 – “Once operational, models used to create the device digital twin 232 can be augmented with additional input created through the observation of the device digital twin 232 itself. During the operation of the device digital twin 232, the performance, behavior, and physical state of the device digital twin 232 changes. These changes are captured and then reflected in future iterations of the digital twin models ( e.g., training process). These changes are validated by the similar behavior and operation of the corresponding device 222 itself. At any point in time, the models deployed to the device digital twin 232 are representative of the codification of the behavior and operational state of the corresponding device 222. New models are created which instantiate the changes to the performance, operation, and physical state of the device digital twin 232 that occur over time. These new models can then be used in a feedback loop. Based on results generated in accordance with the digital twin, one or more debugging actions can be initiated with respect to the infrastructure” & see Also Pg. 12 – Col. 5 – lines 46- 52 – “That is, when user 240 wishes to simulate changes to a given device 222, user 240 can request digital twin management engine 210 to create/construct (spin up or instantiate) a digital twin of the given device 222 using one or more corresponding images (e.g., snapshots or the like) from a device image datastore” (equates to the processing circuitry to determine a correlation between the first snapshot and the second snapshot and generate the result with an actionable output based on the correlation as the processing circuitry has already been linked to the computing environment that manages the configuration of this cited art’s apparatus, wherein the first quote shows how changes in the digital twin model are seen over time and based on the changes within the model debugging actions can be given. The changes of the digital twin model equate to this application’s correlation between the snapshots as the second quote is showing images or snapshots of this model that that the debugging actions would be based on. ) ) the processing circuitry to output the result to an external device for execution with respect to the actionable output (Pg. 13 – Col. 8 – lines 55-67 & Pg. 14 – Col. 9 – lines 1-2 – “It is assumed that the goal is that device digital twin 23 2 represent the state (e.g., hardware, software, and/or data configurations) of device 222 at Tn. Digital twin management engine 210 then receives device-related results (e.g., results of execution of one or more physics-based models 110, the one or more AI-driven models 112, the one or more simulations 114, the one or more analytics 116, and/or the one or more predictions 118 that constitute device digital twin 232) from device digital twin 232 at time Tn. Digital twin management engine 210 then sends some or all of the device-related results received from device digital twin 232 to a debug technician (tech) and/or a debug system 320. Debug tech/system 320 can then initiate or otherwise take one or more debugging actions in response to at least a portion of the received results.” (equates to the processing circuitry to output the result to an external device for execution with respect to the actionable output as the quote provided shows an actionable output being received by a debug tech via results wherein debugging actions can take place or the actionable output can be utilized. The external system is seen via the debug system being different from the digital twin management engine.))
Yet Furlong fails to teach the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset, the plurality of connections including a first connection between the first digital twin model and the second digital twin model, the first connection representing a relationship between the first digital twin model and the second digital twin model at a specified point in time. and processing circuitry to model, track, analyze, and adjust aircraft assets, to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset.
Cleaver discloses a similar apparatus (abstract). Cleaver discloses the plurality of connections including a first connection between the first digital twin model and the second digital twin model (Pg. 11 – Col. 1 – lines 58-64 – “The digital twins process invention. workloads and the digital twins communicate with each other. The hardware manager identifies an impact on a 60 number of parameters that a first set of the digital twins has on a second set of the digital twins. The hardware manager performs a set of actions based on the impact on the number of parameters” (equates to the plurality of connections including a first connection between the first digital twin model and the second digital twin model as the quote shows communication between digital twins as well as impact assessment on one set of digitals twins versus the other thus the connection is either the impact or the communication between a first and second model disclosed above.)) the first connection representing a relationship between the first digital twin model and the second digital twin model at a specified point in time. (Pg. 20 – Col. 20 – lines 32-38 – “With the use of real-time data 700, a near real-time comprehensive linkage between physical and virtual devices can be enabled. This type of linkage can increase the insights in determining impacts occurring on physical devices 412. As a result, this information along with the interconnection of digital twins 410 can help provide optimized management of physical devices 412.” & see also Pg. 15 – Col. 10 – lines 8 – 17 – “Real-time data 336 can be sent from data center 330 to network manager 332 over network 102. In turn, network manager 332 can send or relay real-time data 336 to digital twins 334. In other illustrative examples, real-time data 336 can be sent directly from data center 330 to digital twins 334. In this illustrative example, real-time data 336 is data that is sent as quickly as possible without any intentional delay. Real-time data 336 provides near real-time linkage between digital twins 334 and the physical objects or systems and data center 330” (equates to the first connection representing a relationship between the first digital twin model and the second digital twin model at a specified point in time as the first quote shows how the digital twins utilize the real time data in relation to the physical object it represents as well as, the connection between digital twins. Wherein quote 2 further explains the digital twins receiving real time data and its linkage between the physical objects and digital twin. )).
Yet both Furlong- Cleaver fail to teach the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset. and processing circuitry to model, track, analyze, and adjust aircraft assets, to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset.
Sturlaugson teaches the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset. (Pg. 15 – [0060] – “illustrates a block diagram of the digital twin system 406, according to an exemplary embodiment. The digital twin system 406 may be configured to monitor, assess, track, and/or indicate the state or condition of one or more systems, subsystems, and/or components of a vehicle... to generate or receive a digital twin of a subsystem to enable the determination of the state or condition of the subsystem (e.g., current condition). The subsystem may include one of the subsystems 212 of the aircraft 204.” (equates to the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset as the quote shows the plurality of subsystems of the aircraft being under monitor via a digital twin system.)) and processing circuitry to model, track, analyze, and adjust aircraft assets, (Pg. 15 – [0060] – “illustrates a block diagram of the digital twin system 406, according to an exemplary embodiment. The digital twin system 406 may be configured to monitor, assess, track, and/or indicate the state or condition of one or more systems, subsystems, and/or components of a vehicle... to generate or receive a digital twin of a subsystem to enable the determination of the state or condition of the subsystem (e.g., current condition). The subsystem may include one of the subsystems 212 of the aircraft 204. Further, the digital twin system 406 may be configured to update or synchronize the digital twin of the subsystem.” (equates to the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset as the quote shows modeling tracking and assess condition or analyzation being done to the aircraft digital twin and lastly an updating step equivalent to the adjustment of this application.) ) to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset. (Pg. 15 – [0060] – “Further, the digital twin system 406 may be configured to update or synchronize the digital twin of the subsystem. For example, the digital twin system 406 may update or synchronize the digital twin to correspond to the current state of the subsystem as further described below. The digital twin may be a digital or virtual representation of a state or condition of the subsystem. For example, the digital twin may represent an operational or performance state or condition of the subsystem of the vehicle 104.” (equates to: to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset as the quote shows the updating (adjustment) of a digital twin monitoring a subsystem (first aircraft asset).) It would have been an advantageous addition to the system disclosed by Furlong-Cleaver to include the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset. and processing circuitry to model, track, analyze, and adjust aircraft assets, to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset as these limitations allows for aircraft components to be directly under monitoring and updating via the digital twin network wherein changes can be made to the digital twins based on monitoring the status of the subsystem providing up to date information .
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to include the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset. and processing circuitry to model, track, analyze, and adjust aircraft assets, to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset as this allows for real time information regarding the condition and health of the aircraft asset to be stored within a virtual representation of a physical system allowing for past and current issues of the subsystem to be readily understood.
Regarding Claim 3 Furlong- Cleaver- Sturlaugson teaches (Furlong discloses the following limitations:) The apparatus of claim 1, wherein the correlation includes at least one of i) a change from the first snapshot to the second snapshot over time or ii) a commonality between the first snapshot and the second snapshot. (Pg. 13 – Col. 7 – lines 9-13 – “As shown, process 300 involves digital twin management engine 210 and device digital twin 232 at a first 10 time Tl corresponding to a first state of device 222, and at an nth (e.g., second) time Tn corresponding to an nth (e.g., second) state of device 222. Note that a counter 302 in device digital twin 232 can be used to maintain the time instance associated with each state of device 222 that device 15 digital twin 232 is virtually representing” (equates to wherein the correlation includes at least one of i) a change from the first snapshot to the second snapshot over time as the quote shows a process being implemented that tracks a digital twin at two time points and thus a change from the first snapshot to the second is had)).
Regarding Claim 6 Furlong-Cleaver teaches The apparatus of claim 1, as previously mapped above.
Yet Furlong-Cleaver fails to teach wherein the plurality of digital twin models include at least one of an engine digital twin model, a landing gear digital twin model, a controller digital twin model, an airframe digital twin model, or an aircraft digital twin model.
Sturlaugson teaches a similar apparatus (abstract). Sturlaugson teaches wherein the plurality of digital twin models include at least one of an engine digital twin model, a landing gear digital twin model, a controller digital twin model, an airframe digital twin model, or an aircraft digital twin model (Pg. 14 – [0044] – “The digital twin system 106 may also monitor the state or condition of the subsystems 112 of the vehicle 104 based on the digital twins 118 of the subsystems 112. When the digital twin system 106 determines a fault or degraded condition or state of a subsystem based on the digital twins of the subsystems 112, the digital twin system 106 may take a responsive action, such as by scheduling maintenance for the vehicle 104, notifying an operator, or the like” & see Also Pg. 14 – [0045] – “FIG. 2 illustrates a block diagram of the vehicle 104 of FIG. 1. The vehicle 104 may be an aircraft 204… the aircraft 204 may include a control system 210 or monitoring system, an airframe 211, an interior 214, and a plurality of subsystems 212” & see Also Pg. 14 – [0046] – “Each of the subsystems 212 may include one or more components (not shown) that together may perform the functions of the subsystems 212. The components may be electrical, optical, mechanical, hydraulic, fluidic, pneumatic, structural, and/or aerodynamic components. For example, the components may include actuators, servomechanisms, engines,” (equates to , wherein the aircraft digital twin model includes the engine digital twin model as the digital twin monitors subsystems of the vehicle wherein the vehicle can be an aircraft with engine as seen from the quotes in which the digital twin monitors the engine.)). It would have been an advantageous addition to the apparatus disclosed by Furlong-Cleaver to include wherein the plurality of digital twin models include at least one of an engine digital twin model, a landing gear digital twin model, a controller digital twin model, an airframe digital twin model, or an aircraft digital twin model as this would have been their apparatus more versatile and suited for aircraft type environment allowing for a more robust apparatus to be had.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to include wherein the plurality of digital twin models include at least one of an engine digital twin model, a landing gear digital twin model, a controller digital twin model, an airframe digital twin model, or an aircraft digital twin model as this limitation ensures the apparatus can be used to manage health of aircraft and make the machine available to a wider variety of industries.
Regarding Claim 7 Furlong- Cleaver-Sturlaugson teaches (Furlong discloses the following limitations:) The apparatus of claim 6, the controller digital twin model (Pg. 11 – Col 4 – lines 47- 64 - “Referring now to FIG. 2, a computing environment 200 is depicted within which illustrative embodiments described herein are implemented. As shown, a digital twin management engine 210 is operatively coupled to a computing infrastructure network 220, itself comprising a plurality of devices 222-1, 222-2, 222-3, 222-4, ... , 222-N (referred to herein collectively as devices 222 and individually as device 222). Each device 222 individually or devices 222 collectively can be considered infrastructure ( e.g., infrastructure 102 in FIG. 1). Devices 222 may comprise a wide variety of devices associated with computing infrastructure network 220 including, but not limited to, smart phones, laptops, other mobile devices, personal computers (PC), servers ( e.g., edge or otherwise), CPUs, GPU, gateways, Internet of Thing (IoT) devices, storage arrays, memory devices, routers, switches, appliances, and other computing devices that are part of or otherwise associated with computing infrastructure network 220.” (equates to the controller digital twin model as the various devices listed can be a part of the controller or act as a controller if programmed as such.))
Yet Furlong-Cleaver fails to teach wherein the aircraft digital twin model includes the engine digital twin model, the landing gear digital twin mode, and the airframe digital twin model.
Sturlaugson teaches a similar apparatus (abstract). Sturlaugson teaches wherein the aircraft digital twin model includes the engine digital twin model, (Pg. 14 – [0044] – “The digital twin system 106 may also monitor the state or condition of the subsystems 112 of the vehicle 104 based on the digital twins 118 of the subsystems 112. When the digital twin system 106 determines a fault or degraded condition or state of a subsystem based on the digital twins of the subsystems 112, the digital twin system 106 may take a responsive action, such as by scheduling maintenance for the vehicle 104, notifying an operator, or the like” & see Also Pg. 14 – [0045] – “FIG. 2 illustrates a block diagram of the vehicle 104 of FIG. 1. The vehicle 104 may be an aircraft 204… the aircraft 204 may include a control system 210 or monitoring system, an airframe 211, an interior 214, and a plurality of subsystems 212” & see Also Pg. 14 – [0046] – “Each of the subsystems 212 may include one or more components (not shown) that together may perform the functions of the subsystems 212. The components may be electrical, optical, mechanical, hydraulic, fluidic, pneumatic, structural, and/or aerodynamic components. For example, the components may include actuators, servomechanisms, engines,” (equates to , wherein the aircraft digital twin model includes the engine digital twin model as the digital twin monitors subsystems of the vehicle wherein the vehicle can be an aircraft with engine as seen from the quotes in which the digital twin monitors the engine.)) the landing gear digital twin model, (Pg. 14 – [0044] – “The digital twin system 106 may also monitor the state or condition of the subsystems 112 of the vehicle 104 based on the digital twins 118 of the subsystems 112. When the digital twin system 106 determines a fault or degraded condition or state of a subsystem based on the digital twins of the subsystems 112, the digital twin system 106 may take a responsive action, such as by scheduling maintenance for the vehicle 104, notifying an operator, or the like” & see Also Pg. 14 – [0045] – “FIG. 2 illustrates a block diagram of the vehicle 104 of FIG. 1. The vehicle 104 may be an aircraft 204… the aircraft 204 may include a control system 210 or monitoring system, an airframe 211, an interior 214, and a plurality of subsystems 212” & see Also Pg. 14 – [0046] – “Each of the subsystems 212 may include one or more components (not shown) that together may perform the functions of the subsystems 212. The components may be electrical, optical, mechanical, hydraulic, fluidic, pneumatic, structural, and/or aerodynamic components. For example, the components may include actuators, servomechanisms, engines, motors, electronics modules, pumps, valves, and airframe members. The components may be associated with external portions of the aircraft 204 such as flight control surfaces, landing gear, etc.” (equates to wherein the aircraft digital twin model includes the landing gear digital twin model as the digital twin monitors subsystems of the vehicle wherein the vehicle can be an aircraft with landing gear as seen from the quotes.)), and the airframe digital twin model. Pg. 14 – [0044] – “The digital twin system 106 may also monitor the state or condition of the subsystems 112 of the vehicle 104 based on the digital twins 118 of the subsystems 112. When the digital twin system 106 determines a fault or degraded condition or state of a subsystem based on the digital twins of the subsystems 112, the digital twin system 106 may take a responsive action, such as by scheduling maintenance for the vehicle 104, notifying an operator, or the like” & see Also Pg. 14 – [0045] – “FIG. 2 illustrates a block diagram of the vehicle 104 of FIG. 1. The vehicle 104 may be an aircraft 204… the aircraft 204 may include a control system 210 or monitoring system, an airframe 211, an interior 214, and a plurality of subsystems 212” & see Also Pg. 14 – [0046] – “Each of the subsystems 212 may include one or more components (not shown) that together may perform the functions of the subsystems 212. The components may be electrical, optical, mechanical, hydraulic, fluidic, pneumatic, structural, and/or aerodynamic components. For example, the components may include actuators, servomechanisms, engines, motors, electronics modules, pumps, valves, and airframe members” (equates to , wherein the aircraft digital twin model includes the airframe digital twin model as the digital twin monitors subsystems of the vehicle wherein the vehicle can be an aircraft with engine as seen from the quotes in which the digital twin monitors the airframe members.)) It would have been an advantageous addition to the apparatus disclosed by Furlong-Cleaver to include wherein the plurality of digital twin models include at least one of an engine digital twin model, a landing gear digital twin model, a controller digital twin model, an airframe digital twin model, or an aircraft digital twin model as this would have been their apparatus more versatile and suited for aircraft type environment allowing for a more robust apparatus to be had.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to include wherein the plurality of digital twin models include at least one of an engine digital twin model, a landing gear digital twin model, a controller digital twin model, an airframe digital twin model, or an aircraft digital twin model as this limitation ensures the apparatus can be used to manage health of aircraft and make the machine available to a wider variety of industries.
Regarding Claim 8 Furlong-Cleaver-Sturlaugson teaches The apparatus of claim 7, as previously mapped above.
Yet Furlong-Cleaver fails to teach wherein the aircraft digital twin model is part of a fleet of aircraft digital twin models.
Sturlaugson teaches a similar apparatus (abstract). Sturlaugson teaches wherein the aircraft digital twin model is part of a fleet of aircraft digital twin models. (Pg. 13 – [0037] – “the digital twin system 106 may be associated with a plurality of vehicles ( e.g., a fleet of vehicles)” & See Also Pg. 14 – [0045] – “FIG. 2 illustrates a block diagram of the vehicle 104 of FIG. 1. The vehicle 104 may be an aircraft 204” (equates to wherein the aircraft digital twin model is part of a fleet of aircraft digital twin models as the quote shows the digital twins being related to a plurality of vehicles and a fleet of them and the vehicle being and aircraft.)). It would have been an advantageous addition to the apparatus disclosed by Furlong-Cleaver to include wherein the aircraft digital twin model is part of a fleet of aircraft digital twin models as this would allow the aforementioned device to be able to work within a commercial airline setting and monitor a plethora of aircraft leading to a wider variety of use cases.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to include wherein the aircraft digital twin model is part of a fleet of aircraft digital twin models as this allows for a wide array of expensive vehicles to be monitored quickly and efficiently and thus allowing for a profitable product if it can manage and keep track of aircraft type vehicles within a fleet.
Regarding Claim 9 Furlong- Cleaver- Sturlaugson teaches (Furlong discloses the following limitations: )The apparatus of claim 1, wherein the memory circuitry includes a plurality of containers organizing the plurality of digital twin models. (Pg. 13 – col. 7 – lines 7-13 – “By way of example, process 300 can be executed in accordance with computing environment 200 of FIG. 2. As shown, process 300 involves digital twin management engine 210 and device digital twin 232 at a first 10 time Tl corresponding to a first state of device 222, and at an nth (e.g., second) time Tn corresponding to an nth (e.g., second) state of device 222” & see Also Pg. 14 – Col. 9 – lines 62-66 – “FIG. 5 shows an example processing platform comprising cloud infrastructure 500. The cloud infrastructure 500 comprises a combination of physical and virtual processing resources that may be utilized to implement at least a portion of computing environment 200” & See Also Pg. 14 – Col. 10 – lines 6-9 – “The cloud infrastructure 500 further comprises sets of applications 510-1, 510-2, ... 510-L running on respective ones of the VM/container sets 502-1, 502-2, ... 502-L under the control of the virtualization infrastructure 504” (equates to wherein the memory circuitry includes a plurality of containers organizing the plurality of digital twin models as the quote shows the computing environment which houses the monitoring and updating of the digital twins has a cloud infrastructure where data is stored in containers.))
Regarding Claim 10 Furlong-Cleaver-Sturlaugson teaches The apparatus of claim 9, as mapped above previously.
Yet Furlong- Cleaver fails to specifically teach wherein the actionable output includes at least one of i) triggering maintenance for at least one of the first asset or the second asset, ii) monitoring at least one of the first asset or the second asset, or iii) reconfiguring at least one of the first asset or the second asset.
Sturlaugson teaches a similar apparatus (abstract). Sturlaugson teaches wherein the actionable output includes at least one of i) triggering maintenance for at least one of the first aircraft asset or the second aircraft asset, ii) monitoring at least one of the first aircraft asset or the second aircraft asset, or iii) reconfiguring at least one of the first asset or the second aircraft asset. (Pg. 10 – [0005] – “Physics or model-based methods may be used to generate a state or condition of an operative subsystem of an aircraft…If a fault is detected, the model-based methods may output a sequence of action or maintenance items” & See Also Pg. 14 – [0044] – “determines a fault or degraded condition or state of a subsystem based on the digital twins of the subsystems 112, the digital twin system 106 may take a responsive action, such as by scheduling maintenance for the vehicle 104, notifying an operator” (equates to wherein the actionable output includes at least one of i) triggering maintenance for at least one of the first asset or the second asset as the quotes show the system checking the health of the subsystems of the vehicle and when some subsystem isn’t fully up to standard an output in the form of a notification to the operator is made regarding a maintenance event. )). It would have been an advantageous addition to the apparatus disclosed by Furlong- Cleaver to include wherein the actionable output includes at least one of i) triggering maintenance for at least one of the first asset or the second asset, ii) monitoring at least one of the first asset or the second asset, or iii) reconfiguring at least one of the first asset or the second asset as this would allow the apparatus of Furlong-Cleaver to specifically include particular maintenance needed based on real world data of the subsystem rather than purely forward looking as is done within the artificial aging allowing for up to date conditions to be understood and corrected if need be.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to include wherein the actionable output includes at least one of i) triggering maintenance for at least one of the first asset or the second asset, ii) monitoring at least one of the first asset or the second asset, or iii) reconfiguring at least one of the first asset or the second asset as the ability to trigger a maintenance event on particular assets allows for up to date condition to be understood and immediately corrected upon a simple query into the digital twin management system allowing for more real time data to be seen and maintain the actual part if needed.
Regarding Claim 11 Furlong-Cleaver- Sturlaugson teaches (Furlong Discloses the following limitations) The apparatus of claim 1, and wherein creation of the change event triggers the processing circuitry to process the change event to: (Pg. 13 – Col. 8 – Lines 12 -19 – “apply a change to device digital twin 232 to replicate application of the change to device 222. Applying a change to device digital twin 232 to replicate application of the change to device 222 may further comprise receiving the change to be applied to device digital twin 232 and then executing the change. In some embodiments, the change may be defined via a script or a command line issued by digital twin management” & See Also Pg. 10 – Col. 1 – lines 52-54 – “executable program code that when executed by a processor causes the processor to perform the above steps”) ingest the change event, (Pg. 12 – Col. 6 – lines – 51-63 – “Once operational, models used to create the device digital twin 232 can be augmented with additional input created through the observation of the device digital twin 232 itself. During the operation of the device digital twin 232, the performance, behavior, and physical state of the device digital twin 232 changes. These changes are captured and then reflected in future iterations of the digital twin models ( e.g., training process). These changes are validated by the similar behavior and operation of the corresponding device 222 itself. At any point in time, the models deployed to the device digital twin 232 are representative of the codification of the behavior and operational state of the corresponding device 222. New models are created which instantiate the changes to the performance, operation, and physical state of the device digital twin 232 that occur over time. These new models can then be used in a feedback loop. Based on results generated in accordance with the digital twin, one or more debugging actions can be initiated with respect to the infrastructure” & See Also Pg. 10 – Col. 1 – lines 51-56 – “…storage medium having embodied therein executable program code that when executed by a processor causes the processor to perform the above steps… apparatus with a processor and a memory configured to 55 perform the above steps.” (equates to ingest the change event as the digital twins are undergoing changes by way of the training process disclosed above and are executed by the apparatus and storage medium as seen from the second quote thus ingested.))) store a third snapshot of the plurality of digital twin models based on the change event, (Pg. 12 – Col. 6 – lines 54-58 – “During the operation of the device digital twin 232, the 55 performance, behavior, and physical state of the device digital twin 232 changes. These changes are captured and then reflected in future iterations of the digital twin models ( e.g., training process)” (equates to store a third snapshot of the plurality of digital twin models based on the change event as the quote shows that once a change event is carried through on the digital twin model this is captured and used later in their training process and thus a third snapshot is captured based on the change event. )) and facilitate querying based on the change event (Pg. 12 – Col. 5 – lines 44-50 – “In one or more illustrative embodiments, by way of example only, assume that a given device digital twin 232 is needed/desired for on-demand simulations. That is, when user 240 wishes to simulate changes to a given device 222, user 240 can request digital twin management engine 210 to create/construct (spin up or instantiate) a digital twin of the given device 222” (Equates to and facilitate querying based on the change event as the user is querying the system to facilitate a change event and this the apparatus allows querying based on change events.))
Yet Furlong-Cleaver fail to teach wherein a change in at least one of the first aircraft asset or the second aircraft asset is captured as a change event,
Sturlaugson teaches wherein a change in at least one of the first aircraft asset or the second aircraft asset is captured as a change event, (Pg. 15 – [0058] – “For example, the controller 354 may update or change the digital twin to correspond to the current state of the environmental control system 340 based on the output or simulation data generated by the digital system model of the subsystem” ) It would have been an advantageous addition to the system disclosed by Furlong-Cleaver to include wherein a change in at least one of the first aircraft asset or the second aircraft asset is captured as a change event, as this allows for the change event to be specifically designed toa component relating to the aircraft system and allows for a variety of subsystems within an aircraft to be monitored.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to include wherein a change in at least one of the first aircraft asset or the second aircraft asset is captured as a change event, as this allows for updating of the aircraft components to be realized on a digital twin system allowing for the condition to be understood and catalogued throughout the physical components lifecycle in a simple virtual way.
Regarding Claim 13 Furlong teaches A non-transitory computer readable storage medium comprising instructions which, (Pg. 10 – col. 1 – lines 50-54 – “Further illustrative embodiments are provided in the form of a non-transitory computer-readable storage medium having embodied therein executable program code that when executed by a processor causes the processor to perform the above steps.”) when executed, cause a processor to at least: process a query to search a plurality of snapshots, (Pg. 12 – Col. 5 – lines 46-53 – “That is, when user 240 wishes to simulate changes to a given device 222, user 240 can request digital twin management engine 210 to create/construct (spin up or instantiate) a digital twin of the given device 222 using one or more corresponding images (e.g., snapshots or the like) from a device image datastore (not expressly shown) augmented with real-time data associated with the given device 222” & See Also Pg. 14 – Col.10 lines – 27-28 – “The processing platform 600 in this embodiment comprises a portion of computing environment 200” & See Also Pg. 14 – Col.10 – lines 39- 40 – “The processing device 602-1 in the processing platform 600 comprises a processor 610” & See Also Pg. 11 – Col. 4 – lines 47-51 – “a computing environment 200 is depicted within which illustrative embodiments described herein are implemented. As shown, a digital twin management engine 210 is operatively coupled to a computing infrastructure network 220” (equates to when executed, cause a processor to at least: process a query to search a plurality of snapshots as the processor is shown to be coupled to the computing environment in which the digital twin management system existing within to search for the snapshots as the first quote shows how based on request construct the plurality of snapshots from the database and thus search for them to do so. )) each snapshot including a plurality of digital twin models interconnected by a plurality of connections to form a network of digital twins, (pg. 4 – Fig. 2 & See Also Pg. 6 – Fig. 3B & See Also Pg. 13 – col. 8 – lines 28-33 – “devices 222-1, 222-2, and 222-(individually referred to in the context of FIG. 3B as device 222), and at an nth (e.g., second) time Tn corresponding to an nth ( e.g., second) state of device 222. Note that a counter 302 in device digital twin 232 can be used to maintain the time instance associated with each state of device 222 that device digital twin 232 is virtually representing” & See Also Pg. 12 – Col. 5 – lines 8-22 – “Device digital twins 232 respectively correspond to devices 222 in 10 computing infrastructure network 220, i.e., there is a device digital twin 232 that virtually represents a device 222 (e.g., device digital twin 232-1 virtually represents device 222-1, ... , device digital twin 232-N virtually represents device 222-N). Note, however, that while FIG. 2 illustrates 15 a one-to-one correspondence between devices 222-1, 222-2, 222-3, 222-4, ... , 222-N and device digital twins 232-1, 232-2, 232-3, 232-4, ... , 232-N, alternative embodiments may comprise alternative correspondences, e.g., a single device digital twin 232 can represent more than one of 20 devices 222, more than one of device digital twins 232 can represent a single device 222, etc.” (equates to each snapshot including a plurality of digital twin models interconnected by a plurality of connections to form a network of digital twins as the quote shows the counter keeping track of the time change between the device at two instances and thus a snapshot is formed between the digital twin models and the last quote shows how this can be scaled for up to n devices that can undergo the same time change for each of the plurality of snapshots. A network of digital twins is formed as the fig. 2 included shows the digital twin network of up to N devices. )) each snapshot representing a state of the digital twin models at the specified point in time; (Pg. 14 – Col. 9 – lines 10-17 – “FIG. 4, a methodology 400 is illustrate for artificially aging a digital twin to facilitate debugging of an infrastructure according to an illustrative embodiment. It is to be understood that, in illustrative embodiments, methodology 400 is performed by computing environment 200 of FIG. 2. As shown, step 402 obtains at least one virtual representation of an infrastructure, wherein the virtual representation represents the infrastructure in a first state.” & See Also Pg. 14 – Col. 9 – lines 17-20 – “Step 404 applies at least one dataset to the virtual representation to artificially advance the virtual representation to represent the infrastructure in a second state” & See Also Pg. 7 – Fig. 4 (equates to each snapshot representing a state of the digital twin models at the specified point in time as the quote show the infrastructure being converted into a digital twin that undergoes aging in the computer processing environment wherein the infrastructure is represented by snapshots of its condition at points in time as seen from the quotes and figures.)) identify in response to the query; at least a first snapshot representing the plurality of digital twin models and interconnections at a first point in time and a second snapshot representing the plurality of digital twin models and interconnections at a second point in time (Pg. 12 – Col. 5 – lines 46- 52 – “That is, when user 240 wishes to simulate changes to a given device 222, user 240 can request digital twin management engine 210 to create/construct (spin up or instantiate) a digital twin of the given device 222 using one or more corresponding images (e.g., snapshots or the like) from a device image datastore” & See Also Pg. 12 – Col. 5 – lines 59- 63 - “Digital twin management engine 210 matches the specifications of the given device 222 and load the one or more corresponding images to create a virtual representation ( device digital twin 232) for a specific fidelity (resolution) of the given device 222.” & See Also Pg. 14 – Col.10 lines – 27-28 – “The processing platform 600 in this embodiment comprises a portion of computing environment 200” & See Also Pg. 14 – Col.10 – lines 39- 40 – “The processing device 602-1 in the processing platform 600 comprises a processor 610” & See Also Pg. 11 – Col. 4 – lines 47-51 – “a computing environment 200 is depicted within which illustrative embodiments described herein are implemented. As shown, a digital twin management engine 210 is operatively coupled to a computing infrastructure network 220” & See Also Pg. 11 – Col. 4 – lines 50-53 – “Referring now to FIG. 2, a computing environment 200 is depicted within which illustrative embodiments described herein are implemented. As shown, a digital twin management engine 210 is operatively coupled to a computing infrastructure network 220, itself comprising a plurality of devices 222-1, 222-2, 222-3, 222-4, ... , 222-N” & See Also Pg. 13 – Col. 7 – lines 9-16 – “FIG. 3A illustrates an exemplary process 300 of artificially aging a digital twin according to an illustrative embodiment. By way of example, process 300 can be executed in accordance with computing environment 200 of FIG. 2. As shown, process 300 involves digital twin management engine 210 and device digital twin 232 at a first 10 time Tl corresponding to a first state of device 222, and at an nth (e.g., second) time Tn corresponding to an nth (e.g., second) state of device 222. Note that a counter 302 in device digital twin 232 can be used to maintain the time instance associated with each state of device 222 that device 15 digital twin 232 is virtually representing” & See Also Pg. 4 – Fig.2 & See Also Pg. 5 – Fig. 3A (equates to the processing circuitry to identify, in response to the query, at least a first snapshot representing the plurality of digital twin models and interconnections at a first point in time and a second snapshot representing the plurality of digital twin models and interconnections at a second point in time as the first quote shows a request to construct the digital twin and thus a query is formed wherein the one or more corresponding images or snapshots is identified by the digital twin management engine, and all is done by the processing circuitry as the processor is an integral part of the computing environment which stores the digital twin management engine. The last quote shows the change being generated within the digital twin is done via a time change as a first state or first snapshot and a nth state or second snapshot is seen within. )) determine a correlation between the first snapshot and the second snapshot; (Pg. 12 – Col. 6 – lines – 51-63 – “Once operational, models used to create the device digital twin 232 can be augmented with additional input created through the observation of the device digital twin 232 itself. During the operation of the device digital twin 232, the performance, behavior, and physical state of the device digital twin 232 changes. These changes are captured and then reflected in future iterations of the digital twin models ( e.g., training process). These changes are validated by the similar behavior and operation of the corresponding device 222 itself. At any point in time, the models deployed to the device digital twin 232 are representative of the codification of the behavior and operational state of the corresponding device 222. New models are created which instantiate the changes to the performance, operation, and physical state of the device digital twin 232 that occur over time. These new models can then be used in a feedback loop. Based on results generated in accordance with the digital twin, one or more debugging actions can be initiated with respect to the infrastructure” & see Also Pg. 12 – Col. 5 – lines 46- 52 – “That is, when user 240 wishes to simulate changes to a given device 222, user 240 can request digital twin management engine 210 to create/construct (spin up or instantiate) a digital twin of the given device 222 using one or more corresponding images (e.g., snapshots or the like) from a device image datastore” (equates to determine a correlation between the first snapshot and the second snapshot; as the first quote shows the correlation between the snapshots of the digital twins being based on change between each model and the second quote showing the snapshots used to construct the digital twins being equivalent to a first and second as one or more images are used to construct these models,)) and generate a result with an actionable output based on the correlation. (Pg. 12 – Col. 6 – lines – 51-63 – “Once operational, models used to create the device digital twin 232 can be augmented with additional input created through the observation of the device digital twin 232 itself. During the operation of the device digital twin 232, the performance, behavior, and physical state of the device digital twin 232 changes. These changes are captured and then reflected in future iterations of the digital twin models ( e.g., training process). These changes are validated by the similar behavior and operation of the corresponding device 222 itself. At any point in time, the models deployed to the device digital twin 232 are representative of the codification of the behavior and operational state of the corresponding device 222. New models are created which instantiate the changes to the performance, operation, and physical state of the device digital twin 232 that occur over time. These new models can then be used in a feedback loop. Based on results generated in accordance with the digital twin, one or more debugging actions can be initiated with respect to the infrastructure” (equates to and generate a result with an actionable output based on the correlation as the correlation in this quote is shown by the simulated change between the models wherein a debugging action is outputted based on the correlation determined. ) and output the result to an external device for execution with respect to the actionable output. (Pg. 13 – Col. 8 – lines 55-67 & Pg. 14 – Col. 9 – lines 1-2 – “It is assumed that the goal is that device digital twin 23 2 represent the state (e.g., hardware, software, and/or data configurations) of device 222 at Tn. Digital twin management engine 210 then receives device-related results (e.g., results of execution of one or more physics-based models 110, the one or more AI-driven models 112, the one or more simulations 114, the one or more analytics 116, and/or the one or more predictions 118 that constitute device digital twin 232) from device digital twin 232 at time Tn. Digital twin management engine 210 then sends some or all of the device-related results received from device digital twin 232 to a debug technician (tech) and/or a debug system 320. Debug tech/system 320 can then initiate or otherwise take one or more debugging actions in response to at least a portion of the received results.” (equates to and output the result to an external device for execution with respect to the actionable output as the quote provided shows an actionable output being received by a debug tech via results wherein debugging actions can take place or the actionable output can be utilized. The external system is seen via the debug system being different from the digital twin management engine.))
Yet Furlong fails to teach the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset, the plurality of connections including a first connection between the first digital twin model and the second digital twin model, the first connection representing a relationship between the first digital twin model and the second digital twin model at a specified point in time.
Cleaver discloses a similar storage medium (Pg. 11 – Col. 2 line 1). Cleaver discloses the plurality of connections including a first connection between the first digital twin model and the second digital twin model (Pg. 11 – Col. 1 – lines 58-64 – “The digital twins process invention. workloads and the digital twins communicate with each other. The hardware manager identifies an impact on a 60 number of parameters that a first set of the digital twins has on a second set of the digital twins. The hardware manager performs a set of actions based on the impact on the number of parameters” (equates to the plurality of connections including a first connection between the first digital twin model and the second digital twin model as the quote shows communication between digital twins as well as impact assessment on one set of digitals twins versus the other thus the connection is either the impact or the communication between a first and second model disclosed above.)) the first connection representing a relationship between the first digital twin model and the second digital twin model at a specified point in time. (Pg. 20 – Col. 20 – lines 32-38 – “With the use of real-time data 700, a near real-time comprehensive linkage between physical and virtual devices can be enabled. This type of linkage can increase the insights in determining impacts occurring on physical devices 412. As a result, this information along with the interconnection of digital twins 410 can help provide optimized management of physical devices 412.” & see also Pg. 15 – Col. 10 – lines 8 – 17 – “Real-time data 336 can be sent from data center 330 to network manager 332 over network 102. In turn, network manager 332 can send or relay real-time data 336 to digital twins 334. In other illustrative examples, real-time data 336 can be sent directly from data center 330 to digital twins 334. In this illustrative example, real-time data 336 is data that is sent as quickly as possible without any intentional delay. Real-time data 336 provides near real-time linkage between digital twins 334 and the physical objects or systems and data center 330” (equates to the first connection representing a relationship between the first digital twin model and the second digital twin model at a specified point in time as the first quote shows how the digital twins utilize the real time data in relation to the physical object it represents as well as, the connection between digital twins. Wherein quote 2 further explains the digital twins receiving real time data and its linkage between the physical objects and digital twin. )).
Yet Furlong-Cleaver fail to teach the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset. to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset.
Sturlaugson teaches the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset. (Pg. 15 – [0060] – “illustrates a block diagram of the digital twin system 406, according to an exemplary embodiment. The digital twin system 406 may be configured to monitor, assess, track, and/or indicate the state or condition of one or more systems, subsystems, and/or components of a vehicle... to generate or receive a digital twin of a subsystem to enable the determination of the state or condition of the subsystem (e.g., current condition). The subsystem may include one of the subsystems 212 of the aircraft 204.” (equates to the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset as the quote shows the plurality of subsystems of the aircraft being under monitor via a digital twin system.)) to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset. (Pg. 15 – [0060] – “Further, the digital twin system 406 may be configured to update or synchronize the digital twin of the subsystem. For example, the digital twin system 406 may update or synchronize the digital twin to correspond to the current state of the subsystem as further described below. The digital twin may be a digital or virtual representation of a state or condition of the subsystem. For example, the digital twin may represent an operational or performance state or condition of the subsystem of the vehicle 104.” (equates to: to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset as the quote shows the updating (adjustment) of a digital twin monitoring a subsystem (first aircraft asset).) It would have been an advantageous addition to the system disclosed by Furlong-Cleaver to include the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset. to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset as these limitations allows for aircraft components to be under monitoring and updating via the digital twin network wherein changes can be made to the digital twins based on monitoring the status of the subsystem providing up to date information .
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to include the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset. to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset as this allows for real time information regarding the condition and health of the aircraft asset to be stored within a virtual representation of a physical system allowing for past and current issues of the subsystem to be readily understood.
Regarding Claim 14 Furlong-Cleaver- Sturlaugson teaches (Furlong discloses the following limitations:) The non-transitory computer readable storage medium of claim 13, (Pg. 10 – col. 1 – lines 50-54 – “Further illustrative embodiments are provided in the form of a non-transitory computer-readable storage medium having embodied therein executable program code that when executed by a processor causes the processor to perform the above steps.”) wherein the first snapshot represents the plurality of digital twin models at a first point in time and wherein the second snapshot represents the plurality of digital twin models at a second point in time, (Pg. 11 – Col. 4 – lines 50-53 – “Referring now to FIG. 2, a computing environment 200 is depicted within which illustrative embodiments described herein are implemented. As shown, a digital twin management engine 210 is operatively coupled to a computing infrastructure network 220, itself comprising a plurality of devices 222-1, 222-2, 222-3, 222-4, ... , 222-N” & See Also Pg. 13 – Col. 7 – lines 9-16 – “FIG. 3A illustrates an exemplary process 300 of artificially aging a digital twin according to an illustrative embodiment. By way of example, process 300 can be executed in accordance with computing environment 200 of FIG. 2. As shown, process 300 involves digital twin management engine 210 and device digital twin 232 at a first 10 time Tl corresponding to a first state of device 222, and at an nth (e.g., second) time Tn corresponding to an nth (e.g., second) state of device 222. Note that a counter 302 in device digital twin 232 can be used to maintain the time instance associated with each state of device 222 that device 15 digital twin 232 is virtually representing” & See Also Pg. 4 – Fig.2 & See Also Pg. 5 – Fig. 3A (equates to wherein the first snapshot represents the plurality of digital twin models at a first point in time and wherein the second snapshot represents the plurality of digital twin models at a second point in time as the second quote shows the device of figure 2 being able to be transitioned into a digital twin at time one to a second point in time. The second quote also shows that this can be done for a plurality of devices as it can be done in the computing environment of fig. 2 where N devices can be stored. )) and wherein the instructions, when executed, cause the processor to correlate the first snapshot and the second snapshot by comparing the first snapshot and the second snapshot to determine at least one of i) a change from the first snapshot to the second snapshot over time or ii) a commonality between the first snapshot and the second snapshot. (Pg. 14 – Col.10 lines – 27-28 – “The processing platform 600 in this embodiment comprises a portion of computing environment 200” & See Also Pg. 12 – Col. 6 – lines – 51-63 – “Once operational, models used to create the device digital twin 232 can be augmented with additional input created through the observation of the device digital twin 232 itself. During the operation of the device digital twin 232, the performance, behavior, and physical state of the device digital twin 232 changes. These changes are captured and then reflected in future iterations of the digital twin models ( e.g., training process). These changes are validated by the similar behavior and operation of the corresponding device 222 itself. At any point in time, the models deployed to the device digital twin 232 are representative of the codification of the behavior and operational state of the corresponding device 222. New models are created which instantiate the changes to the performance, operation, and physical state of the device digital twin 232 that occur over time. These new models can then be used in a feedback loop. Based on results generated in accordance with the digital twin, one or more debugging actions can be initiated with respect to the infrastructure” & see Also Pg. 12 – Col. 5 – lines 46- 52 – “That is, when user 240 wishes to simulate changes to a given device 222, user 240 can request digital twin management engine 210 to create/construct (spin up or instantiate) a digital twin of the given device 222 using one or more corresponding images (e.g., snapshots or the like) from a device image datastore” (equates to wherein the instructions, when executed, cause the processor to correlate the first snapshot and the second snapshot by comparing the first snapshot and the second snapshot to determine at least one of i) a change from the first snapshot to the second snapshot over time or ii) a commonality between the first snapshot and the second snapshot as the processor existing in the processing platform which is couple to the computing environment which stores the digital twin management system that carries out the operations of quotes two and three. Wherein aforementioned quotes one or more images and thus a first and second snapshot are used to determine a change between the digital twins as shown.) )
Regarding Claim 15 Furlong-Cleaver- Sturlaugson teaches (Furlong discloses the following limitations:) The non-transitory computer readable storage medium of claim 13, (Pg. 10 – col. 1 – lines 50-54 – “Further illustrative embodiments are provided in the form of a non-transitory computer-readable storage medium having embodied therein executable program code that when executed by a processor causes the processor to perform the above steps.”) wherein the instructions, when executed, cause the processor (Pg. 10 – Col. 1 – 52-54 – “executable program code that when executed by a processor causes the processor to perform the above steps.”) to search a plurality of containers including an asset property container, (Pg. 10 – Col. 1 – lines 53-54 – “executed by a processor causes the processor to perform the above steps.” & See Also Pg. 13 – Col. 8 – lines 1-4 – “configuration-related metadata for device 222 may comprise one or more images ( e.g., backup images) generated of one or more of data, software, and system files associated with device 222.” & see Also Pg. 13 – Col. 8 – lines 6-11 - “portion of the configuration related metadata may further comprise instantiating one or more virtual processing elements ( e.g., VMs, containers, etc.) in which to execute the virtualized replica of the device 222 by mirroring, in the virtualized replica, at least a portion of the configuration-related metadata of device 222.” (equates to search a plurality of containers including an asset property container as the first quote shows the processor being able to handle techniques described within the art wherein the art later discloses configuration-related metadata relating to software ran on devices or other properties of interest for a device wherein this property data may be included in its own container as seen from the last quote.)) an asset relationship container, (Pg. 12 – Col. 5 – lines 53 – 65 – “In some illustrative embodiments, digital twin management engine 210 instantiates one or more virtual machines or VMs (e.g., using vSphere, Kernel-based Virtual Machines or KYM, etc.) or one or more containers ( e.g., using a Kubernetes container orchestration platform, etc.) to implement the given device digital twin 232. Digital twin management engine 210 matches the specifications of the given device 222 and loads the one or more corresponding images to create a virtual representation ( device digital twin 232) for a specific fidelity (resolution) of the given device 222. Depending on the use case and data availability, one or multiple digital twin fidelities can be selected by user 240,” (equates to an asset relationship container as the above quote shows a container being used for the device digital twin, wherein the container may store one or multiple digital twin fidelities corresponding to the same device at a plurality of resolution for the user to use and look at and a relationship between the asset and its variety of resolutions are stored in the container.)) and a lookup container to identify the first snapshot and the second snapshot. (Pg. 15 – Col. 11 – “For example, the disclosed techniques are applicable to a wide variety of other types of information processing 40 systems, host devices, storage systems, container monitoring tools, container management or orchestration systems” & See Also Pg. 12 – Col. 5 – lines 48 - 53 – “digital twin management engine 210 to create/construct (spin up or instantiate) a digital twin of the given device 222 using one or more corresponding images (e.g., snapshots or the like) from a device image datastore (not expressly shown) augmented with real-time data associated with the given device 222.” (equates to a lookup container to identify the first snapshot and the second snapshot as the first quote shows how container management can be implemented for disclosed techniques within the cited art, wherein one of the techniques disclosed is the identification of one or more images used to construct the digital twin as seen from quote 2. Container management equates to a lookup container as from the specification [0047] it discloses – “can include a lookup container to facilitate organization of snapshots”.))
Regarding Claim 16 Furlong-Cleaver teaches The non-transitory computer readable storage medium of claim 15, as mapped above.
Yet Furlong-Cleaver fails to specifically teach wherein the actionable output includes at least one of i) triggering maintenance for at least one of the first aircraft asset or the second aircraft asset, ii) monitoring at least one of the first aircraft asset or the second aircraft asset, or iii) reconfiguring at least one of the first aircraft asset or the second aircraft asset.
Sturlaugson teaches a similar apparatus (abstract). Sturlaugson teaches wherein the actionable output includes at least one of i) triggering maintenance for at least one of the first aircraft asset or the second aircraft asset, ii) monitoring at least one of the first aircraft asset or the second aircraft asset, or iii) reconfiguring at least one of the first aircraft asset or the second aircraft asset. (Pg. 10 – [0005] – “Physics or model-based methods may be used to generate a state or condition of an operative subsystem of an aircraft…If a fault is detected, the model-based methods may output a sequence of action or maintenance items” & See Also Pg. 14 – [0044] – “determines a fault or degraded condition or state of a subsystem based on the digital twins of the subsystems 112, the digital twin system 106 may take a responsive action, such as by scheduling maintenance for the vehicle 104, notifying an operator” & See Also Pg. 15 – [0060] – “illustrates a block diagram of the digital twin system 406, according to an exemplary embodiment. The digital twin system 406 may be configured to monitor, assess, track, and/or indicate the state or condition of one or more systems, subsystems, and/or components of a vehicle... to generate or receive a digital twin of a subsystem to enable the determination of the state or condition of the subsystem (e.g., current condition). The subsystem may include one of the subsystems 212 of the aircraft 204.” (equates to wherein the actionable output includes at least one of i) triggering maintenance for at least one of the first aircraft asset or the second aircraft asset, ii) monitoring at least one of the first aircraft asset or the second aircraft asset, or iii) reconfiguring at least one of the first aircraft asset or the second aircraft asset. as the quotes show the system checking the health of the subsystems of the vehicle and when some subsystem isn’t fully up to standard an output in the form of a notification to the operator is made regarding a maintenance event, and the second quote shows the digital twin asset being an aircraft subsystem )). It would have been an advantageous addition to the apparatus disclosed by Furlong to include wherein the actionable output includes at least one of i) triggering maintenance for at least one of the first aircraft asset or the second aircraft asset, ii) monitoring at least one of the first aircraft asset or the second aircraft asset, or iii) reconfiguring at least one of the first aircraft asset or the second aircraft asset as this would allow the apparatus of Furlong-Cleaver to specifically include particular maintenance needed based on real world data of the subsystem rather than purely forward looking as is done within the artificial aging allowing for up to date conditions to be understood and corrected if need be.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to include wherein the actionable output includes at least one of i) triggering maintenance for at least one of the first aircraft asset or the second aircraft asset, ii) monitoring at least one of the first aircraft asset or the second aircraft asset, or iii) reconfiguring at least one of the first aircraft asset or the second aircraft asset as the ability to trigger a maintenance event on particular assets allows for up to date condition to be understood and immediately corrected upon a simple query into the digital twin management system allowing for more real time data to be seen and maintain the actual part if needed.
Regarding Claim 17 Furlong-Cleaver- Sturlaugson teaches (Furlong discloses the following limitations:) The non-transitory computer readable storage medium of claim 13, (Pg. 10 – col. 1 – lines 50-54 – “Further illustrative embodiments are provided in the form of a non-transitory computer-readable storage medium having embodied therein executable program code that when executed by a processor causes the processor to perform the above steps.”) wherein the instructions, when executed, cause the processor to process (Pg. 10 – Col. 1 – lines 53-54 – “executed by a processor causes the processor to perform the above steps.”) a change event to at least one of: ingest the change event, store a snapshot of the plurality of digital twin models based on the change event, or facilitate querying based on the change event. (Pg. 12 – Col. 6 – lines – 51-63 – “Once operational, models used to create the device digital twin 232 can be augmented with additional input created through the observation of the device digital twin 232 itself. During the operation of the device digital twin 232, the performance, behavior, and physical state of the device digital twin 232 changes. These changes are captured and then reflected in future iterations of the digital twin models ( e.g., training process). These changes are validated by the similar behavior and operation of the corresponding device 222 itself. At any point in time, the models deployed to the device digital twin 232 are representative of the codification of the behavior and operational state of the corresponding device 222. New models are created which instantiate the changes to the performance, operation, and physical state of the device digital twin 232 that occur over time. These new models can then be used in a feedback loop. Based on results generated in accordance with the digital twin, one or more debugging actions can be initiated with respect to the infrastructure” & See Also Pg. 10 – Col. 1 – lines 51-56 – “…storage medium having embodied therein executable program code that when executed by a processor causes the processor to perform the above steps… apparatus with a processor and a memory configured to 55 perform the above steps.” (equates to ingest the change event as the digital twins are undergoing changes by way of the training process disclosed above, wherein the processor can execute any disclosed step so of the cited art.)
Regarding Claim 18 Furlong teaches A method comprising: (Pg. 10 – Col. 1 – Lines 36 – 42 – “For example, according to one illustrative embodiment, a method comprises obtaining at least one virtual representation of an infrastructure, wherein the virtual representation represents the infrastructure in a first state, and applying at least one dataset to the virtual representation to artificially advance the virtual representation to represent the infrastructure in a second state” ) processing, by executing an instruction using a processor, (Pg. 10 – Col. 1 – lines 52-54 – “embodied therein executable program code that when executed by a processor causes the processor to perform the above steps”) a query to search a plurality of snapshots, (Pg. 12 – Col. 5 – lines 48-51 – “user 240 can request digital twin management engine 210 to create/construct (spin up or instantiate) a digital twin of the given device 222 using one or more corresponding images (e.g., snapshots or the like) from a device image datastore” (equates to a query to search a plurality of snapshots as the user can request to build a digital model wherein the digital twin management engine searches a datastore comprising a plurality of snapshots.)) each snapshot including a plurality of digital twin models interconnected by a plurality of connections to form a network of digital twins, (pg. 4 – Fig. 2 & See Also Pg. 6 – Fig. 3B & See Also Pg. 13 – col. 8 – lines 28-33 – “devices 222-1, 222-2, and 222-(individually referred to in the context of FIG. 3B as device 222), and at an nth (e.g., second) time Tn corresponding to an nth ( e.g., second) state of device 222. Note that a counter 302 in device digital twin 232 can be used to maintain the time instance associated with each state of device 222 that device digital twin 232 is virtually representing” & See Also Pg. 12 – Col. 5 – lines 8-22 – “Device digital twins 232 respectively correspond to devices 222 in 10 computing infrastructure network 220, i.e., there is a device digital twin 232 that virtually represents a device 222 (e.g., device digital twin 232-1 virtually represents device 222-1, ... , device digital twin 232-N virtually represents device 222-N). Note, however, that while FIG. 2 illustrates 15 a one-to-one correspondence between devices 222-1, 222-2, 222-3, 222-4, ... , 222-N and device digital twins 232-1, 232-2, 232-3, 232-4, ... , 232-N, alternative embodiments may comprise alternative correspondences, e.g., a single device digital twin 232 can represent more than one of 20 devices 222, more than one of device digital twins 232 can represent a single device 222, etc.” (equates to each snapshot including a plurality of digital twin models interconnected by a plurality of connections to form a network of digital twins as the quote shows the counter keeping track of the time change between the device at two instances and thus a snapshot is formed between the digital twin models and the last quote shows how this can be scaled for up to n devices that can undergo the same time change for each of the plurality of snapshots. A network of digital twins is formed as the fig. 2 included shows the digital twin network of up to N devices. )) each snapshot representing a state of the digital twin models at the specified point in time; (Pg. 14 – Col. 9 – lines 10-17 – “FIG. 4, a methodology 400 is illustrate for artificially aging a digital twin to facilitate debugging of an infrastructure according to an illustrative embodiment. It is to be understood that, in illustrative embodiments, methodology 400 is performed by computing environment 200 of FIG. 2. As shown, step 402 obtains at least one virtual representation of an infrastructure, wherein the virtual representation represents the infrastructure in a first state.” & See Also Pg. 14 – Col. 9 – lines 17-20 – “Step 404 applies at least one dataset to the virtual representation to artificially advance the virtual representation to represent the infrastructure in a second state” & See Also Pg. 7 – Fig. 4 (equates to each snapshot representing a state of the digital twin models at the specified point in time as the quote show the infrastructure being converted into a digital twin that undergoes aging in the computer processing environment wherein the infrastructure is represented by snapshots of its condition at points in time as seen from the quotes and figures.)) identifying, in response to the query by executing an instruction using the processor, at least a first snapshot representing the plurality of digital twin models and interconnections at a first point in time and a second snapshot representing the plurality of digital twin models and interconnections at a second point in time (Pg. 12 – Col. 5 – lines 46- 52 – “That is, when user 240 wishes to simulate changes to a given device 222, user 240 can request digital twin management engine 210 to create/construct (spin up or instantiate) a digital twin of the given device 222 using one or more corresponding images (e.g., snapshots or the like) from a device image datastore” & See Also Pg. 12 – Col. 5 – lines 59- 63 - “Digital twin management engine 210 matches the specifications of the given device 222 and load the one or more corresponding images to create a virtual representation ( device digital twin 232) for a specific fidelity (resolution) of the given device 222.” & See Also Pg. 14 – Col.10 lines – 27-28 – “The processing platform 600 in this embodiment comprises a portion of computing environment 200” & See Also Pg. 14 – Col.10 – lines 39- 40 – “The processing device 602-1 in the processing platform 600 comprises a processor 610” & See Also Pg. 11 – Col. 4 – lines 47-51 – “a computing environment 200 is depicted within which illustrative embodiments described herein are implemented. As shown, a digital twin management engine 210 is operatively coupled to a computing infrastructure network 220” & See Also Pg. 11 – Col. 4 – lines 50-53 – “Referring now to FIG. 2, a computing environment 200 is depicted within which illustrative embodiments described herein are implemented. As shown, a digital twin management engine 210 is operatively coupled to a computing infrastructure network 220, itself comprising a plurality of devices 222-1, 222-2, 222-3, 222-4, ... , 222-N” & See Also Pg. 13 – Col. 7 – lines 9-16 – “FIG. 3A illustrates an exemplary process 300 of artificially aging a digital twin according to an illustrative embodiment. By way of example, process 300 can be executed in accordance with computing environment 200 of FIG. 2. As shown, process 300 involves digital twin management engine 210 and device digital twin 232 at a first 10 time Tl corresponding to a first state of device 222, and at an nth (e.g., second) time Tn corresponding to an nth (e.g., second) state of device 222. Note that a counter 302 in device digital twin 232 can be used to maintain the time instance associated with each state of device 222 that device 15 digital twin 232 is virtually representing” & See Also Pg. 4 – Fig.2 & See Also Pg. 5 – Fig. 3A (equates to identifying, in response to the query by executing an instruction using the processor, at least a first snapshot representing the plurality of digital twin models and interconnections at a first point in time and a second snapshot representing the plurality of digital twin models and interconnections at a second point in time as the first quote shows a request to construct the digital twin and thus a query is formed wherein the one or more corresponding images or snapshots is identified by the digital twin management engine, and all is done by the processing circuitry as the processor is an integral part of the computing environment which stores the digital twin management engine. The last quote shows the change being generated within the digital twin is done via a time change as a first state or first snapshot and a nth state or second snapshot is seen within. )) determining, by executing an instruction using the processor, (Pg. 10 – Col. 1 – lines 52-54 – “executable program code that when executed by a processor causes the processor to perform the above steps”) a correlation between the first snapshot and the second snapshot; (Pg. 12 – Col. 6 – lines – 51-63 – “Once operational, models used to create the device digital twin 232 can be augmented with additional input created through the observation of the device digital twin 232 itself. During the operation of the device digital twin 232, the performance, behavior, and physical state of the device digital twin 232 changes. These changes are captured and then reflected in future iterations of the digital twin models ( e.g., training process). These changes are validated by the similar behavior and operation of the corresponding device 222 itself. At any point in time, the models deployed to the device digital twin 232 are representative of the codification of the behavior and operational state of the corresponding device 222. New models are created which instantiate the changes to the performance, operation, and physical state of the device digital twin 232 that occur over time. These new models can then be used in a feedback loop. Based on results generated in accordance with the digital twin, one or more debugging actions can be initiated with respect to the infrastructure” & see Also Pg. 12 – Col. 5 – lines 46- 52 – “That is, when user 240 wishes to simulate changes to a given device 222, user 240 can request digital twin management engine 210 to create/construct (spin up or instantiate) a digital twin of the given device 222 using one or more corresponding images (e.g., snapshots or the like) from a device image datastore” (equates to determine a correlation between the first snapshot and the second snapshot; as the first quote shows the correlation between the snapshots of the digital twins being based on change between each model and the second quote showing the snapshots used to construct the digital twins being equivalent to a first and second as one or more images are used to construct these models,)) generating, by executing an instruction using the processor, (Pg. 10 – Col. 1 – lines 52-54 – “executable program code that when executed by a processor causes the processor to perform the above steps”) a result with an actionable output based on the correlation. (Pg. 12 – Col. 6 – lines – 51-63 – “Once operational, models used to create the device digital twin 232 can be augmented with additional input created through the observation of the device digital twin 232 itself. During the operation of the device digital twin 232, the performance, behavior, and physical state of the device digital twin 232 changes. These changes are captured and then reflected in future iterations of the digital twin models ( e.g., training process). These changes are validated by the similar behavior and operation of the corresponding device 222 itself. At any point in time, the models deployed to the device digital twin 232 are representative of the codification of the behavior and operational state of the corresponding device 222. New models are created which instantiate the changes to the performance, operation, and physical state of the device digital twin 232 that occur over time. These new models can then be used in a feedback loop. Based on results generated in accordance with the digital twin, one or more debugging actions can be initiated with respect to the infrastructure” (equates to and generate a result with an actionable output based on the correlation as the correlation in this quote is shown by the simulated change between the models wherein a debugging action is outputted based on the correlation determined. ) and outputting the result to an external device for execution with respect to the actionable output. (Pg. 13 – Col. 8 – lines 55-67 & Pg. 14 – Col. 9 – lines 1-2 – “It is assumed that the goal is that device digital twin 23 2 represent the state (e.g., hardware, software, and/or data configurations) of device 222 at Tn. Digital twin management engine 210 then receives device-related results (e.g., results of execution of one or more physics-based models 110, the one or more AI-driven models 112, the one or more simulations 114, the one or more analytics 116, and/or the one or more predictions 118 that constitute device digital twin 232) from device digital twin 232 at time Tn. Digital twin management engine 210 then sends some or all of the device-related results received from device digital twin 232 to a debug technician (tech) and/or a debug system 320. Debug tech/system 320 can then initiate or otherwise take one or more debugging actions in response to at least a portion of the received results.” (equates to and outputting the result to an external device for execution with respect to the actionable output as the quote provided shows an actionable output being received by a debug tech via results wherein debugging actions can take place or the actionable output can be utilized. The external system is seen via the debug system being different from the digital twin management engine.))
Yet fails to teach the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset , the plurality of connections including a first connection between the first digital twin model and the second digital twin model, the first connection representing a relationship between the first digital twin model and the second digital twin model at a specified point in time.
Cleaver discloses a similar storage medium (Pg. 11 – Col. 2 line 1). Cleaver discloses the plurality of connections including a first connection between the first digital twin model and the second digital twin model (Pg. 11 – Col. 1 – lines 58-64 – “The digital twins process invention. workloads and the digital twins communicate with each other. The hardware manager identifies an impact on a 60 number of parameters that a first set of the digital twins has on a second set of the digital twins. The hardware manager performs a set of actions based on the impact on the number of parameters” (equates to the plurality of connections including a first connection between the first digital twin model and the second digital twin model as the quote shows communication between digital twins as well as impact assessment on one set of digitals twins versus the other thus the connection is either the impact or the communication between a first and second model disclosed above.)) the first connection representing a relationship between the first digital twin model and the second digital twin model at a specified point in time. (Pg. 20 – Col. 20 – lines 32-38 – “With the use of real-time data 700, a near real-time comprehensive linkage between physical and virtual devices can be enabled. This type of linkage can increase the insights in determining impacts occurring on physical devices 412. As a result, this information along with the interconnection of digital twins 410 can help provide optimized management of physical devices 412.” & see also Pg. 15 – Col. 10 – lines 8 – 17 – “Real-time data 336 can be sent from data center 330 to network manager 332 over network 102. In turn, network manager 332 can send or relay real-time data 336 to digital twins 334. In other illustrative examples, real-time data 336 can be sent directly from data center 330 to digital twins 334. In this illustrative example, real-time data 336 is data that is sent as quickly as possible without any intentional delay. Real-time data 336 provides near real-time linkage between digital twins 334 and the physical objects or systems and data center 330” (equates to the first connection representing a relationship between the first digital twin model and the second digital twin model at a specified point in time as the first quote shows how the digital twins utilize the real time data in relation to the physical object it represents as well as, the connection between digital twins. Wherein quote 2 further explains the digital twins receiving real time data and its linkage between the physical objects and digital twin. )).
Yet Furlong-Cleaver fails to teach the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset, to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset.
Sturlaugson teaches the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset. (Pg. 15 – [0060] – “illustrates a block diagram of the digital twin system 406, according to an exemplary embodiment. The digital twin system 406 may be configured to monitor, assess, track, and/or indicate the state or condition of one or more systems, subsystems, and/or components of a vehicle... to generate or receive a digital twin of a subsystem to enable the determination of the state or condition of the subsystem (e.g., current condition). The subsystem may include one of the subsystems 212 of the aircraft 204.” (equates to the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset as the quote shows the plurality of subsystems of the aircraft being under monitor via a digital twin system.)) to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset. (Pg. 15 – [0060] – “Further, the digital twin system 406 may be configured to update or synchronize the digital twin of the subsystem. For example, the digital twin system 406 may update or synchronize the digital twin to correspond to the current state of the subsystem as further described below. The digital twin may be a digital or virtual representation of a state or condition of the subsystem. For example, the digital twin may represent an operational or performance state or condition of the subsystem of the vehicle 104.” (equates to: to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset as the quote shows the updating (adjustment) of a digital twin monitoring a subsystem (first aircraft asset).) It would have been an advantageous addition to the system disclosed by Furlong-Cleaver to include the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset. to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset as these limitations allows for aircraft components to be under monitoring and updating via the digital twin network wherein changes can be made to the digital twins based on monitoring the status of the subsystem providing up to date information .
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to include the plurality of digital twin models including a first digital twin model of a first aircraft asset and a second digital twin model of a second aircraft asset. to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset as this allows for real time information regarding the condition and health of the aircraft asset to be stored within a virtual representation of a physical system allowing for past and current issues of the subsystem to be readily understood.
Regarding Claim 19 Furlong-Cleaver- Sturlaugson teaches (Furlong discloses the following limitation:) The method of claim 18, wherein the first snapshot represents the plurality of digital twin models at a first point in time and wherein the second snapshot represents the plurality of digital twin models at a second point in time, (Pg. 11 – Col. 4 – lines 50-53 – “Referring now to FIG. 2, a computing environment 200 is depicted within which illustrative embodiments described herein are implemented. As shown, a digital twin management engine 210 is operatively coupled to a computing infrastructure network 220, itself comprising a plurality of devices 222-1, 222-2, 222-3, 222-4, ... , 222-N” & See Also Pg. 13 – Col. 7 – lines 9-16 – “FIG. 3A illustrates an exemplary process 300 of artificially aging a digital twin according to an illustrative embodiment. By way of example, process 300 can be executed in accordance with computing environment 200 of FIG. 2. As shown, process 300 involves digital twin management engine 210 and device digital twin 232 at a first 10 time Tl corresponding to a first state of device 222, and at an nth (e.g., second) time Tn corresponding to an nth (e.g., second) state of device 222. Note that a counter 302 in device digital twin 232 can be used to maintain the time instance associated with each state of device 222 that device 15 digital twin 232 is virtually representing” & See Also Pg. 4 – Fig.2 & See Also Pg. 5 – Fig. 3A (equates to wherein the first snapshot represents the plurality of digital twin models at a first point in time and wherein the second snapshot represents the plurality of digital twin models at a second point in time as the second quote shows the device of figure 2 being able to be transitioned into a digital twin at time one to a second point in time. The second quote also shows that this can be done for a plurality of devices as it can be done in the computing environment of fig. 2 where N devices can be stored. )) and wherein the method includes correlating the first snapshot and the second snapshot by comparing the first snapshot and the second snapshot to determine at least one of i) a change from the first snapshot to the second snapshot over time or ii) a commonality between the first snapshot and the second snapshot. (Pg. 10 – Col. 1 – lines – 36-42 – “For example, according to one illustrative embodiment, a method comprises obtaining at least one virtual representation of an infrastructure, wherein the virtual representation represents the infrastructure in a first state, and applying at least one dataset to the virtual representation to artificially advance the virtual representation to represent the infrastructure in a second state.” & See Also Pg. 12 – Col. 6 – lines – 51-63 – “Once operational, models used to create the device digital twin 232 can be augmented with additional input created through the observation of the device digital twin 232 itself. During the operation of the device digital twin 232, the performance, behavior, and physical state of the device digital twin 232 changes. These changes are captured and then reflected in future iterations of the digital twin models ( e.g., training process). These changes are validated by the similar behavior and operation of the corresponding device 222 itself. At any point in time, the models deployed to the device digital twin 232 are representative of the codification of the behavior and operational state of the corresponding device 222. New models are created which instantiate the changes to the performance, operation, and physical state of the device digital twin 232 that occur over time. These new models can then be used in a feedback loop. Based on results generated in accordance with the digital twin, one or more debugging actions can be initiated with respect to the infrastructure” & see Also Pg. 12 – Col. 5 – lines 46- 52 – “That is, when user 240 wishes to simulate changes to a given device 222, user 240 can request digital twin management engine 210 to create/construct (spin up or instantiate) a digital twin of the given device 222 using one or more corresponding images (e.g., snapshots or the like) from a device image datastore” (equates to wherein the method includes correlating the first snapshot and the second snapshot by comparing the first snapshot and the second snapshot to determine at least one of i) a change from the first snapshot to the second snapshot over time or ii) a commonality between the first snapshot and the second snapshot as the method carries out the steps of quotes two and three. Wherein aforementioned quotes show one or more images and thus a first and second snapshot are used to determine a change between the digital twins as shown.))
Regarding Claim 20 Furlong-Cleaver- Sturlaugson teaches (Furlong discloses the following limitations:) The method of claim 18, wherein processing the query includes processing a change event to at least one of: (Pg. 12 – Col. 5 – Lines 44-59 – “In one or more illustrative embodiments, by way of example only, assume that a given device digital twin 232 is needed/desired for on-demand simulations. That is, when user 240 wishes to simulate changes to a given device 222, user 240 can request digital twin management engine 210 to create/construct (spin up or instantiate) a digital twin of the given device 222 using one or more corresponding images (e.g., snapshots or the like) from a device image datastore (not expressly shown) augmented with real-time data associated with the given device 222. In some illustrative embodiments, digital twin management engine 210 instantiates one or more virtual machines or VMs (e.g., using vSphere, Kernel-based Virtual Machines or KYM, etc.) or one or more containers ( e.g., using a Kubernetes container orchestration platform, etc.) to implement the given device digital twin 232.” & See Also Pg. 13 – Col. 8 – Lines 12 -19 – “apply a change to device digital twin 232 to replicate application of the change to device 222. Applying a change to device digital twin 232 to replicate application of the change to device 222 may further comprise receiving the change to be applied to device digital twin 232 and then executing the change. In some embodiments, the change may be defined via a script or a command line issued by digital twin management” (equates to wherein processing the query includes processing a change event to at least one of as the first quote shows a request being initiated for the digital twin construction wherein the second the second quote shows the ability to change the device through replication of an application in which a command line is utilize to receive a change and apply to the digital twin.)) ingest the change event, store a snapshot of the first digital twin model of the plurality of digital twin models based on the change event, or facilitate querying based on the change event. ((Pg. 12 – Col. 6 – lines – 51-63 – “Once operational, models used to create the device digital twin 232 can be augmented with additional input created through the observation of the device digital twin 232 itself. During the operation of the device digital twin 232, the performance, behavior, and physical state of the device digital twin 232 changes. These changes are captured and then reflected in future iterations of the digital twin models ( e.g., training process). These changes are validated by the similar behavior and operation of the corresponding device 222 itself. At any point in time, the models deployed to the device digital twin 232 are representative of the codification of the behavior and operational state of the corresponding device 222. New models are created which instantiate the changes to the performance, operation, and physical state of the device digital twin 232 that occur over time. These new models can then be used in a feedback loop. Based on results generated in accordance with the digital twin, one or more debugging actions can be initiated with respect to the infrastructure” & See Also Pg. 10 – Col. 1 – lines 51-56 – “…storage medium having embodied therein executable program code that when executed by a processor causes the processor to perform the above steps… apparatus with a processor and a memory configured to 55 perform the above steps.” (equates to ingest the change event as the digital twins are undergoing changes by way of the training process disclosed above and are executed by the apparatus and storage medium as seen from the second quote and thus ingested.)))
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Furlong -Cleaver- Sturlaugson as previously mapped and in further view of Krimmer (WO2023083413A1).
Regarding Claim 4 Furlong-Cleaver- Sturlaugson teaches The apparatus of claim 3, as mapped above
Yet all fail to teach wherein the commonality includes at least one of a related asset on a same airframe or a similar asset on a different airframe.
Krimmer teaches a similar apparatus of accessing aircraft component health (abstract). Krimmer teaches wherein the commonality includes at least one of a related asset on a same airframe or a similar asset on a different airframe. (Pg. 6 – [0019] – “a group of engines, in particular the engines of a predetermined fleet. In this way, a comparison of an engine with one or a fleet of engines can be carried out at a reference engine load point, which is essentially freely definable. The proposed method also allows the user to individually assemble the engine fleet, for example engines of the same construction standards, in the same or different installation periods, with the same rating, etc. In addition, it is also possible to view individual engine modules and compare them with individual engine modules.” & See Also Pg. 6 – [0020] – “predetermined engine performance parameter at the reference engine load point between the time of attachment and detachment of the engine from an aircraft wing is determined. 242 In this way, the aging contribution of individual engine modules to the overall aging of the engine can be determined.” (equates to wherein the commonality includes at least one of a related asset on a same airframe or a similar asset on a different airframe as the first quote shows a fleet of aircraft in which engine modules or assets can be compared with one another wherein the commonality is the engine modules throughout the fleet. The first quote shows the related airframe as the loading point can be freely defined and the second being from the aircraft wing – a part of the airframe. )) It would have been an advantageous addition to the apparatus disclosed by Furlong-Cleaver to include wherein the commonality includes at least one of a related asset on a same airframe or a similar asset on a different airframe as this would allow for similar components to be compared to one another and for easy health assessments to take place across a fleet of aircraft.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to include wherein the commonality includes at least one of a related asset on a same airframe or a similar asset on a different airframe as this allows for a variety of maintenance operations to take place for similar components on similar structures allowing for easy replacement or upkeep to follow suit.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Furlong- Cleaver- Sturlaugson as previously mapped and in further view of Jackson (US 2012/0166249 Al).
Regarding Claim 5 Furlong-Cleaver- Sturlaugson teaches The apparatus of claim 3, as previously mapped above.
Yet all fail to teach wherein the change includes at least one of i) at least one of the first aircraft asset or the second aircraft asset moved from a first airframe to a second airframe, ii) a difference between a first configuration of the first aircraft asset and the second aircraft asset on the first airframe to a second configuration of the first aircraft asset and the second aircraft asset on the first airframe, or iii) a difference between the first configuration of the first aircraft asset and the second aircraft asset on the first airframe and a third configuration of the first aircraft asset and the second aircraft asset on the second airframe.
Jackson teaches a similar apparatus (abstract). Jackson teaches w wherein the change includes at least one of i) at least one of the first aircraft asset or the second aircraft asset moved from a first airframe to a second airframe, ii) a difference between a first configuration of the first aircraft asset and the second aircraft asset on the first airframe to a second configuration of the first aircraft asset and the second aircraft asset on the first airframe, or iii) a difference between the first configuration of the first aircraft asset and the second aircraft asset on the first airframe and a third configuration of the first aircraft asset and the second aircraft asset on the second airframe. (Pg. 13 – [0113] – “That is to say the stagger values for one engine configuration are compared to those for other available engine configurations.” & See Also Pg. 13 – [0116] – “In assessing the beneficial or detrimental impact of an engine configuration or a proposed stagger exchange, a numeric value is defined, which is referred to herein as the stagger index. The stagger index represents a count of the number of times the target stagger is met or exceeded on an airframe.” & See Also Pg. 13 – [0112] – “one or more routines which survey the engines in the fleet to determine a level of stagger for aircraft in the fleet.” (equates to wherein the change includes at least one of i) at least one of the first aircraft asset or the second aircraft asset moved from a first airframe to a second airframe, ii) a difference between a first configuration of the first aircraft asset and the second aircraft asset on the first airframe to a second configuration of the first aircraft asset and the second aircraft asset on the first airframe, or iii) a difference between the first configuration of the first aircraft asset and the second aircraft asset on the first airframe and a third configuration of the first aircraft asset and the second aircraft asset on the second airframe. as the difference in configuration of the first asset and second asset are seen by quote one’s engine configuration, where they specifically use a stagger metric to determine stress induced on the airframes from the variety of engine configuration (quote 2). Wherein quote 3 shows this can be done for a fleet of vehicles and that engine configuration on a variety of airframe within the fleet can be monitored and maintained.)) It would have been an advantageous addition to the apparatus disclosed by Furlong-Cleaver to include wherein the change includes at least one of i) at least one of the first aircraft asset or the second aircraft asset moved from a first airframe to a second airframe, ii) a difference between a first configuration of the first aircraft asset and the second aircraft asset on the first airframe to a second configuration of the first aircraft asset and the second aircraft asset on the first airframe, or iii) a difference between the first configuration of the first aircraft asset and the second aircraft asset on the first airframe and a third configuration of the first aircraft asset and the second aircraft asset on the second airframe. as this limitation allows for a variety of asset configuration to be quickly studied and monitored ensuring an optimal asset configuration is used throughout the fleet of vehicles.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to include wherein the change includes at least one of i) at least one of the first aircraft asset or the second aircraft asset moved from a first airframe to a second airframe, ii) a difference between a first configuration of the first aircraft asset and the second aircraft asset on the first airframe to a second configuration of the first aircraft asset and the second aircraft asset on the first airframe, or iii) a difference between the first configuration of the first aircraft asset and the second aircraft asset on the first airframe and a third configuration of the first aircraft asset and the second aircraft asset on the second airframe as this allows for a variety of placements and asset configurations to be under management allowing for quick replacement and adjustments to take place within the fleet of aircraft.
Claims 12 is rejected under 35 U.S.C. 103 as being unpatentable over Furlong- Cleaver-Sturlaugson as previously mapped and in further view of Carbognani (WO2025/090210A1).
Regarding Claim 12 Furlong- Cleaver-Sturlaugson teaches The apparatus of claim 11, wherein the processing circuitry (Pg. 14 – Col. 10 – lines 27-29 – “The processing platform 600 in this embodiment comprises a portion of computing environment 200 and includes a plurality of processing devices”) to facilitate ingestion of change events, (Pg. 12 – Col. 6 – lines – 51-63 – “Once operational, models used to create the device digital twin 232 can be augmented with additional input created through the observation of the device digital twin 232 itself. During the operation of the device digital twin 232, the performance, behavior, and physical state of the device digital twin 232 changes. These changes are captured and then reflected in future iterations of the digital twin models ( e.g., training process). These changes are validated by the similar behavior and operation of the corresponding device 222 itself. At any point in time, the models deployed to the device digital twin 232 are representative of the codification of the behavior and operational state of the corresponding device 222. New models are created which instantiate the changes to the performance, operation, and physical state of the device digital twin 232 that occur over time. These new models can then be used in a feedback loop. Based on results generated in accordance with the digital twin, one or more debugging actions can be initiated with respect to the infrastructure” & See Also Pg. 10 – Col. 1 – lines 51-56 – “…storage medium having embodied therein executable program code that when executed by a processor causes the processor to perform the above steps… apparatus with a processor and a memory configured to 55 perform the above steps.” (equates to facilitate ingestion of change events as the digital twins are undergoing changes by way of the training process disclosed above and are executed by the apparatus and storage medium as seen from the second quote.)) storage of snapshots, (Pg. 12 – Col. 5 – lines 50-53 – “using one or more corresponding images (e.g., snapshots or the like) from a device image datastore (not expressly shown) augmented with real-time data associated with the given device 222” (equates to storage of snapshots as this quote shows the storage of device snapshots for use in constructing the digital twin of this art.)) and querying of the memory circuitry. (Pg. 12 – Col 5 – lines 48-53 – “request digital twin management engine 210 to create/construct (spin up or instantiate) a digital twin of the given device 222 using one or more corresponding images (e.g., snapshots or the like) from a device image datastore (not expressly shown) augmented with real-time data associated with the given device 222” (equates to querying of the memory circuitry as the quote shows a request to construct a digital twin wherein the digital twin management engine pulls snapshots from the datastore or memory circuitry to do so. ))
Yet Furlong-Cleaver fails to teach includes an application program interface.
Carbognani teaches a similar apparatus (abstract). Carbognani teaches includes an application program interface (Pg. 5 – [0018] – “Conventionally, digital twins were generated by hand, using specialized programming, application program interfaces (APis),”). It would have been an advantageous addition to the apparatus disclosed by Furlong-Cleaver to include: includes an application program interface as having an API allows a structured and controlled way for different software systems to interact and exchange data when communicating between the variety of storage and processing circuitry that allows the digital twin management system to function.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to include includes an application program interface as having an API allows for seamless data transaction across a variety of differently built software and hardware implemented throughout the apparatus.
Claim 21 is rejected under 35 U.S.C. 103 as being unpatentable over Furlong-Cleaver – Sturlaugson and in view of Shaopeng (CN117150632A) .
Regarding Claim 21 Furlong-Cleaver-Sturlaugson teaches The apparatus of claim 1 as previously mapped above.
Yet Furlong-Cleaver fails to teach wherein the query is triggered by an aircraft controller in response to a change detected with respect to an aircraft asset.
Shaopeng teaches wherein the query is triggered by an aircraft controller in response to a change detected with respect to an aircraft asset. (Pg. 3 – [20] - “When sufficient conditions are monitored to trigger real-time calculations, the calculation command is returned to the data processing layer, and the simulation calculation results are used to calculate the airport runway. Evaluate the health status and output the evaluation results;” & See Also Pg. 12 – [158] – “Based on preset trigger conditions. For example, aircraft takeoff and landing activities can be considered as a sufficient condition to trigger real-time calculation; when an aircraft takes off and land, based on the structured data in step S200 at the current moment, the digital twin physical calculation model is used to calculate, Obtain relevant data calculation results for the monitoring indicators.” & See Also Pg. 7 – [88] – “the data processing layer includes a monitoring data processing module, a tower data processing module, and a digital twin physical core engine module” (equates to wherein the query is triggered by an aircraft controller in response to a change detected with respect to an aircraft asset. As the first quote shows a condition indicating a change event in which a calculation relating to the condition or health of the aircraft is done ensuring working condition of the aircraft based on unfavorable conditions. The second quote further shows the trigger event being a change event of the flight status of the aircraft. The third quote showing the data processing layer acting as an aircraft controller.) ) It would have been an advantageous addition to the system disclosed by Furlong-Cleaver-Sturlaugson to include wherein the query is triggered by an aircraft controller in response to a change detected with respect to an aircraft asset as this allows a direct status inquiry into the condition of the aircraft to be immediately triggered based on change events happening to the aircraft allowing time to be saved as the query into the status of the aircraft is automatically checked rather than querying based upon seeing a change event.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to include wherein the query is triggered by an aircraft controller in response to a change detected with respect to an aircraft asset as this allows an automatic means of monitoring the health status of the aircraft and ensures the monitoring done is based on the specific change event experienced by the aircraft.
Response to Arguments
Response to 35 U.S.C. § 101 rejection of claims 1, and 3-21 .Applicant’s arguments have been considered but are not persuasive.
Applicant Argues on pages 1-4 , “The Applicant respectfully submits that the claimed subject matter of claims I and 3-21 cannot reasonably and accurately be performed entirely in a human mind. That is, there is no function that is associated with a human mind even if aided with a pen and paper. Specifically, it is not possible in the human mind to form a network of digital twins, search memory circuitry, store snapshots of the network of digital twins and interconnections at different points in time, process snapshots stored in the memory circuitry, query to determine a correlation between the snapshots, and output the result to an external device for execution with respect to the actionable output trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 1375-76 (Fed. Cir. 2011) (distinguishing Research Corp. Techs. Inc. v. Microsoft Corp., 627 F.3d 859 (Fed. Cir. 2010)).
As noted in the USPTO's October 2019 Update on Subject Matter Eligibility (the "2019 USPTO Guidance"), claimed subject matter is directed to a "mental process “only when it can be practically performed by the human mind, such as
"observations, evaluations, judgments, and opinions." Complex computations, simulations, and processes are not an observation, evaluation, judgment, or opinion, nor can such features be practically performed by the human mind. Creating, storing, processing, and querying a network of digital twin models to trigger an adjustment via an external system with respect to at least one aircraft asset is not practically performable by the human mind (in fact, it is not performable by mental process at all). The 2019 USPTO Guidance provides various examples that expressly indicate such complex computations and processes are not "mental processes" under 35 U.S.C. §101. Indeed, the USPTO itself agrees that complex computations like simulations cannot be performed by the human mind. Example 38 of Subject Matter Eligibility Examples issued on January 7, 2019 ("USPTO Eligibility Examples") analyzes a claim term that recites "simulating a first digital representation of the analog circuit based on the first random value and the location of each circuit element with the analog circuit." In indicating that this claim in Example 38 is not directed to an abstract idea, the USPTO Eligibility Examples explains "[w]ith respect to mental processes, the claim does not recite a mental process because the steps are not practically performed in the human mind." (USPTO Eligibility Examples, p. 7 (Emphasis added)).
In a similar manner, the features of independent claim I of the present application likewise do not recite a mental process because the features to perform snapshot storage, interconnection, query, and output to an external device cannot be practically performed in the human mind.” -– As to point (A), Examiner respectfully disagrees. Applicant appears to argue that at Step 2A Prong 1, the claim provided does not show how the limitations can be reasonably performed in the human mind and that the recitation of “to model, track, analyze, and adjust aircraft assets, the processing circuitry” and “the processing circuitry to output the result to an external device for execution with respect to the actionable output to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset” each of the limitations precludes the claim from being reasonably performed by the human mind. In Step 2A Prong 1, Examiner considers the impact of additional elements. In this case, the limitations “the processing circuitry to output the result to an external device for execution with respect to the actionable output” are additional elements considered after Step 2A Prong 1. The remaining elements recite abstract ideas that fall into the mental process grouping. As previously stated the limitation “to model, track, analyze, and adjust aircraft assets” , is not including a specific adjustment in which control over the aircraft is asserted or an action being done in physical space as the modeling, tracking, analyzation, and adjustment can done via a human mind with the aid of pen and paper. In response to “trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset” the examiner submits that this is similarly claiming an adjustment being done to the aircraft but because no physical change or control over the working status of the aircraft is being claimed the adjustment being triggered via the data gathering step may simply be a mental process that can be executed via pen and paper.
Response to 35 U.S.C. § 103 rejection of claims 1 and 3-21 applicant’s amendments to the claim changes the scope. Applicant’s arguments have been considered but are not persuasive.
Applicant argues on pages 5, “Claim 1 sets forth, inter alia, processing circuitry to model, track, analyze, and adjust aircraft assets, the processing circuitry to process a query to search the memory circuitry, the processing circuitry to identify, in response to the query, at least a first snapshot representing a network of a plurality of digital twin models and interconnections at a first point in time and a second snapshot representing the network of the plurality of digital twin models and interconnections at a second point in time, the processing circuitry to determine a correlation between the first snapshot and the second snapshot and generate the result with an actionable output based on the correlation, the processing circuitry to output the result to an external device for execution with respect to the actionable output to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset.
The cited references fail to teach or suggest such an apparatus. While Furlong and Cleaver mention digital twins, neither Furlong nor Cleaver teaches or suggests processing snapshots of networks of digital twin models of aircraft assets including comparing and correlating different snapshots of the network of digital twins at different points in time, as set forth in claim 1. Instead, Furlong applies a data set to a digital twin to change its state but does not store snapshots or correlate between snapshots, and Cleaver evaluates how parameters from a first digital twin impact a second digital twin, not correlating between snapshots of a network of digital twins at different points in time. Further neither Furlong nor Cleaver generates and outputs a result to an external device for execution with respect to an actionable output to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset, as set forth in claim 1.
While not relied upon to reject claim 1, none of Krimmer, Jackson, Sturlaugson, or Carbognani remedies the deficiencies of Furlong and Cleaver with respect to claim 1. As such, the cited art, taken alone or in combination, fails to anticipate or render obvious the elements set forth in claim 1. The Applicant submits that the rejections of claim 1, and all claims depending therefrom, have been overcome and should be withdrawn.” – As to point B the examiner respectfully disagrees. Applicant asserts that Furlong does not teach “the processing circuitry to output the result to an external device for execution with respect to the actionable output to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset”. During Patent Examination, pending claims must be given their broadest reasonable interpretation consistent with the specification (see MPEP 2111). The broadest reasonable interpretation of the aforementioned limitation within the amendment is to display a result to an external device in which any action can be performed being a change to the current state in regards to an asset that is relating to one of the two claimed aircraft assets. Furlong teaches gathering results from a simulated digital twin in which a debugging action is performed (as mapped above in claims 1, 13, and 18). Sturlaugson teaches performing an update or an adjustment to various subsystems within an aircraft dependent on which asset is being monitored. (as mapped above in claims 1, 13, and 18) Therefor the Examiner respectfully disagrees with the applicants arguments and assert that Furlong-Cleaver-Sturlaugson teaches “the processing circuitry to output the result to an external device for execution with respect to the actionable output to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset”. Furlong teaches: the processing circuitry to output the result to an external device for execution with respect to the actionable output (Pg. 13 – Col. 8 – lines 55-67 & Pg. 14 – Col. 9 – lines 1-2 – “It is assumed that the goal is that device digital twin 23 2 represent the state (e.g., hardware, software, and/or data configurations) of device 222 at Tn. Digital twin management engine 210 then receives device-related results (e.g., results of execution of one or more physics-based models 110, the one or more AI-driven models 112, the one or more simulations 114, the one or more analytics 116, and/or the one or more predictions 118 that constitute device digital twin 232) from device digital twin 232 at time Tn. Digital twin management engine 210 then sends some or all of the device-related results received from device digital twin 232 to a debug technician (tech) and/or a debug system 320. Debug tech/system 320 can then initiate or otherwise take one or more debugging actions in response to at least a portion of the received results.” (equates to the processing circuitry to output the result to an external device for execution with respect to the actionable output as the quote provided shows an actionable output being received by a debug tech via results wherein debugging actions can take place or the actionable output can be utilized. The external system is seen via the debug system being different from the digital twin management engine.))
Sturlaugson teaches: to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset. (Pg. 15 – [0060] – “Further, the digital twin system 406 may be configured to update or synchronize the digital twin of the subsystem. For example, the digital twin system 406 may update or synchronize the digital twin to correspond to the current state of the subsystem as further described below. The digital twin may be a digital or virtual representation of a state or condition of the subsystem. For example, the digital twin may represent an operational or performance state or condition of the subsystem of the vehicle 104.” (equates to: to trigger an adjustment with respect to at least one of the first aircraft asset or the second aircraft asset as the quote shows the updating (adjustment) of a digital twin monitoring a subsystem (first aircraft asset).)
Applicant argues on page 5, “Claim 13 sets forth, inter alia, to identify, in response to the query, at least a first snapshot representing a network of a plurality of digital twin models of aircraft assets and interconnections at a first point in time and a second snapshot representing the plurality of digital twin models and interconnections at a second point in time; determine a correlation between the first snapshot and the second snapshot; generate a result with an actionable output based on the correlation; and output the result to an external device for execution with respect to the actionable output to trigger an adjustment with respect to at least one of a first aircraft asset or a second aircraft asset. The cited references fail to teach or suggest such a medium. The Applicant submits that the rejections of claim 13, and all claims depending therefrom, have been overcome and should be withdrawn.” – As to Point C see Point B
Applicant argues on page 6 – “Claim 18 sets forth, inter alia, identifying, in response to the query, at least a first snapshot representing a network of a plurality of digital twin models of aircraft assets and interconnections at a first point in time and a second snapshot representing the plurality of digital twin models and interconnections at a second point in time; determining a correlation between the first snapshot and the second snapshot; generating a result with an actionable output based on the correlation; and outputting the result to an external device for execution with respect to the actionable output to trigger an adjustment with respect to at least one of a first aircraft asset or a second aircraft asset. The cited references fail to teach or suggest such a method. The Applicant submits that the rejections of claim 18, and all claims depending therefrom, have been overcome and should be withdrawn.” - As to Point D see Point B
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US20170286572 .
– An apparatus may implement a digital twin of a twinned physical system such that one or more sensors to sense values of one or more designated parameters of the twinned physical system. A computer processor may receive data associated with the sensors and, for at least a selected portion of the twinned physical system, monitor a condition of the selected portion of the twinned physical system and/or assess a remaining useful life of the selected portion based at least in part on the sensed values of the one or more designated parameters
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/R.A.W./ Examiner, Art Unit 3667
/Hitesh Patel/ Supervisory Patent Examiner, Art Unit 3667
3/13/26