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 6/17/26. Claims 1, and 3-21 are pending.
Response to Amendments
Amendments filed on 6/17/26 are under consideration. Claims 1, 11, 13, and 18 are amended.
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.)) is captured as a change event and triggers creation of a third snapshot associated with the first digital twin model, (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 is captured as a change event and triggers creation of a third snapshot associated with the first digital twin model l as the quote shows that a change event reflecting performance or state is captured and used later in their training process and thus a third snapshot is captured based on the change event. ))
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 the first connection; 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, wherein a change resulting from the adjustment of at least one of the first aircraft asset or the second aircraft asset, the second digital twin model, and the first connection
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. )), and the first connection (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”) the second digital twin model, and the first connection (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”)
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, wherein a change resulting from the adjustment of 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).) wherein a change resulting from the adjustment of 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 wherein a change resulting from the adjustment of at least one of the first aircraft asset or the second aircraft asset as the quote shows the updating done to a subsystem of a digital twin and thus a change has occurred due to an adjustment.)) 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, wherein a change resulting from the adjustment of 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, wherein a change resulting from the adjustment of 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 the 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 fails to teach and associated connections.
Cleaver teaches and associated connections. (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 and associated connections. As the quote shows )) It would have been an advantageous addition to the system disclosed by Furlong-Sturlaugson to include and associated connections as this allows for digital twin models to have established connections made between them to understand how the devices are working together in a network.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to include and associated connections as this limitation allows for a linking between digital twins to be established and better understand how changes in one twin affect the others.
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.)) is captured as a change event and triggers creation of a third snapshot associated with the first digital twin model, (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 is captured as a change event and triggers creation of a third snapshot associated with the first digital twin model l as the quote shows that a change event reflecting performance or state is captured and used later in their training process and thus a third snapshot is captured based on the change event. ))
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 the first connection; wherein a change resulting from the adjustment of at least one of the first aircraft asset or the second aircraft asset, the second digital twin model, and the first connection.
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. )). and the first connection (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”) the second digital twin model, and the first connection (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”)
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, wherein a change resulting from the adjustment of 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).) wherein a change resulting from the adjustment of 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 wherein a change resulting from the adjustment of at least one of the first aircraft asset or the second aircraft asset as the quote shows the updating done to a subsystem of a digital twin and thus a change has occurred due to an adjustment.)) 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, wherein a change resulting from the adjustment of 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, wherein a change resulting from the adjustment of 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.)) is captured as a change event and triggers creation of a third snapshot associated with the first digital twin model, (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 is captured as a change event and triggers creation of a third snapshot associated with the first digital twin model l as the quote shows that a change event reflecting performance or state is captured and used later in their training process and thus a third snapshot is captured based on the change event. ))
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. and the first connection wherein a change resulting from the adjustment of at least one of the first aircraft asset or the second aircraft asset, the second digital twin model, and the first connection
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. )). and the first connection (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”) the second digital twin model, and the first connection (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”)
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. and the first connection wherein a change resulting from the adjustment of 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).) wherein a change resulting from the adjustment of 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 wherein a change resulting from the adjustment of at least one of the first aircraft asset or the second aircraft asset as the quote shows the updating done to a subsystem of a digital twin and thus a change has occurred due to an adjustment.)) 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 and are persuasive.
Applicant Argues on pages 1-4 , “Claims 1, and 3-21 were rejected under 35 USC 101 as allegedly directed to an abstract idea (mental process). The Applicant respectfully traverses this rejection.
The Applicant notes the Examiners' remarks in response to the previously submitted arguments in the last response. In particular, the Office Action notes "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." Office Action at p. 61. By this response, claims 1, 13, and 18 have been amended to set forth triggering an adjustment of at least one of the first aircraft asset or the second aircraft asset, such that the asset is physically changed and its working status is controlled. As such, the Examiner's concern should be satisfied. The claims are not directed to a mental process. The pending claims are patent eligible under 35 USC 101, and this rejection should be withdrawn.
” -– As to point (A), Examiner respectfully agrees. In particular the inclusion of the limitation, “wherein a change resulting from the adjustment of at least one of the first aircraft asset or the second aircraft asset…” adds a detail of physical manipulation to a real world aircraft component which cannot be performed inside the human mind and thus removes the previous mental process consideration formerly keeping the claim set rejected under 35 U.S.C. 101.
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 2-3, “Claim 1 sets forth, inter alia, snapshots including not only digital twin models of aircraft assets but also connections between those assets. As such, claim 1 sets forth snapshots that are not just of individual digital twins but rather networks of digital twin models including their connections, reflecting the state of that network at a given time. As further set forth in claim 1, a change resulting from the adjustment of at least one of the first aircraft asset or the second aircraft asset is captured as a change event and triggers creation of a third snapshot associated with the first digital twin model, the second digital twin model, and the first connection. None of the cited references teaches or suggests such a change.
As noted in the Office Action, the cited references mention digital twins and simulations. However, none of the cited references teaches or suggests such digital twin network snapshots, let alone comparison of network snapshots of models and connections at different points in time including, as set forth in claim 1, a third snapshot created of the digital twin models and their connection as a result of a change event. Instead, each of Furlong, Cleaver, Sturlaugson, Krimmer, Jackson, Carbognani, and Shaopeng mentions individual digital twins and simulations, and those digital twins may have subsystems included therein, but there is no teaching or suggestion of multiple digital twins of multiple disparate aircraft assets with a connection therebetween that is reflected in a snapshot, as set forth in claim 1.
For at least these reasons, the cited references fail to 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-Cleaver-Sturlaugson does not teach “wherein a change resulting from the adjustment of at least one of the first aircraft asset or the second aircraft asset is captured as a change event and triggers creation of a third snapshot associated with the first digital twin model, the second digital twin model, and the first connection”. 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 make a determination a change has happened to the digital twin based on an alteration made and thus capture the change across the different digital twins and a defined linked between the digital twins. Furlong teaches capturing a change of the condition of the digital twin and using the captured change for training later on (as mapped above in claims 1, 13, and 18). Cleaver teaches a a plurality of digital twins and making connections between the digital twins for performance monitoring . (as mapped above in claims 1, 13, and 18). And Finally Sturlaugson teaches a specific updating of the digital twin subsystem and the specific adjustment being mentioned. Therefor the Examiner respectfully disagrees with the applicants arguments and assert that Furlong-Cleaver-Sturlaugson teaches “wherein a change resulting from the adjustment of at least one of the first aircraft asset or the second aircraft asset is captured as a change event and triggers creation of a third snapshot associated with the first digital twin model, the second digital twin model, and the first connection”.
Furlong teaches: is captured as a change event and triggers creation of a third snapshot associated with the first digital twin model, (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 is captured as a change event and triggers creation of a third snapshot associated with the first digital twin model l as the quote shows that a change event reflecting performance or state is captured and used later in their training process and thus a third snapshot is captured based on the change event. ))
Cleaver teaches: the second digital twin model, and the first connection (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”)
Sturlaugson teaches: wherein a change resulting from the adjustment of 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 wherein a change resulting from the adjustment of at least one of the first aircraft asset or the second aircraft asset as the quote shows the updating done to a subsystem of a digital twin and thus a change has occurred due to an adjustment.))
Applicant argues on page 5, “Claim 13 sets forth, inter alia, snapshots including not only digital twin
models of aircraft assets but also connections between those assets. As such, claim 13 sets forth snapshots that are not just of individual digital twins but rather networks of digital twin models including their connections, reflecting the state of that network at a given time. As further set forth in claim 13, a change resulting from the adjustment of at least one of the first aircraft asset or the second aircraft asset is captured as a change event and triggers creation of a third snapshot associated with the first digital twin model, the second digital twin model, and the first connection. None of the cited references teaches or suggests such a change. 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, snapshots including not only digital twin models of aircraft assets but also connections between those assets. As such, claim 18 sets forth snapshots that are not just of individual digital twins but rather networks of digital twin models including their connections, reflecting the state of that network at a given time. As further set forth in claim 18, a change resulting from the adjustment of at least one of the first aircraft asset or the second aircraft asset is captured as a change event and triggers creation of a third snapshot associated with the first digital twin model, the second digital twin model, and the first connection. None of the cited references teaches or suggests such a change. 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
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
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/R.A.W./ Examiner, Art Unit 3667
/Hitesh Patel/ Supervisory Patent Examiner, Art Unit 3667
9/1/26
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