DETAILED ACTION
The instant application having Application No. 18/667188 filed on 05/17/2024 is presented for examination by the examiner.
Examiner Notes
Examiner cites particular columns and line numbers in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner.
Drawings
The applicant’s drawings submitted are acceptable for examination purposes.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-9 and 18-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Claim 1-9 and 18-20 is rejected under 35 U.S.C. 101 as directed to non-statutory subject matter of software per se.
Regarding claim 1 and 18, although the preamble of the claim recites “a digital twin system “and GPU server, the body of the claim does not positively recite any elements of hardware. The body of the claim recites ‘multiple twin model modules’, “multiple digital factory modules” and “a simulator module” In light of the specification, the ‘multiple twin model modules’, “multiple digital factory modules” and “a simulator module” are implemented in software, which is non-statutory subject matter. Therefore, it is reasonable for one of ordinary skill in the art to interpret the aforementioned logic is a software component.
Claims 2-9 and 19-20 are rejected under 35 U.S.C. 101 as directed to non-statutory subject matter for at least the reason stated above. Claims 2-9 and 19-20 are depended on claim 1 and 18, however, they do not add any feature or subject matter that would solve any of the non-statutory deficiencies of claim 1 and 18.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim 1, 3, and 7-9 are rejected under 35 U.S.C. 103(a) as being unpatentable over US 2022/0164502 to Pei et al. (hereafter “Pei”) in view of US 2023/0082099 to Schmidt et al. (hereafter “Schmidt”)
As per claim 1, Pei discloses A digital twin system comprising:
multiple twin model modules (FIGs. 1-2; paragraphs 0039, 0041 and 0075-0076: “Physical space elements include the physical entity of the pump machine unit, the running state of the pump machine unit and the control process of the pump machine unit. Virtual space elements include physical model of pump machine unit, virtual state of pump machine unit and virtual control of pump machine unit to realize digital simulation model similar to physical space. The digital twin includes the physical object twin, the operation process twin and the control performance twin. Digital twin model realizes information interaction and digital mapping between physical space and virtual space of running pump machine unit through data-driven dynamic optimization simulation model.” [Wingdings font/0xE0] physical object twin, running process twin and control process twin), wherein respective ones of the twin model modules i) comprise control logic (FIGs. 1-2 and 4-5; paragraphs 0008, 0015, 0022, 0028, 0067-0068 and 0076: “establishment of control model, including: establishing a mapping of a control process same with the physical entity to make the digital twin body be capable of imitating a same control process and thereby realize adjustment of related parameters, and thereby realizing the control performance twin” [Wingdings font/0xE0] FIG. 5: simulation feedback [Wingdings font/0xE0] data decision [Wingdings font/0xE0] control data [Wingdings font/0xE0] control center) and ii) are configured to virtualize respective control systems for respective ones of multiple factories (FIGs. 1-2 and 4-5; paragraphs 0075-0077: “The physical object twin, the operation process twin and the control performance twin of the physical body are realized through the digital space and the digital twin, so as to realize the mapping from the physical body to the virtual twin body. The information portal provide human-computer interaction platform, not only can access all database and module, and can realize consistent with the physical space in visual effect on the geometric structure of virtual scene, can realize consistent with physical model motion process of virtual scene, can be controlled with physical model consistent with the virtual scene, to achieve the 1:1 mirror physical space and virtual space. The optimization module provides optimization scheme for the adjustment of new working conditions”);
ii) are controlled by respective ones of the multiple twin model modules to create a virtual factory model (FIGs. 1-2 and 4-5; paragraphs 0075-0077: “The physical object twin, the operation process twin and the control performance twin of the physical body are realized through the digital space and the digital twin, so as to realize the mapping from the physical body to the virtual twin body. The information portal provide human-computer interaction platform, not only can access all database and module, and can realize consistent with the physical space in visual effect on the geometric structure of virtual scene, can realize consistent with physical model motion process of virtual scene, can be controlled with physical model consistent with the virtual scene, to achieve the 1:1 mirror physical space and virtual space. The optimization module provides optimization scheme for the adjustment of new working conditions”); and
a simulator module configured to manage the multiple twin model modules (FIGs. 5-6; paragraphs 0030, 0058, 0062, 0068 and 0080-0081: “When user demand conditions changes, the system and method are used to provide new solutions of adjustment of new working condition through optimization algorithm and machine learning, to evaluate multiple schemes and then enter into the digital twin body for simulation calculation, and make decision the result of the simulation and then delivery to the pump machine unit control center.”).
Pei does not explicitly disclose multiple digital factory modules, wherein respective ones of the digital factory modules i) are configured to virtualize respective ones of the multiple factories.
Schmidt further discloses multiple digital factory modules, wherein respective ones of the digital factory modules (FIGs. 1 and 3; paragraphs 0006, 0027-0028 and 0037-0038: “Digital twin environment 103 includes one or more virtual representations of the one or more entities or systems operating in industrial automation environment 101. In an ideal model, digital twin environment 103 can replicate exact performance of the devices in industrial automation environment 101. For example, a digital twin in digital twin environment 103 that represents a motor of industrial automation environment 101 may demonstrate a faithful virtual representation with respect to vibration, motor speed, electrical and mechanical output, and more. To model devices with complete fidelity requires sufficient processing power by a computing device and sensor data obtainable in industrial automation environment 101.” [Wingdings font/0xE0] blocks 322-328 (factory modules)) i) are configured to virtualize respective ones of the multiple factories (FIGs. 1 and 3; paragraphs 0006, 0027-0028 and 0037-0038: “Digital twin environment 103 includes one or more virtual representations of the one or more entities or systems operating in industrial automation environment 101. In an ideal model, digital twin environment 103 can replicate exact performance of the devices in industrial automation environment 101. For example, a digital twin in digital twin environment 103 that represents a motor of industrial automation environment 101 may demonstrate a faithful virtual representation with respect to vibration, motor speed, electrical and mechanical output, and more. To model devices with complete fidelity requires sufficient processing power by a computing device and sensor data obtainable in industrial automation environment 101.” [Wingdings font/0xE0] blocks 312-318 (multiple factories)).
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Schmidth into Pei’s teaching because it would provide for the purpose of configuring digital twin models and simulating industrial systems based on characteristics of digital twins (Schmidt, paragraph 0006).
As per claim 3, Pei discloses wherein the simulator module is configured to set up conditions of the control logic for controlling a virtual factory in each twin model module (FIGs. 5-6; paragraphs 0023, 0027, 0062, 0068 and 0079: “When the user enters the demand condition, optimization algorithm and machine learning start to calculate the scheme. The calculated scheme data flow is evaluated and then enters the digital twin for simulation calculation; (3) the results of the simulation calculation are evaluated and fed back to the decision-making machine. After the data decision, the data control is finally obtained and transmitted to the pump machine unit control center to control the pump machine unit for the adjustment of relevant parameters, so as to realize the optimized operation and adjustment of the pump machine unit.”).
As per claim 7, Pei does not explicitly disclose wherein the simulator module comprises a model manager configured to manage connection with each twin model module or each digital factory module.
Schmidt further discloses wherein the simulator module comprises a model manager configured to manage connection with each twin model module or each digital factory module (paragraphs 0028 and 0061: “In an ideal model, digital twin environment 103 can replicate exact performance of the devices in industrial automation environment 101. For example, a digital twin in digital twin environment 103 that represents a motor of industrial automation environment 101 may demonstrate a faithful virtual representation with respect to vibration, motor speed, electrical and mechanical output, and more. To model devices with complete fidelity requires sufficient processing power by a computing device and sensor data obtainable in industrial automation environment 101. In other embodiments, a digital twin in digital twin environment 103 may represent an entity with less than full fidelity of all characteristics and personalities. In order to obtain entity characteristics and performance data, among other things, from devices in industrial automation environment 101, digital twin environment 103 can communicate with industrial automation environment via sensor interface 102. Sensor interface 102 can comprise one or more wireless or wired connections, application programming interfaces (APIs), or other communication protocol configured to provide real-time or simulated sensor data from one or more entities of industrial automation environment 101”).
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Schmidth into Pei’s teaching because it would provide for the purpose of configuring digital twin models and simulating industrial systems based on characteristics of digital twins (Schmidt, paragraph 0006).
As per claim 8, Pei discloses wherein each of the multiple twin model modules is set to be combined with any one of the multiple digital factory modules (FIGs. 1-2 and 4-5; paragraphs 0075-0077: “The physical object twin, the operation process twin and the control performance twin of the physical body are realized through the digital space and the digital twin, so as to realize the mapping from the physical body to the virtual twin body.”)
As per claim 9, Pei does not explicitly disclose a data analyzing module configured to receive data from at least one of each twin model module, each digital factory module, or the simulator module; and
analyze the received data.
Schmidt further discloses a data analyzing module configured to receive data from at least one of each twin model module (FIG. 5; paragraphs 0025, 0031-0032 and 0036), each digital factory module (FIG. 5; paragraphs 0025, 0031-0032 and 0036), or the simulator module; and
analyze the received data (FIG. 5; paragraphs 0025, 0031-0032 and 0036).
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Schmidth into Pei’s teaching because it would provide for the purpose of configuring digital twin models and simulating industrial systems based on characteristics of digital twins (Schmidt, paragraph 0006).
Claim 2 is rejected under 35 U.S.C. 103(a) as being unpatentable over Pei in view of Schmidt, as applied to claim 1, and further in view of US 2021/0109837 to Rakshit and US 2022/0335824 to Carson et al. (hereafter “Carson”)
As per claim 2, Pei does not explicitly disclose wherein the multiple twin model modules are executed on at least one graphics processing unit (GPU) server, and when a first twin model module from among the multiple twin model modules is executed, the simulator module assigns resources for executing the first twin model module in the at least one GPU server.
Rakshit further discloses wherein the multiple twin model modules are executed on at least one server (FIGs. 2B; paragraphs 0084 and 0087), and when a first twin model module from among the multiple twin model modules is executed, the simulator module assigns resources for executing the first twin model module in the at least one server (FIGs. 2B; paragraphs 0084 and 0087).
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Rakshit into Pei’s teaching and Schmidt’s teaching because it would provide for the purpose of providing computing resources via the host system hardware to one or more containers comprising the containerized computer environment for the digital twin module software to execute and perform functions of the digital twin module (Rakshit, paragraph 0084).
Carson further discloses the server is GPU sever (paragraphs 0140 and 0229).
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Carson into Pei’s teaching, Schmidt’s teaching and Rakshit’s teaching because it would provide for the purpose of information can be rendered based on a digital twin generated and maintained by the digital twin module of the server (Carson, paragraph 0350).
Claim 4 is rejected under 35 U.S.C. 103(a) as being unpatentable over Pei in view of Schmidt, as applied to claim 3, and further in view of US 2021/0109837 to Rakshit and US 2004/0268283 to Perry et al. (hereafter “Perry”) and US 2002/0144282 to Van Ee (hereafter “Van”)
As per claim 4, Pei does not explicitly disclose wherein the simulator module is configured to:
create webpages to set up the conditions of the control logic; and set up the conditions of the control logic using set values inputted through the webpages.
Pery further discloses wherein the simulator module is configured to:
create webpages (paragraphs 0047-0049 and 0121: “According to one embodiment, the schematic diagram generation module 416 used to generate the schematic web pages is the WEBENCH Electrical Simulator. While the illustrated embodiment uses the WEBENCH Electrical Simulator module for generating schematic diagram web pages, the present invention is not limited to any particular schematic diagram generation module 416. Any module capable of generating a schematic diagram based on a list of components and schematic information may be used.”) to set up the conditions of the control logic (FIG. 41; paragraphs 0047-0049 and 0121-0125)
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Perry into Pei’s teaching and Schmidt’s teaching because it would provide for the purpose of enabling a user to create, modify, simulate and save an electrical circuit using an Internet browser over an Internet connection (Perry, paragraph 0048).
Van discloses set up the conditions of the control logic using set values inputted through the webpages (paragraph 0025).
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Van into Pei’s teaching, Schmidt’s teaching, and Perry’s teaching because it would provide for the purpose of letting the user specify his/her desired configuration of A/V system 102 through text and/or mouse input via a specific Web site (Van, paragraph 0025).
Claim 5 is rejected under 35 U.S.C. 103(a) as being unpatentable over Pei in view of Schmidt, as applied to claim 1, and further in view of US 2023/0132451 to Makker et al. (hereafter “Makker”)
As per claim 5, Pei does not explicitly disclose wherein the simulator module is configured to request any one of start, end, and restart of a simulation from each twin model module.
Makker further discloses wherein the simulator module is configured to request any one of start, end, and restart of a simulation from each twin model module (paragraphs 0234 and 0237: “upon an initial connection the digital twin and mobile circuitry exchange data messages with data for displaying a simulated scene in the digital twin, e.g., according to a default starting position. For example, a virtual simulation may begin at an entrance to the enclosure, or at any other point of interest (e.g., chosen by a user). In some embodiments when the user is actually located in the enclosure being represented, the starting position may correspond to the current location of the user (e.g., an initiate message may provide geographic coordinates of a GPS-equipped user remote controller). Data or commands within messages between the mobile circuitry and the digital twin may include navigation actions (resulting in updated views being returned from the digital twin) and/or control actions (e.g., point and click) to indicate a desired change in an alterable state of a target.”).
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Makker into Pei’s teaching and Schmidt’s teaching because it would provide for the purpose of the mobile circuitry and the digital twin exchange one or more messages that enable a user to control (including to monitor and/or alter) operation of real targets (e.g., by manipulating their virtual twin elements in digital twin) (Makker, paragraph 0234).
Claim 6 is rejected under 35 U.S.C. 103(a) as being unpatentable over Pei in view of Schmidt, as applied to claim 1, and further in view of US 2019/0258747 to Milev.
As per claim 6, Pei does not explicitly disclose wherein the simulator module is configured to:
request status information from a twin model module; and
receive the status information from the twin model module.
Milev further discloses wherein the simulator module is configured to:
request status information from a twin model module (FIGs. 3-4; paragraphs 0046-0047: “receiving a query input from a user via a user device (e.g., computer, audio, video, etc.). For example, the query input may include a request for information from or otherwise about a digital twin executing on a host platform. As a non-limiting example, the query input may include speech that is spoken by the user and input via an audio device such as a microphone, headset, telephone, smartphone, etc. As another example, the query may be input via a text message entered via a keyboard or other input means. The substance of the query may include a request for information about an operating performance being modeled by the twin.”); and
receive the status information from the twin model module (FIGs. 3-4; paragraphs 0046-0047: “the determining the response in 430 may include generating a word or a phrase that provides knowledge about the component based on an operating state of the component.”).
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Milev into Pei’s teaching and Schmidt’s teaching because it would provide for the purpose of providing an interactive digital twin that can communicate (e.g., via speech, text, gestures, etc.) with a user and provide the user with knowledge and responses to queries and requests (Milev, paragraph 0005).
Claims 10, 13, and 15-16 are rejected under 35 U.S.C. 103(a) as being unpatentable over Pei in view of US 2023/0351819 to Robles et al. (hereafter “Robles”) and further in view of US 2019/0266295 to Masuda et al. (hereafter “Masuda”)
As per claim 10, Pei discloses A method for controlling a digital twin system comprising:
registering, by a simulator module, models for multiple digital factories, wherein the models (FIGs. 1; paragraphs 0026-0027, 0071-0072 and 0075-0076: “step 8: construction of data model, including: building a computable data model, using methods of machine learning, iterative optimization and intelligent decision to realize data mirroring and data exchanging of the physical body and the virtual twin body based on multi-source data of database;” [Wingdings font/0xE0] creating/constructing models) for digital factories are virtual representations (FIGs. 1; paragraphs 0026-0027, 0071-0072 and 0075-0076: “step 8: construction of data model, including: building a computable data model, using methods of machine learning, iterative optimization and intelligent decision to realize data mirroring and data exchanging of the physical body and the virtual twin body based on multi-source data of database;” [Wingdings font/0xE0] virtual/digital twin body) of multiple factories representations (FIGs. 1; paragraphs 0026-0027, 0071-0072 and 0075-0076: “step 8: construction of data model, including: building a computable data model, using methods of machine learning, iterative optimization and intelligent decision to realize data mirroring and data exchanging of the physical body and the virtual twin body based on multi-source data of database;” [Wingdings font/0xE0] physical body);
wherein the multiple twin models are virtual representations (FIGs. 1-2; paragraphs 0039, 0041 and 0075-0076: “Physical space elements include the physical entity of the pump machine unit, the running state of the pump machine unit and the control process of the pump machine unit. Virtual space elements include physical model of pump machine unit, virtual state of pump machine unit and virtual control of pump machine unit to realize digital simulation model similar to physical space. The digital twin includes the physical object twin, the operation process twin and the control performance twin. Digital twin model realizes information interaction and digital mapping between physical space and virtual space of running pump machine unit through data-driven dynamic optimization simulation model.” [Wingdings font/0xE0] physical object twin, running process twin and control process twin) of respective control systems for respective ones of the multiple factories (FIGs. 1-2; paragraphs 0039, 0041 and 0075-0076: physical entities [Wingdings font/0xE0] running state of pump machine unit [Wingdings font/0xE0] control process of pump machine units);
generating, by the first twin model, control logic (paragraphs 0005, 0008, 0018 and 0012: “A data model of the digital twin includes a perception monitoring layer, a network transmission layer, a data blending layer and an interactive control layer. The perception monitoring layer is configured to provide a monitoring information flow for the physical object twinning of the digital twin. The network transmission layer is configured to provide a control information flow for the operation process twinning of the digital twin. The data blending layer is configured to provide a data information flow for the control performance twinning of the digital twin. The interactive control layer is configured to provide a decision control flow for the digital twin.”) for a first digital factory from among the multiple digital factories (paragraphs 0005, 0008, 0018 and 0012: “The pump machine unit data collection center is configured to perform a collection of flow in each the pipeline, a collection of start-stop state of each the pump, a collection of water pressure in each the pipeline, a collection of opening degree of the electric valve, a collection of speed of each the pump, a collection of power of each the pump and a collection of other required data. And the pump machine unit control center is configured to perform a control of speed of each the speed, a control of opening degree of the electric valve and a control of start-stop of each the pump.”);
requesting, by the simulator module, start of a simulation from a first twin model from among multiple twin models (FIG. 5; paragraphs 0079: “When the user enters the demand condition, optimization algorithm and machine learning start to calculate the scheme. The calculated scheme data flow is evaluated and then enters the digital twin for simulation calculation” [Wingdings font/0xE0] user enters demand/evaluated scheme data flow enters/starts the virtual twin body).
Pei does not explicitly disclose initializing, by a simulator module, models for multiple digital factories; transferring, by the first twin model, a command generated based on the control logic to a first digital factory module; and processing, by the first digital factory module, an operation corresponding to the command received from the first twin model to conduct a simulation.
Robles further discloses initializing, by a simulator module, models for multiple digital factories (FIG. 7; paragraph 0089: “identifying a component effect on a performance of a vehicle may begin with initializing a model for a vehicle performance simulation at least by generating a simulation configuration file for a mechanical system configured to control and that in operation may control the performance of the vehicle”).
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Robles into Pei’s teaching because it would provide for the purpose of using the simulation configuration file for the mechanical system and the simulation configuration file for the power system and the modification scripting of the degraded mode of the selected component, a simulation generating performance data for the vehicle; and transforming the performance data to a visualization of the performance of the vehicle (Robles, paragraph 0007).
Masuda further discloses transferring, by the first twin model, a command generated based on the control logic to a first digital factory module (paragraph 0120: “The driver's real-life approach to driving the vehicle is described by the onboard data 156 that is used to generate the simulations. In some embodiments, the scheduler system 199 includes software (e.g., the modeling application 133 whose operation is controlled by the determination module 204) that generates a “driver behavior model” of the driver's real-life approach to driving the vehicle 123 based on the onboard data 156, and this driver behavior model is used to operate the modified digital twin in a manner that is consistent with the driver's real-life approach to driving the vehicle 123 in the real-world.” [Wingdings font/0xE0] the driver behavior model operating the digital twin); and
processing, by the first digital factory module, an operation corresponding to the command received from the first twin model to conduct a simulation (paragraph 0120: the digital twin performing the operations in response to the driver behavior model).
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Masuda into Pei’s teaching and Robles’ teaching because it would provide for the purpose of driver behavior model is used to operate the modified digital twin in a manner that is consistent with the driver's real-life approach to driving the vehicle in the real-world (Masuda, paragraph 0120).
As per claim 13, Pei does not explicitly disclose setting up, by the simulator module, conditions of the control logic for controlling each virtual factory with each twin model module.
Masuda further discloses setting up, by the simulator module, conditions of the control logic for controlling each virtual factory with each twin model module (paragraph 0120: “The driver's real-life approach to driving the vehicle is described by the onboard data 156 that is used to generate the simulations. In some embodiments, the scheduler system 199 includes software (e.g., the modeling application 133 whose operation is controlled by the determination module 204) that generates a “driver behavior model” of the driver's real-life approach to driving the vehicle 123 based on the onboard data 156, and this driver behavior model is used to operate the modified digital twin in a manner that is consistent with the driver's real-life approach to driving the vehicle 123 in the real-world.”[Wingdings font/0xE0] generating driver behavior model (control logic as claimed))
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Masuda into Pei’s teaching and Robles’ teaching because it would provide for the purpose of driver behavior model is used to operate the modified digital twin in a manner that is consistent with the driver's real-life approach to driving the vehicle in the real-world (Masuda, paragraph 0120).
As per claim 15, Pei discloses wherein each of the multiple twin model modules is set to be combined with any one of the multiple digital factory modules (FIGs. 1-2 and 4-5; paragraphs 0075-0077: “The physical object twin, the operation process twin and the control performance twin of the physical body are realized through the digital space and the digital twin, so as to realize the mapping from the physical body to the virtual twin body.”)
As per claim 16, Pei discloses reporting, by each digital factory module,
a result corresponding to a control command to a twin model module connected with this digital factory module (FIG. 5; paragraphs 0079: data of running state [Wingdings font/0xE0] information portal/database/data fusion in digital space [Wingdings font/0xE0] simulation calculation in virtual twin body)
Claim 11 is rejected under 35 U.S.C. 103(a) as being unpatentable over Pei in view of Robles and Masuda, as applied to claim 10, and further in view of US 2007/0043568 to Dhanakshirur et al. (hereafter “Dhanakshirur”) and US 2024/0037463 to Ryali et al. (hereafter “Ryali”)
As per claim 11, Pei does not explicitly disclose wherein the simulator module operates on a central processing unit (CPU) server and the multiple twin models are executed on at least one graphics processing unit (GPU) server.
Dhanakshirur further discloses wherein the simulator module operates on a central processing unit (CPU) server (paragraph 0009)
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Dhanakshirur into Pei’s teaching, Robles’ teaching and Masuda’s teaching because it would provide for the purpose of The processor can be programmed to execute a voice application having a plurality of audio prompts, play audio if a pre-stored audio is available for a particular prompt, capture text when no pre-stored audio is available, and forward the captured text to a prompt collecting tool (Dhanakshirur, paragraph 0009).
Ryali further discloses the multiple twin models are executed on at least one graphics processing unit (GPU) server (paragraph 0058).
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Ryali into Pei’s teaching, Robles’ teaching, Masuda’s teaching, and Dhanakshirur’s teaching because it would provide for the purpose of A characteristic illustration of the necessity of a GPU is when dealing with large amounts of data (e.g., video data) where a need for processing it at the edge device level (Ryali, paragraph 0058).
Claim 12 is rejected under 35 U.S.C. 103(a) as being unpatentable over Pei in view of Robles, Masuda, Dhanakshirur, and Ryali, as applied to claim 11, and further in view of US 2020/0134374 to Oros.
As per claim 12, Pei does not explicitly disclose wherein the models for the multiple digital factories are executed on the at least one GPU server.
Oros further discloses wherein the models for the multiple digital factories are executed on the at least one GPU server (paragraphs 0029 and 0083).
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Oros into Pei’s teaching, Robles’ teaching, Masuda’s teaching, Dhanakshirur’s teaching and Ryali’s teaching because it would provide for the purpose of A characteristic illustration of the necessity of a GPU is when dealing with large amounts of data (e.g., video data) where a need for processing it at the edge device level to dynamically updating, or retraining and updating, AI/ML, models in digital processes at runtime (Oros, paragraph 0004).
Claim 14 is rejected under 35 U.S.C. 103(a) as being unpatentable over Pei in view of Robles, Masuda, as applied to claim 13, and further in view of Perry and Van.
As per claim 14, Pei does not explicitly disclose creating, by the simulator module, webpages to set up the conditions of the control logic; and
setting up, by the simulator module, the conditions of the control logic using set values inputted through the webpages.
Perry further discloses creating, by the simulator module, webpages (paragraphs 0047-0049 and 0121: “According to one embodiment, the schematic diagram generation module 416 used to generate the schematic web pages is the WEBENCH Electrical Simulator. While the illustrated embodiment uses the WEBENCH Electrical Simulator module for generating schematic diagram web pages, the present invention is not limited to any particular schematic diagram generation module 416. Any module capable of generating a schematic diagram based on a list of components and schematic information may be used.”) to set up the conditions of the control logic (FIG. 41; paragraphs 0047-0049 and 0121-0125)
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Perry into Pei’s teaching, Robles’ teaching and Masuda’s teaching because it would provide for the purpose of enabling a user to create, modify, simulate and save an electrical circuit using an Internet browser over an Internet connection (Perry, paragraph 0048).
Van further discloses setting up, by the simulator module, the conditions of the control logic using set values inputted through the webpages (paragraph 0025).
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Van into Pei’s teaching, Robles’ teaching, Masuda’s teaching, and Perry’s teaching because it would provide for the purpose of letting the user specify his/her desired configuration of A/V system 102 through text and/or mouse input via a specific Web site (Van, paragraph 0025).
Claim 17 is rejected under 35 U.S.C. 103(a) as being unpatentable over Pei in view of Robles, Masuda, as applied to claim 13, and further in view of Schmidth and US 2013/01003376 to Gaddam et al. (hereafter “Gaddam”).
As per claim 17, Pei does not explicitly disclose receiving, by a data analyzing module, data from at least one of each twin model module, each digital factory module, and the simulator module; and
analyzing, by the data analyzing module, the received data.
Schmidth further discloses receiving, by a data analyzing module, data from at least one of each twin model module (FIG. 5; paragraphs 0025, 0031-0032 and 0036), each digital factory module (FIG. 5; paragraphs 0025, 0031-0032 and 0036); and
analyzing, by the data analyzing module, the received data (FIG. 5; paragraphs 0025, 0031-0032 and 0036).
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Schmidth into Pei’s teaching, Robles’ teaching and Masuda’s teaching because it would provide for the purpose of configuring digital twin models and simulating industrial systems based on characteristics of digital twins (Schmidt, paragraph 0006).
Gaddam further discloses receiving, by a data analyzing module, data from the simulator module (paragraph 0053).
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Gaddam into Pei’s teaching, Robles’ teaching, Masuda’s teaching, and Schmidth’s teaching because it would provide for the purpose of to determine whether the information is valid (Gaddam, paragraph 0053).
Claims 18-20 are rejected under 35 U.S.C. 103(a) as being unpatentable over Pei in view of Schmidt, further in view of Rakshit and Carson.
As per claim 18, Pei discloses multiple twin model modules (FIGs. 1-2; paragraphs 0039, 0041 and 0075-0076: “Physical space elements include the physical entity of the pump machine unit, the running state of the pump machine unit and the control process of the pump machine unit. Virtual space elements include physical model of pump machine unit, virtual state of pump machine unit and virtual control of pump machine unit to realize digital simulation model similar to physical space. The digital twin includes the physical object twin, the operation process twin and the control performance twin. Digital twin model realizes information interaction and digital mapping between physical space and virtual space of running pump machine unit through data-driven dynamic optimization simulation model.” [Wingdings font/0xE0] physical object twin, running process twin and control process twin), wherein respective ones of the multiple twin model modules i) comprise control logic (FIGs. 1-2 and 4-5; paragraphs 0008, 0015, 0022, 0028, 0067-0068 and 0076: “establishment of control model, including: establishing a mapping of a control process same with the physical entity to make the digital twin body be capable of imitating a same control process and thereby realize adjustment of related parameters, and thereby realizing the control performance twin” [Wingdings font/0xE0] FIG. 5: simulation feedback [Wingdings font/0xE0] data decision [Wingdings font/0xE0] control data [Wingdings font/0xE0] control center) and ii) are configured to virtualize respective control systems for respective ones of multiple factories (FIGs. 1-2 and 4-5; paragraphs 0075-0077: “The physical object twin, the operation process twin and the control performance twin of the physical body are realized through the digital space and the digital twin, so as to realize the mapping from the physical body to the virtual twin body. The information portal provide human-computer interaction platform, not only can access all database and module, and can realize consistent with the physical space in visual effect on the geometric structure of virtual scene, can realize consistent with physical model motion process of virtual scene, can be controlled with physical model consistent with the virtual scene, to achieve the 1:1 mirror physical space and virtual space. The optimization module provides optimization scheme for the adjustment of new working conditions”); and ii) are controlled by respective ones of the multiple twin model modules (FIGs. 1-2 and 4-5; paragraphs 0075-0077: “The physical object twin, the operation process twin and the control performance twin of the physical body are realized through the digital space and the digital twin, so as to realize the mapping from the physical body to the virtual twin body. The information portal provide human-computer interaction platform, not only can access all database and module, and can realize consistent with the physical space in visual effect on the geometric structure of virtual scene, can realize consistent with physical model motion process of virtual scene, can be controlled with physical model consistent with the virtual scene, to achieve the 1:1 mirror physical space and virtual space. The optimization module provides optimization scheme for the adjustment of new working conditions”).
Pei does not explicitly disclose A graphics processing unit (GPU) server comprising: Multiple twin model modules; and multiple digital factory modules, wherein respective ones of the digital factory modules i) are configured to create respective virtual factory models by virtualizing respective ones of the multiple factories.
Schmidth further discloses multiple digital factory modules, wherein respective ones of the digital factory modules (FIGs. 1 and 3; paragraphs 0006, 0027-0028 and 0037-0038: “Digital twin environment 103 includes one or more virtual representations of the one or more entities or systems operating in industrial automation environment 101. In an ideal model, digital twin environment 103 can replicate exact performance of the devices in industrial automation environment 101. For example, a digital twin in digital twin environment 103 that represents a motor of industrial automation environment 101 may demonstrate a faithful virtual representation with respect to vibration, motor speed, electrical and mechanical output, and more. To model devices with complete fidelity requires sufficient processing power by a computing device and sensor data obtainable in industrial automation environment 101.” [Wingdings font/0xE0] blocks 322-328 (factory modules)) i) are configured to create respective virtual factory models by virtualizing respective ones of the multiple factories (FIGs. 1 and 3; paragraphs 0006, 0027-0028 and 0037-0038: “Digital twin environment 103 includes one or more virtual representations of the one or more entities or systems operating in industrial automation environment 101. In an ideal model, digital twin environment 103 can replicate exact performance of the devices in industrial automation environment 101. For example, a digital twin in digital twin environment 103 that represents a motor of industrial automation environment 101 may demonstrate a faithful virtual representation with respect to vibration, motor speed, electrical and mechanical output, and more. To model devices with complete fidelity requires sufficient processing power by a computing device and sensor data obtainable in industrial automation environment 101.” [Wingdings font/0xE0] blocks 312-318 (multiple factories)).
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Schmidth into Pei’s teaching because it would provide for the purpose of configuring digital twin models and simulating industrial systems based on characteristics of digital twins (Schmidt, paragraph 0006).
Rakshit further discloses A server comprising: Multiple twin model modules (FIGs. 2B; paragraphs 0084 and 0087).
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Rakshit into Pei’s teaching and Schmidt’s teaching because it would provide for the purpose of providing computing resources via the host system hardware to one or more containers comprising the containerized computer environment for the digital twin module software to execute and perform functions of the digital twin module (Rakshit, paragraph 0084).
Casrson further discloses the server is GPU sever (paragraphs 0140 and 0229).
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Carson into Pei’s teaching, Schmidt’s teaching and Rakshit’s teaching because it would provide for the purpose of information can be rendered based on a digital twin generated and maintained by the digital twin module of the server (Carson, paragraph 0350).
As per claim 19, Pei does not explicitly disclose wherein, when a first twin model module from among the multiple twin model modules is executed, resources for executing the first twin model module are assigned in the GPU server.
Raskshit further discloses wherein, when a first twin model module from among the multiple twin model modules is executed, resources for executing the first twin model module are assigned in the server (FIGs. 2B; paragraphs 0084 and 0087).
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Rakshit into Pei’s teaching and Schmidt’s teaching because it would provide for the purpose of providing computing resources via the host system hardware to one or more containers comprising the containerized computer environment for the digital twin module software to execute and perform functions of the digital twin module (Rakshit, paragraph 0084).
Casrson further discloses the server is GPU sever (paragraphs 0140 and 0229).
It would have been obvious to a person having ordinary skill in the art at the time before the effective filling date of the claimed invention to combine a teaching of Carson into Pei’s teaching, Schmidt’s teaching and Rakshit’s teaching because it would provide for the purpose of information can be rendered based on a digital twin generated and maintained by the digital twin module of the server (Carson, paragraph 0350).
As per claim 20, Pei discloses wherein each twin model module is configured to set up conditions of control logic for controlling a virtual factory (FIGs. 5-6; paragraphs 0023, 0027, 0062, 0068 and 0079: “When the user enters the demand condition, optimization algorithm and machine learning start to calculate the scheme. The calculated scheme data flow is evaluated and then enters the digital twin for simulation calculation; (3) the results of the simulation calculation are evaluated and fed back to the decision-making machine. After the data decision, the data control is finally obtained and transmitted to the pump machine unit control center to control the pump machine unit for the adjustment of relevant parameters, so as to realize the optimized operation and adjustment of the pump machine unit.”).
Conclusion
The following prior art made of record and not relied upon is cited to establish the level of skill in the applicant’s art and those arts considered reasonably pertinent to applicant’s disclosure. See MPEP 707.05(c).
Prior arts:
US 2023/0306149 to Gaganam
digital twin management engine 310 is configured to perform a benchmark function 312 (e.g., comparing performance metrics of the units of equipment which the digital twins virtually represent to one or more standards, goals, preferences, and/or requirements), a monitor function 314 (e.g., obtaining and tracking data from the digital twins and/or units of equipment, as well as receiving data from other systems and/or users), a report function 316 (e.g., sending data to the digital twins and/or units of equipment, as well as sending data to other systems and/or users), as well as one or more other management functions 318.
US 2023/0128173 to Sha
(i) a model component which is configured to represent one or more parameters of the corresponding physical component, and which comprises one or more interfaces to enable communication between templates integrated within the virtual representation; (ii) a simulation component which is configured to provide evaluation of the virtual representation prior to the virtual representation being used to manage the physical components;
US 2021/0248289 to Fasano
As variant, the digital twin 4 of the twinned physical system 3, i.e. the digital virtual replicas are constantly updated and analyzed by measuring data from their real counterparts, i.e. the twinned physical system or object 3 and from the physical environment that surrounds them in their real physical world. The digital platform 1 is able to react on the digital twin 4 and it can run analysis related to historical data, current data and forecasts.
US 2020/0030979 to Bank
one or more processors to execute virtual modules 252 to generate digital twins for simulation of real counterparts, such as robotic unit 231, and objects 222, 214. For example, the virtual modules 252 may render a display of a simulated robotic unit 231, as a digital representation of an actual robotic unit 231, with identical spatial dimensions and motion characteristics related to skills and tasks assigned to the robotic unit and executed by application programs of the skill engine 110. The rendering of the simulation by the virtual modules 252 may be displayed to the user in the MR device 115. Virtual control data, such as sensor simulations, are fed to the skill engine 110 via data input 255. Visual sensor data from sensor 212 may provide visual information related to activity of real versions of robotic unit 231 and objects 222, 214. Simulation data provided by virtual modules 252 may be generated using tools such as Siemens LMS Virtual Lab, or the like.
US 2019/0384870 to Shiraishi
The digital twin system 199 includes code and routines that are operable to receive the modified vehicle model data 177 for a particular vehicle 123 as an input, as well as simulation data 155 that describes one or more virtual roadway environments (e.g., a road surface and other features of the road surface) as well as one or more static and dynamic objects included in the virtual roadway environments (e.g., traffic signs, traffic lights, pedestrians, pot holes, animals, other vehicles, etc.) and then perform hundreds or thousands of simulations
US 2019/0163215 to Cheng
the digital twin environment 925 can be divided into multiple virtual spaces 940-944. Each virtual space 940-944 can model a different digital twin instance and/or component of the digital twin 920 and/or each virtual space 940-944 can be used to perform a different analysis, simulation, etc., of the same digital twin 920. Using the multiple virtual spaces 940-944, the digital twin 920 can be tested inexpensively and efficiently in a plurality of ways while preserving building HVAC integrity. An operator, technician, HVAC control 110-114, etc., can then understand how the facility 102-106 may react to a variety of settings/configurations in a variety of scenarios, for example.
Any inquiry concerning this communication should be directed to examiner Tuan Dao, whose telephone/fax numbers are (571) 270 3387 and (571) 270 4387, respectively. The examiner can normally be reached on every Monday-Thursday, and the second Friday of the bi-week from 7:30AM to 5:00PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Pierre Vital, can be reached at (571) 272 4215.
The fax phone number for the organization where this application or proceeding is assigned is (571) 273 8300.
Any inquiry of a general nature of relating to the status of this application or proceeding should be directed to the TC 2100 Group receptionist whose telephone number is (571) 272 2100.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) Form at https://www.uspto.gov/patents/uspto-automated- interview-request-air-form.
/TUAN C DAO/ Primary Examiner, Art Unit 2198
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