DETAILED ACTION
Claims 1-20 have been examined.
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 .
Claim Rejections - 35 U.S.C. § 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.
The invention, as taught in Claims 1-20, is directed to “mental steps” and “mathematical steps” without significantly more.
The claims recite:
• training dataset (i.e., in the broadest reasonable interpretation, mathematical data)
• “generating, based on a training dataset, a data-driven model configured to output first model-predicted data associated with at least one process of an industrial plant”/“a data-driven model” dataset (i.e., in the broadest reasonable interpretation, mathematical steps) Applicant’s Specification, paragraph [0036] recites the following:
[0036] The term "data-driven model" may refer to a data entity that describes a model that is generated based on empirical data. In some example, the empirical data may be obtained from historical data, simulations, experiments, a combination thereof, and/or the like.
***
In some embodiments, the data-driven model includes a regression model, such as a linear regression model, a partial least square regression model, a support vector regression model, and/or the like. In some examples, the data-driven model may include one or more regression models that are previously trained, using one or more supervised and/or unsupervised machine learning techniques, to generate model-predicted data for one or more target process variables.
Note that it may be purely mathematical models, such as “linear regression model, a partial least square regression model,…, and/or the like”, as defined in the Specification.
• first model-predicted data associated with at least one process of an industrial plant (i.e., in the broadest reasonable interpretation, mathematical data)
• predicted value for each of one or more target process variables associated with the at least one process (i.e., in the broadest reasonable interpretation, mathematical data)
• integrating the data-driven model within a process simulation model (i.e., as defined in the Specification and in its broadest reasonable interpretation, mental steps, since it may be a “flowsheet”.) Specifically, Applicant’s Specification, paragraph [0034] recites in relevant part:
[0034] The term "process simulation model" may refer to a model-based representation of one or more processes of an industrial plant.
***
In one or more embodiments, a process simulation model embodies a flowsheet (i.e., mental steps) that describes the process flow through an industrial plant. Non-limiting examples of a process simulation model include first principles model, data-driven models, and hybrid simulation models.
• process simulation model (i.e., as defined in the Specification and in its broadest reasonable interpretation, mental steps, since it may be a “flowsheet”.) Specifically, Applicant’s Specification, paragraph [0034] recites in relevant part:
[0034] The term "process simulation model" may refer to a model-based representation of one or more processes of an industrial plant.
***
In one or more embodiments, a process simulation model embodies a flowsheet (i.e., mental steps) that describes the process flow through an industrial plant. Non-limiting examples of a process simulation model include first principles model, data-driven models, and hybrid simulation models.
• operating conditions (i.e., in the broadest reasonable interpretation, mathematical data)
• the first model-predicted data comprise a predicted value for each of one or more target process variables associated with the at least one process (i.e., in the broadest reasonable interpretation, mental steps)
• predict value for each of one or more other process variables relative to the one or more target process variables (i.e., in the broadest reasonable interpretation, mental steps)
• generating, …, the first model-predicted data (i.e., in the broadest reasonable interpretation, mental steps or mathematical steps)
• determining at least one operating parameter for a physical component involved in the at least one process of the industrial plant using the first model-predicted data (i.e., in the broadest reasonable interpretation, mental steps)
Claim 1
Step 1 inquiry: Does this claim fall within a statutory category?
The preamble of the claim recites “1. A computer-implemented method for data-driven model predictions within a process simulation system, the computer-implemented method comprising…” Therefore, it is a “computer-implemented method” (or “process”), which is a statutory category of invention. Therefore, the answer to the inquiry is: “YES.”
Step 2A (Prong One) inquiry:
Are there limitations in Claim 1 that recite abstract ideas?
YES. The following limitations in Claim 1 recite abstract ideas that fall within at least one of the groupings of abstract ideas enumerated in the 2019 PEG. Specifically, they are “mental steps” and “mathematical steps”:
• training dataset (i.e., in the broadest reasonable interpretation, mathematical data)
• “generating, based on a training dataset, a data-driven model configured to output first model-predicted data associated with at least one process of an industrial plant”/“a data-driven model” dataset (i.e., in the broadest reasonable interpretation, mathematical steps) Applicant’s Specification, paragraph [0036] recites the following:
[0036] The term "data-driven model" may refer to a data entity that describes a model that is generated based on empirical data. In some example, the empirical data may be obtained from historical data, simulations, experiments, a combination thereof, and/or the like.
***
In some embodiments, the data-driven model includes a regression model, such as a linear regression model, a partial least square regression model, a support vector regression model, and/or the like. In some examples, the data-driven model may include one or more regression models that are previously trained, using one or more supervised and/or unsupervised machine learning techniques, to generate model-predicted data for one or more target process variables.
Note that it may be purely mathematical models, such as “linear regression model, a partial least square regression model,…, and/or the like”, as defined in the Specification.
• first model-predicted data associated with at least one process of an industrial plant (i.e., in the broadest reasonable interpretation, mathematical data)
• predicted value for each of one or more target process variables associated with the at least one process (i.e., in the broadest reasonable interpretation, mathematical data)
• integrating the data-driven model within a process simulation model (i.e., as defined in the Specification and in its broadest reasonable interpretation, mental steps, since it may be a “flowsheet”.) Specifically, Applicant’s Specification, paragraph [0034] recites in relevant part:
[0034] The term "process simulation model" may refer to a model-based representation of one or more processes of an industrial plant.
***
In one or more embodiments, a process simulation model embodies a flowsheet (i.e., mental steps) that describes the process flow through an industrial plant. Non-limiting examples of a process simulation model include first principles model, data-driven models, and hybrid simulation models.
• process simulation model (i.e., as defined in the Specification and in its broadest reasonable interpretation, mental steps, since it may be a “flowsheet”.) Specifically, Applicant’s Specification, paragraph [0034] recites in relevant part:
[0034] The term "process simulation model" may refer to a model-based representation of one or more processes of an industrial plant.
***
In one or more embodiments, a process simulation model embodies a flowsheet (i.e., mental steps) that describes the process flow through an industrial plant. Non-limiting examples of a process simulation model include first principles model, data-driven models, and hybrid simulation models.
• operating conditions (i.e., in the broadest reasonable interpretation, mathematical data)
• the first model-predicted data comprise a predicted value for each of one or more target process variables associated with the at least one process (i.e., in the broadest reasonable interpretation, mental steps)
• predict value for each of one or more other process variables relative to the one or more target process variables (i.e., in the broadest reasonable interpretation, mental steps)
• generating, …, the first model-predicted data (i.e., in the broadest reasonable interpretation, mental steps or mathematical steps)
• determining at least one operating parameter for a physical component involved in the at least one process of the industrial plant using the first model-predicted data (i.e., in the broadest reasonable interpretation, mental steps)
Step 2A (Prong Two) inquiry:
Are there additional elements or a combination of elements in the claim that apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that it is more than a drafting effort designed to monopolize the exception?
Applicant’s claims contain the following “additional elements”:
(1) An “execution of the at least one process”
(2) A “deploying the process simulation model”
(3) A “generating, based on a training dataset, a data-driven model”
(4) integrating the data-driven model within a process simulation model
(5) the process simulation model is configured to simulate an execution of the at least one process at one or more operating conditions of a plurality of operating conditions
(6) deploying the process simulation model for use
(7) receiving, from one or more sensors, input data associated with the at least one process of the industrial plant
(8) using the data-driven model
(9) industrial plant
(10) applying the at least one operating parameter to automatically reconfigure the physical component of the industrial plant
(1) A “execution of the at least one process” is a broad term which is described at a high level and includes general purpose computers. M.P.E.P. § 2106.04(d)(I) recites:
The courts have also identified limitations that did not integrate a judicial exception into a practical application:
• Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f);
• Adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g); and
• Generally linking the use of a judicial exception to a particular technological environment or field of use, as discussed in MPEP § 2106.05(h).
This “execution of the at least one process” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(2) A “deploying the process simulation model” is a broad term which is described at a high level. M.P.E.P. § 2106.04(d)(I) recites:
The courts have also identified limitations that did not integrate a judicial exception into a practical application:
• Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f);
• Adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g); and
• Generally linking the use of a judicial exception to a particular technological environment or field of use, as discussed in MPEP § 2106.05(h).
This “deploying the process simulation model” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(3) A “generating, based on a training dataset, a data-driven model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “generating, based on a training dataset, a data-driven model” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(4) A “integrating the data-driven model within a process simulation model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “integrating the data-driven model within a process simulation model” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(5) A “process simulation model is configured to simulate an execution of the at least one process at one or more operating conditions of a plurality of operating conditions” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “the process simulation model is configured to simulate an execution of the at least one process at one or more operating conditions of a plurality of operating conditions” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(6) A “deploying the process simulation model for use” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “deploying the process simulation model for use” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(7) A “receiving, from one or more sensors, input data associated with the at least one process of the industrial plant” is a broad term which is described at a high level. M.P.E.P. § 2106.05(g) recites:
2106.05(g) Insignificant Extra-Solution Activity [R-10.2019]
Another consideration when determining whether a claim integrates the judicial exception into a practical application in Step 2A Prong Two or recites significantly more in Step 2B is whether the additional elements add more than insignificant extra-solution activity to the judicial exception. The term “extra-solution activity” can be understood as activities incidental to the primary process or product that are merely a nominal or tangential addition to the claim. Extra-solution activity includes both pre-solution and post-solution activity.
This “receiving, from one or more sensors, input data associated with the at least one process of the industrial plant” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(8) A “using the data-driven model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “using the data-driven model” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(9) A “industrial plant” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “industrial plant” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(10) A “applying the at least one operating parameter to automatically reconfigure the physical component of the industrial plant” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “applying the at least one operating parameter to automatically reconfigure the physical component of the industrial plant” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
The answer to the inquiry is “NO”, no additional elements integrate the claimed abstract idea into a practical application.
Step 2B inquiry:
Does the claim provide an inventive concept, i.e., does the claim recite additional element(s) or a combination of elements that amount to significantly more than the judicial exception in the claim?
Applicant’s claims contain the following “additional elements”:
(1) An “execution of the at least one process”
(2) A “deploying the process simulation model”
(3) A “generating, based on a training dataset, a data-driven model”
(4) integrating the data-driven model within a process simulation model
(5) the process simulation model is configured to simulate an execution of the at least one process at one or more operating conditions of a plurality of operating conditions
(6) deploying the process simulation model for use
(7) receiving, from one or more sensors, input data associated with the at least one process of the industrial plant
(8) using the data-driven model
(9) industrial plant
(10) applying the at least one operating parameter to automatically reconfigure the physical component of the industrial plant
(1) A “execution of the at least one process” is a broad term which is described at a high level and includes general purpose computers. M.P.E.P. § 2106.05 (I)(A)(i-ii) recites:
Limitations that the courts have found not to be enough to qualify as “significantly more” when recited in a claim with a judicial exception include:
i. Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 573 U.S. at 225-26, 110 USPQ2d at 1984 (see MPEP § 2106.05(f));
ii. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d));
Further, M.P.E.P. § 2016.05(f) recites:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words “apply it” (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer. As explained by the Supreme Court, in order to make a claim directed to a judicial exception patent-eligible, the additional element or combination of elements must do “‘more than simply stat[e] the [judicial exception] while adding the words ‘apply it’”. Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984 (warning against a § 101 analysis that turns on “the draftsman’s art”).
Further, M.P.E.P. § 2106.05(f)(2) recites:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process.
Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
Further, Applicant's execution method is well-understood, routine and conventional. Applicant's Specification, paragraph [0110] recites:
[0110] The processes and logic flows described herein can be performed by one or more programmable processors executing one or more computer programs to perform actions by operating on input information/data and generating output. Processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor will receive instructions and information/data from a read-only memory or a random access memory or both. The essential elements of a computer are a processor for performing actions in accordance with instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive information/data from or transfer information/data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto-optical disks, or optical disks. However, a computer need not have such devices. Devices suitable for storing computer program instructions and information/data include all forms of non-volatile memory, media and memory devices, including by way of example semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices; magnetic disks, e.g., internal hard disks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(2) A “deploying the process simulation model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (I)(A)(i-ii) recites:
Limitations that the courts have found not to be enough to qualify as “significantly more” when recited in a claim with a judicial exception include:
i. Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 573 U.S. at 225-26, 110 USPQ2d at 1984 (see MPEP § 2106.05(f));
ii. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d));
Further, M.P.E.P. § 2016.05(f) recites:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words “apply it” (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer. As explained by the Supreme Court, in order to make a claim directed to a judicial exception patent-eligible, the additional element or combination of elements must do “‘more than simply stat[e] the [judicial exception] while adding the words ‘apply it’”. Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984 (warning against a § 101 analysis that turns on “the draftsman’s art”).
Further, M.P.E.P. § 2106.05(f)(2) recites:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process.
Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
Applicant's “deploying” is well-understood, routine, and conventional because that deploying operation involves generic receiving, generating/calculating, and applying data. Applicant’s Specification, paragraph [0103] recites:
[0103] At block 606, the apparatus 200 includes first principles-driven prediction circuitry 210,data-driven prediction circuitry 212,optional control circuitry 214,communications circuitry 208,input/output circuitry 206,processor 202, and/or the like, or a combination thereof, that deploys the process simulation model for use. In some embodiments, deploying the process simulation model for use includes receiving input data, generating, using the data- driven model, the first model-predicted data, and applying the model-predicted data in one or more of engineering studies or offline optimization operation. In some embodiments, the input data includes process data associated with the at least one process. In some embodiments, the first model-predicted data is implemented as a constraint in one or more of (i) engineering studies or (ii) optimization operation.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(3) A “generating, based on a training dataset, a data-driven model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(4) A “integrating the data-driven model within a process simulation model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(5) A “the process simulation model is configured to simulate an execution of the at least one process at one or more operating conditions of a plurality of operating conditions” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(6) A “deploying the process simulation model for use” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(7) A “receiving, from one or more sensors, input data associated with the at least one process of the industrial plant” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); …
Further, M.P.E.P. § 2106.05(d)(I)(2) recites in part:
2. A factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity. Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (Fed. Cir. 2018). However, this does not mean that a prior art search is necessary to resolve this inquiry. Instead, examiners should rely on what the courts have recognized, or those in the art would recognize, as elements that are well-understood, routine, conventional activity in the relevant field when making the required determination. For example, in many instances, the specification of the application may indicate that additional elements are well-known or conventional. See, e.g., Intellectual Ventures v. Symantec, 838 F.3d at 1317; 120 USPQ2d at 1359 ("The written description is particularly useful in determining what is well-known or conventional"); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1418 (Fed. Cir. 2015) (relying on specification’s description of additional elements as "well-known", "common" and "conventional"); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 614, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (Specification described additional elements as "either performing basic computer functions such as sending and receiving data, or performing functions ‘known’ in the art.").
Further the claimed receiving of sensor data is generic, well-understood, routine, and conventional. Paragraph [0059] of Applicant’s Specification recites the following:
[0059] In some embodiments, one or more inputs for the first principles model 110 may be fixed input(s), while one or more inputs for the first principles model 110 may be variable input(s).
***
Additionally or alternatively, one or more inputs for the first principles model 110 may include process data (e.g., plant data) received from the industrial plant system 104. In some embodiments, process data includes values (e.g., measurements) for one or more selected process variables. Non-limiting examples of process variables may include temperature, feed flow, pressure, and/or the like. In some examples, one or more equipment and/or processes associated with the industrial plant system 104 may include sensor device(s) for measuring and/or providing a portion of the input data (e.g., feed flow, temperature, pressure, and/or the like) for the first principles model 110. In some examples, a portion of the input data is measured in near real-time and provided to the first principles model in near real-time. In some examples, a portion of the input data may
include values for process variables that are periodically measured during plant operating using laboratory techniques (e.g., measured in a laboratory).
Merely using the conventional computer to receive data is well known, understood, and conventional. Thus, it adds nothing significantly more to the judicial exception.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(8) A “using the data-driven model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(9) A “industrial plant” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Further, the term “an industrial plant” is generic, well-understood, routine, and conventional. Specifically, paragraph [0025] of Applicant’s Specification recites:
[0025] Various embodiments of the present disclosure address technical challenges related to process simulation. Process simulation models may be configured for modelling and/or simulating process(es) associated with, for example, an industrial plant (e.g., gas processing plants, oil refineries, and/or the like).
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(10) A “applying the at least one operating parameter to automatically reconfigure the physical component of the industrial plant” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
Therefore, the answer to the inquiry is “NO”, no additional elements provide an inventive concept that is significantly more than the claimed abstract ideas the claimed abstract idea into a practical application.
Claim 1 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 2
Claim 2 recites:
2. The computer-implemented method of claim 1, wherein the process simulation model comprise the data-driven model and a first principles model.
Applicant’s Claim 2 merely teaches pure mathematical data entities. Applicant's Specification, paragraph [0036] recites:
[0036] The term "data-driven model" may refer to a data entity that describes a model that is generated based on empirical data. In some example, the empirical data may be obtained from historical data, simulations, experiments, a combination thereof, and/or the like. A data-driven model may be configured to extract and/or determine correlations and/or patterns in input data to generate corresponding output. In some embodiments, a data-driven model may include a machine learning model. An example of a data-driven model is machine learning soft sensor model. In some embodiments a data-driven model, such as a machine learning soft sensor model is configured, trained, and/or the like to generate model-predicted data (e.g., data-driven model-predicted data) that includes predicted values for one or more target process variables. In some examples, the data-driven model may include one or more of any type of machine learning model including one or more supervised, unsupervised, semi-supervised, reinforcement learning models, and/or the like. In some examples, the data-driven model may include multiple models configured to perform one or more different stages of a prediction process. In some embodiments, the data-driven model includes a neural network, such as a recurrent neural network, deep neural network, and/or the like. In some examples, the data-driven model may include one or more neural networks that are previously trained, using one or more supervised and/or unsupervised machine learning techniques, to generate model-predicted data for one or more target process variables. In some embodiments, the data-driven model includes a regression model, such as a linear regression model, a partial least square regression model, a support vector regression model, and/or the like. In some examples, the data-driven model may include one or more regression models that are previously trained, using one or more supervised and/or unsupervised machine learning techniques, to generate model-predicted data for one or more target process variables.
It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 2 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 3
Claim 3 recites:
3. The computer-implemented method of claim 2, wherein the first principles model is configured to generate (i.e., calculate)second model-predicted data, wherein the second model-predicted data comprise a predicted value for each of one or more other process variables relative to the one or more target process variables.
Applicant’s Claim 3 merely teaches, in the broadest reasonable interpretation, limitations to pure mathematical calculation. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 3 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 4
Claim 4 recites:
4. The computer-implemented method of claim 1, wherein deploying the process simulation model for use comprises:
receiving input data, wherein the input data comprise process data associated with the at least one process;
generating, using the data-driven model, the first model-predicted data; and
applying the model-predicted data in one or more of (i) engineering studies or (ii) offline optimization operation.
Applicant’s Claim 4 merely teaches, in its broadest reasonable interpretation, limitations to generic mathematical processes of receiving unspecified mathematical data, processing that data in a completely unspecified way, and applying that data in one of two fields of use. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 4 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 5
Claim 5 recites:
5. The computer-implemented method of claim 1, wherein the first model-predicted data is implemented as a constraint in one or more of (i) engineering studies or (ii) optimization operation.
Applicant’s Claim 5 merely teaches, in its broadest reasonable interpretation, limitations to generic mathematical data applied to one of two fields of use. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 5 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 6
Claim 6 recites:
6. The computer-implemented method of claim 1, wherein the data-driven model is configured to model the at least one process.
Applicant’s Claim 6 merely teaches, in its broadest reasonable interpretation, limitations to generic mathematical data applied to one unspecified field of use. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 6 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 7
Claim 7 recites:
7. The computer-implemented method of claim 1, wherein the data-driven model comprises a neural network model.
Applicant’s Claim 7 merely teaches the mathematical data parameters that describe a generic neural network. Applicant's Specification, paragraph [0036] recites:
[0036] The term "data-driven model" may refer to a data entity that describes a model that is generated based on empirical data. In some example, the empirical data may be obtained from historical data, simulations, experiments, a combination thereof, and/or the like. A data-driven model may be configured to extract and/or determine correlations and/or patterns in input data to generate corresponding output. In some embodiments, a data-driven model may include a machine learning model. An example of a data-driven model is machine learning soft sensor model. In some embodiments a data-driven model, such as a machine learning soft sensor model is configured, trained, and/or the like to generate model-predicted data (e.g., data-driven model-predicted data) that includes predicted values for one or more target process variables. In some examples, the data-driven model may include one or more of any type of machine learning model including one or more supervised, unsupervised, semi-supervised, reinforcement learning models, and/or the like. In some examples, the data-driven model may include multiple models configured to perform one or more different stages of a prediction process. In some embodiments, the data-driven model includes a neural network, such as a recurrent neural network, deep neural network, and/or the like. In some examples, the data-driven model may include one or more neural networks that are previously trained, using one or more supervised and/or unsupervised machine learning techniques, to generate model-predicted data for one or more target process variables. In some embodiments, the data-driven model includes a regression model, such as a linear regression model, a partial least square regression model, a support vector regression model, and/or the like. In some examples, the data-driven model may include one or more regression models that are previously trained, using one or more supervised and/or unsupervised machine learning techniques, to generate model-predicted data for one or more target process variables.
It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 7 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 8
Claim 8 recites:
8. The computer-implemented method of claim 1, wherein the data-driven model comprises a regression model.
Applicant’s Claim 8 merely teaches the mathematical data parameters that describe a generic, mathematical regression/prediction model. Applicant's Specification, paragraph [0036] recites:
[0036] The term "data-driven model" may refer to a data entity that describes a model that is generated based on empirical data. In some example, the empirical data may be obtained from historical data, simulations, experiments, a combination thereof, and/or the like. A data-driven model may be configured to extract and/or determine correlations and/or patterns in input data to generate corresponding output. In some embodiments, a data-driven model may include a machine learning model. An example of a data-driven model is machine learning soft sensor model. In some embodiments a data-driven model, such as a machine learning soft sensor model is configured, trained, and/or the like to generate model-predicted data (e.g., data-driven model-predicted data) that includes predicted values for one or more target process variables. In some examples, the data-driven model may include one or more of any type of machine learning model including one or more supervised, unsupervised, semi-supervised, reinforcement learning models, and/or the like. In some examples, the data-driven model may include multiple models configured to perform one or more different stages of a prediction process. In some embodiments, the data-driven model includes a neural network, such as a recurrent neural network, deep neural network, and/or the like. In some examples, the data-driven model may include one or more neural networks that are previously trained, using one or more supervised and/or unsupervised machine learning techniques, to generate model-predicted data for one or more target process variables. In some embodiments, the data-driven model includes a regression model, such as a linear regression model, a partial least square regression model, a support vector regression model, and/or the like. In some examples, the data-driven model may include one or more regression models that are previously trained, using one or more supervised and/or unsupervised machine learning techniques, to generate model-predicted data for one or more target process variables.
It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 8 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 9
Claim 9 recites:
9. The computer-implemented method of claim 1, wherein the data-driven model is previously trained using one or more supervised training techniques.
Applicant’s Claim 9 merely teaches the mathematical data parameters that describe a generic, mathematical supervised learning model. Applicant's Specification, paragraph [0036] recites:
[0036] The term "data-driven model" may refer to a data entity that describes a model that is generated based on empirical data. In some example, the empirical data may be obtained from historical data, simulations, experiments, a combination thereof, and/or the like. A data-driven model may be configured to extract and/or determine correlations and/or patterns in input data to generate corresponding output. In some embodiments, a data-driven model may include a machine learning model. An example of a data-driven model is machine learning soft sensor model. In some embodiments a data-driven model, such as a machine learning soft sensor model is configured, trained, and/or the like to generate model-predicted data (e.g., data-driven model-predicted data) that includes predicted values for one or more target process variables. In some examples, the data-driven model may include one or more of any type of machine learning model including one or more supervised, unsupervised, semi-supervised, reinforcement learning models, and/or the like. In some examples, the data-driven model may include multiple models configured to perform one or more different stages of a prediction process. In some embodiments, the data-driven model includes a neural network, such as a recurrent neural network, deep neural network, and/or the like. In some examples, the data-driven model may include one or more neural networks that are previously trained, using one or more supervised and/or unsupervised machine learning techniques, to generate model-predicted data for one or more target process variables. In some embodiments, the data-driven model includes a regression model, such as a linear regression model, a partial least square regression model, a support vector regression model, and/or the like. In some examples, the data-driven model may include one or more regression models that are previously trained, using one or more supervised and/or unsupervised machine learning techniques, to generate model-predicted data for one or more target process variables.
It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 9 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 10
Claim 10 recites:
10. The computer-implemented method of claim 2, wherein the data-driven model is trained using the training dataset, wherein the training dataset comprises a plurality of sets of historical process data and corresponding ground truth data for one or more target process variables.
Applicant’s Claim 10 merely teaches the mathematical data parameters that describe a generic, mathematical learning model. Applicant's Specification, paragraph [0036] recites:
[0036] The term "data-driven model" may refer to a data entity that describes a model that is generated based on empirical data. In some example, the empirical data may be obtained from historical data, simulations, experiments, a combination thereof, and/or the like. A data-driven model may be configured to extract and/or determine correlations and/or patterns in input data to generate corresponding output. In some embodiments, a data-driven model may include a machine learning model. An example of a data-driven model is machine learning soft sensor model. In some embodiments a data-driven model, such as a machine learning soft sensor model is configured, trained, and/or the like to generate model-predicted data (e.g., data-driven model-predicted data) that includes predicted values for one or more target process variables. In some examples, the data-driven model may include one or more of any type of machine learning model including one or more supervised, unsupervised, semi-supervised, reinforcement learning models, and/or the like. In some examples, the data-driven model may include multiple models configured to perform one or more different stages of a prediction process. In some embodiments, the data-driven model includes a neural network, such as a recurrent neural network, deep neural network, and/or the like. In some examples, the data-driven model may include one or more neural networks that are previously trained, using one or more supervised and/or unsupervised machine learning techniques, to generate model-predicted data for one or more target process variables. In some embodiments, the data-driven model includes a regression model, such as a linear regression model, a partial least square regression model, a support vector regression model, and/or the like. In some examples, the data-driven model may include one or more regression models that are previously trained, using one or more supervised and/or unsupervised machine learning techniques, to generate model-predicted data for one or more target process variables.
It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 10 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 11
Claim 11 recites:
11. The computer-implemented method of claim 2, wherein the historical process data in each set of historical process data and corresponding ground truth data comprises one or more of (i) historical predicted values for the one or more target process variables or (ii) historical values for a set of measured process variables.
Applicant’s Claim 11 merely teaches mathematical training values. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 11 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 12
Step 1 inquiry: Does this claim fall within a statutory category?
The preamble of the claim recites “12. An apparatus comprising…” Therefore, it is an “apparatus,” which is a statutory category of invention. Therefore, the answer to the inquiry is: “YES.”
Step 2A (Prong One) inquiry:
Are there limitations in Claim 12 that recite abstract ideas?
YES. The following limitations in Claim 12 recite abstract ideas that fall within at least one of the groupings of abstract ideas enumerated in the 2019 PEG. Specifically, they are “mental steps” and “mathematical steps”:
• training dataset (i.e., in the broadest reasonable interpretation, mathematical data)
• “generating, based on a training dataset, a data-driven model configured to output first model-predicted data associated with at least one process of an industrial plant”/“a data-driven model” dataset (i.e., in the broadest reasonable interpretation, mathematical steps) Applicant’s Specification, paragraph [0036] recites the following:
[0036] The term "data-driven model" may refer to a data entity that describes a model that is generated based on empirical data. In some example, the empirical data may be obtained from historical data, simulations, experiments, a combination thereof, and/or the like.
***
In some embodiments, the data-driven model includes a regression model, such as a linear regression model, a partial least square regression model, a support vector regression model, and/or the like. In some examples, the data-driven model may include one or more regression models that are previously trained, using one or more supervised and/or unsupervised machine learning techniques, to generate model-predicted data for one or more target process variables.
Note that it may be purely mathematical models, such as “linear regression model, a partial least square regression model,…, and/or the like”, as defined in the Specification.
• first model-predicted data associated with at least one process of an industrial plant (i.e., in the broadest reasonable interpretation, mathematical data)
• predicted value for each of one or more target process variables associated with the at least one process (i.e., in the broadest reasonable interpretation, mathematical data)
• integrating the data-driven model within a process simulation model (i.e., as defined in the Specification and in its broadest reasonable interpretation, mental steps, since it may be a “flowsheet”.) Specifically, Applicant’s Specification, paragraph [0034] recites in relevant part:
[0034] The term "process simulation model" may refer to a model-based representation of one or more processes of an industrial plant.
***
In one or more embodiments, a process simulation model embodies a flowsheet (i.e., mental steps) that describes the process flow through an industrial plant. Non-limiting examples of a process simulation model include first principles model, data-driven models, and hybrid simulation models.
• process simulation model (i.e., as defined in the Specification and in its broadest reasonable interpretation, mental steps, since it may be a “flowsheet”.) Specifically, Applicant’s Specification, paragraph [0034] recites in relevant part:
[0034] The term "process simulation model" may refer to a model-based representation of one or more processes of an industrial plant.
***
In one or more embodiments, a process simulation model embodies a flowsheet (i.e., mental steps) that describes the process flow through an industrial plant. Non-limiting examples of a process simulation model include first principles model, data-driven models, and hybrid simulation models.
• operating conditions (i.e., in the broadest reasonable interpretation, mathematical data)
• the first model-predicted data comprise a predicted value for each of one or more target process variables associated with the at least one process (i.e., in the broadest reasonable interpretation, mental steps)
• predict value for each of one or more other process variables relative to the one or more target process variables (i.e., in the broadest reasonable interpretation, mental steps)
• generating, …, the first model-predicted data (i.e., in the broadest reasonable interpretation, mental steps or mathematical steps)
• determining at least one operating parameter for a physical component involved in the at least one process of the industrial plant using the first model-predicted data (i.e., in the broadest reasonable interpretation, mental steps)
Step 2A (Prong Two) inquiry:
Are there additional elements or a combination of elements in the claim that apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that it is more than a drafting effort designed to monopolize the exception?
Applicant’s claims contain the following “additional elements”:
(1) An “execution of the at least one process”
(2) A “deploy the process simulation model”
(3) A “generating, based on a training dataset, a data-driven model”
(4) integrating the data-driven model within a process simulation model
(5) the process simulation model is configured to simulate an execution of the at least one process at one or more operating conditions of a plurality of operating conditions
(6) deploying the process simulation model for use
(7) receiving, from one or more sensors, input data associated with the at least one process of the industrial plant
(8) using the data-driven model
(9) industrial plant
(10) applying the at least one operating parameter to automatically reconfigure the physical component of the industrial plant
(1) A “execution of the at least one process” is a broad term which is described at a high level and includes general purpose computers. M.P.E.P. § 2106.04(d)(I) recites:
The courts have also identified limitations that did not integrate a judicial exception into a practical application:
• Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f);
• Adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g); and
• Generally linking the use of a judicial exception to a particular technological environment or field of use, as discussed in MPEP § 2106.05(h).
This “execution of the at least one process” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(2) A “deploy the process simulation model” is a broad term which is described at a high level. M.P.E.P. § 2106.04(d)(I) recites:
The courts have also identified limitations that did not integrate a judicial exception into a practical application:
• Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f);
• Adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g); and
• Generally linking the use of a judicial exception to a particular technological environment or field of use, as discussed in MPEP § 2106.05(h).
This “deploy the process simulation model” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(3) A “generating, based on a training dataset, a data-driven model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “generating, based on a training dataset, a data-driven model” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(4) A “integrating the data-driven model within a process simulation model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “integrating the data-driven model within a process simulation model” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(5) A “process simulation model is configured to simulate an execution of the at least one process at one or more operating conditions of a plurality of operating conditions” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “the process simulation model is configured to simulate an execution of the at least one process at one or more operating conditions of a plurality of operating conditions” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(6) A “deploying the process simulation model for use” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “deploying the process simulation model for use” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(7) A “receiving, from one or more sensors, input data associated with the at least one process of the industrial plant” is a broad term which is described at a high level. M.P.E.P. § 2106.05(g) recites:
2106.05(g) Insignificant Extra-Solution Activity [R-10.2019]
Another consideration when determining whether a claim integrates the judicial exception into a practical application in Step 2A Prong Two or recites significantly more in Step 2B is whether the additional elements add more than insignificant extra-solution activity to the judicial exception. The term “extra-solution activity” can be understood as activities incidental to the primary process or product that are merely a nominal or tangential addition to the claim. Extra-solution activity includes both pre-solution and post-solution activity.
This “receiving, from one or more sensors, input data associated with the at least one process of the industrial plant” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(8) A “using the data-driven model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “using the data-driven model” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(9) A “industrial plant” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “industrial plant” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(10) A “applying the at least one operating parameter to automatically reconfigure the physical component of the industrial plant” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “applying the at least one operating parameter to automatically reconfigure the physical component of the industrial plant” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
The answer to the inquiry is “NO”, no additional elements integrate the claimed abstract idea into a practical application.
Step 2B inquiry:
Does the claim provide an inventive concept, i.e., does the claim recite additional element(s) or a combination of elements that amount to significantly more than the judicial exception in the claim?
Applicant’s claims contain the following “additional elements”:
(1) An “execution of the at least one process”
(2) A “deploy the process simulation model”
(3) A “generating, based on a training dataset, a data-driven model”
(4) integrating the data-driven model within a process simulation model
(5) the process simulation model is configured to simulate an execution of the at least one process at one or more operating conditions of a plurality of operating conditions
(6) deploying the process simulation model for use
(7) receiving, from one or more sensors, input data associated with the at least one process of the industrial plant
(8) using the data-driven model
(9) industrial plant
(10) applying the at least one operating parameter to automatically reconfigure the physical component of the industrial plant
(1) A “execution of the at least one process” is a broad term which is described at a high level and includes general purpose computers. M.P.E.P. § 2106.05 (I)(A)(i-ii) recites:
Limitations that the courts have found not to be enough to qualify as “significantly more” when recited in a claim with a judicial exception include:
i. Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 573 U.S. at 225-26, 110 USPQ2d at 1984 (see MPEP § 2106.05(f));
ii. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d));
Further, M.P.E.P. § 2016.05(f) recites:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words “apply it” (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer. As explained by the Supreme Court, in order to make a claim directed to a judicial exception patent-eligible, the additional element or combination of elements must do “‘more than simply stat[e] the [judicial exception] while adding the words ‘apply it’”. Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984 (warning against a § 101 analysis that turns on “the draftsman’s art”).
Further, M.P.E.P. § 2106.05(f)(2) recites:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process.
Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
Further, Applicant's execution method is well-understood, routine and conventional. Applicant's Specification, paragraph [0110] recites:
[0110] The processes and logic flows described herein can be performed by one or more programmable processors executing one or more computer programs to perform actions by operating on input information/data and generating output. Processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor will receive instructions and information/data from a read-only memory or a random access memory or both. The essential elements of a computer are a processor for performing actions in accordance with instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive information/data from or transfer information/data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto-optical disks, or optical disks. However, a computer need not have such devices. Devices suitable for storing computer program instructions and information/data include all forms of non-volatile memory, media and memory devices, including by way of example semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices; magnetic disks, e.g., internal hard disks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(2) A “deploy the process simulation model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (I)(A)(i-ii) recites:
Limitations that the courts have found not to be enough to qualify as “significantly more” when recited in a claim with a judicial exception include:
i. Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 573 U.S. at 225-26, 110 USPQ2d at 1984 (see MPEP § 2106.05(f));
ii. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d));
Further, M.P.E.P. § 2016.05(f) recites:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words “apply it” (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer. As explained by the Supreme Court, in order to make a claim directed to a judicial exception patent-eligible, the additional element or combination of elements must do “‘more than simply stat[e] the [judicial exception] while adding the words ‘apply it’”. Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984 (warning against a § 101 analysis that turns on “the draftsman’s art”).
Further, M.P.E.P. § 2106.05(f)(2) recites:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process.
Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
Applicant's “deploy” is well-understood, routine, and conventional because that deploying operation involves generic receiving, generating/calculating, and applying data. Applicant’s Specification, paragraph [0103] recites:
[0103] At block 606, the apparatus 200 includes first principles-driven prediction circuitry 210,data-driven prediction circuitry 212,optional control circuitry 214,communications circuitry 208,input/output circuitry 206,processor 202, and/or the like, or a combination thereof, that deploys the process simulation model for use. In some embodiments, deploying the process simulation model for use includes receiving input data, generating, using the data- driven model, the first model-predicted data, and applying the model-predicted data in one or more of engineering studies or offline optimization operation. In some embodiments, the input data includes process data associated with the at least one process. In some embodiments, the first model-predicted data is implemented as a constraint in one or more of (i) engineering studies or (ii) optimization operation.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(3) A “generating, based on a training dataset, a data-driven model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(4) A “integrating the data-driven model within a process simulation model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(5) A “the process simulation model is configured to simulate an execution of the at least one process at one or more operating conditions of a plurality of operating conditions” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(6) A “deploying the process simulation model for use” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(7) A “receiving, from one or more sensors, input data associated with the at least one process of the industrial plant” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); …
Further, M.P.E.P. § 2106.05(d)(I)(2) recites in part:
2. A factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity. Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (Fed. Cir. 2018). However, this does not mean that a prior art search is necessary to resolve this inquiry. Instead, examiners should rely on what the courts have recognized, or those in the art would recognize, as elements that are well-understood, routine, conventional activity in the relevant field when making the required determination. For example, in many instances, the specification of the application may indicate that additional elements are well-known or conventional. See, e.g., Intellectual Ventures v. Symantec, 838 F.3d at 1317; 120 USPQ2d at 1359 ("The written description is particularly useful in determining what is well-known or conventional"); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1418 (Fed. Cir. 2015) (relying on specification’s description of additional elements as "well-known", "common" and "conventional"); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 614, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (Specification described additional elements as "either performing basic computer functions such as sending and receiving data, or performing functions ‘known’ in the art.").
Further the claimed receiving of sensor data is generic, well-understood, routine, and conventional. Paragraph [0059] of Applicant’s Specification recites the following:
[0059] In some embodiments, one or more inputs for the first principles model 110 may be fixed input(s), while one or more inputs for the first principles model 110 may be variable input(s).
***
Additionally or alternatively, one or more inputs for the first principles model 110 may include process data (e.g., plant data) received from the industrial plant system 104. In some embodiments, process data includes values (e.g., measurements) for one or more selected process variables. Non-limiting examples of process variables may include temperature, feed flow, pressure, and/or the like. In some examples, one or more equipment and/or processes associated with the industrial plant system 104 may include sensor device(s) for measuring and/or providing a portion of the input data (e.g., feed flow, temperature, pressure, and/or the like) for the first principles model 110. In some examples, a portion of the input data is measured in near real-time and provided to the first principles model in near real-time. In some examples, a portion of the input data may
include values for process variables that are periodically measured during plant operating using laboratory techniques (e.g., measured in a laboratory).
Merely using the conventional computer to receive data is well known, understood, and conventional. Thus, it adds nothing significantly more to the judicial exception.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(8) A “using the data-driven model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(9) A “industrial plant” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Further, the term “an industrial plant” is generic, well-understood, routine, and conventional. Specifically, paragraph [0025] of Applicant’s Specification recites:
[0025] Various embodiments of the present disclosure address technical challenges related to process simulation. Process simulation models may be configured for modelling and/or simulating process(es) associated with, for example, an industrial plant (e.g., gas processing plants, oil refineries, and/or the like).
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(10) A “applying the at least one operating parameter to automatically reconfigure the physical component of the industrial plant” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
Therefore, the answer to the inquiry is “NO”, no additional elements provide an inventive concept that is significantly more than the claimed abstract ideas the claimed abstract idea into a practical application.
Claim 12 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 13
Claim 13 recites:
13. The apparatus of claim 12, wherein the process simulation model comprise the data-driven model and a first principles model.
Applicant’s Claim 13 merely teaches pure mathematical data entities. Applicant's Specification, paragraph [0036] recites:
[0036] The term "data-driven model" may refer to a data entity that describes a model that is generated based on empirical data. In some example, the empirical data may be obtained from historical data, simulations, experiments, a combination thereof, and/or the like. A data-driven model may be configured to extract and/or determine correlations and/or patterns in input data to generate corresponding output. In some embodiments, a data-driven model may include a machine learning model. An example of a data-driven model is machine learning soft sensor model. In some embodiments a data-driven model, such as a machine learning soft sensor model is configured, trained, and/or the like to generate model-predicted data (e.g., data-driven model-predicted data) that includes predicted values for one or more target process variables. In some examples, the data-driven model may include one or more of any type of machine learning model including one or more supervised, unsupervised, semi-supervised, reinforcement learning models, and/or the like. In some examples, the data-driven model may include multiple models configured to perform one or more different stages of a prediction process. In some embodiments, the data-driven model includes a neural network, such as a recurrent neural network, deep neural network, and/or the like. In some examples, the data-driven model may include one or more neural networks that are previously trained, using one or more supervised and/or unsupervised machine learning techniques, to generate model-predicted data for one or more target process variables. In some embodiments, the data-driven model includes a regression model, such as a linear regression model, a partial least square regression model, a support vector regression model, and/or the like. In some examples, the data-driven model may include one or more regression models that are previously trained, using one or more supervised and/or unsupervised machine learning techniques, to generate model-predicted data for one or more target process variables.
It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 13 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 14
Claim 14 recites:
14. The apparatus of claim 13, wherein the first principles model is configured to generate second model-predicted data, wherein the second model-predicted data comprise a predicted value for each of one or more other process variables relative to the one or more target process variables.
Applicant’s Claim 14 merely teaches , in the broadest reasonable interpretation, limitations to pure mathematical calculation. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 14 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 15
Claim 15 recites:
15. The apparatus of claim 12, wherein deploying the process simulation model for use comprises:
receiving input data, wherein the input data comprise process data associated with the at least one process;
generating, using the data-driven model, the first model-predicted data; and
applying the model-predicted data in one or more of (i) engineering studies or (ii) offline optimization operation.
Applicant’s Claim 15 merely teaches , in its broadest reasonable interpretation, limitations to generic mathematical processes of receiving unspecified mathematical data, processing that data in a completely unspecified way, and applying that data in one of two fields of use. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 15 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 16
Claim 16 recites:
16. The apparatus of claim 12, wherein the first model-predicted data is implemented as a constraint in one or more of (i) engineering studies or (ii) optimization operation.
Applicant’s Claim 16 merely teaches , in its broadest reasonable interpretation, limitations to generic mathematical data applied to one of two fields of use. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 16 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 17
Claim 17 recites:
17. The apparatus of claim 12, wherein the data-driven model is configured to model the at least one process.
Applicant’s Claim 17 merely teaches, in its broadest reasonable interpretation, limitations to generic mathematical data applied to one unspecified field of use. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 17 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 18
Claim 18 recites:
18. The apparatus of claim 12, wherein the data-driven model comprises a neural network model.
Applicant’s Claim 18 merely teaches the mathematical data parameters that describe a generic neural network. Applicant's Specification, paragraph [0036] recites:
[0036] The term "data-driven model" may refer to a data entity that describes a model that is generated based on empirical data. In some example, the empirical data may be obtained from historical data, simulations, experiments, a combination thereof, and/or the like. A data-driven model may be configured to extract and/or determine correlations and/or patterns in input data to generate corresponding output. In some embodiments, a data-driven model may include a machine learning model. An example of a data-driven model is machine learning soft sensor model. In some embodiments a data-driven model, such as a machine learning soft sensor model is configured, trained, and/or the like to generate model-predicted data (e.g., data-driven model-predicted data) that includes predicted values for one or more target process variables. In some examples, the data-driven model may include one or more of any type of machine learning model including one or more supervised, unsupervised, semi-supervised, reinforcement learning models, and/or the like. In some examples, the data-driven model may include multiple models configured to perform one or more different stages of a prediction process. In some embodiments, the data-driven model includes a neural network, such as a recurrent neural network, deep neural network, and/or the like. In some examples, the data-driven model may include one or more neural networks that are previously trained, using one or more supervised and/or unsupervised machine learning techniques, to generate model-predicted data for one or more target process variables. In some embodiments, the data-driven model includes a regression model, such as a linear regression model, a partial least square regression model, a support vector regression model, and/or the like. In some examples, the data-driven model may include one or more regression models that are previously trained, using one or more supervised and/or unsupervised machine learning techniques, to generate model-predicted data for one or more target process variables.
It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 18 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 19
Claim 19 recites:
19. The apparatus of claim 12, wherein the data-driven model comprises a regression model.
Applicant’s Claim 19 merely teaches the mathematical data parameters that describe a generic, mathematical regression/prediction model. Applicant's Specification, paragraph [0036] recites:
[0036] The term "data-driven model" may refer to a data entity that describes a model that is generated based on empirical data. In some example, the empirical data may be obtained from historical data, simulations, experiments, a combination thereof, and/or the like. A data-driven model may be configured to extract and/or determine correlations and/or patterns in input data to generate corresponding output. In some embodiments, a data-driven model may include a machine learning model. An example of a data-driven model is machine learning soft sensor model. In some embodiments a data-driven model, such as a machine learning soft sensor model is configured, trained, and/or the like to generate model-predicted data (e.g., data-driven model-predicted data) that includes predicted values for one or more target process variables. In some examples, the data-driven model may include one or more of any type of machine learning model including one or more supervised, unsupervised, semi-supervised, reinforcement learning models, and/or the like. In some examples, the data-driven model may include multiple models configured to perform one or more different stages of a prediction process. In some embodiments, the data-driven model includes a neural network, such as a recurrent neural network, deep neural network, and/or the like. In some examples, the data-driven model may include one or more neural networks that are previously trained, using one or more supervised and/or unsupervised machine learning techniques, to generate model-predicted data for one or more target process variables. In some embodiments, the data-driven model includes a regression model, such as a linear regression model, a partial least square regression model, a support vector regression model, and/or the like. In some examples, the data-driven model may include one or more regression models that are previously trained, using one or more supervised and/or unsupervised machine learning techniques, to generate model-predicted data for one or more target process variables.
It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 19 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 20
Step 1 inquiry: Does this claim fall within a statutory category?
The preamble of the claim recites “20. A computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising an executable portion configured to…” Therefore, it is a “computer program product,” which is not, itself, limited to a “non-transitory computer-readable storage medium”. Therefore, the answer to the inquiry is: “NO.”
Step 2A (Prong One) inquiry:
Are there limitations in Claim 20 that recite abstract ideas?
YES. The following limitations in Claim 20 recite abstract ideas that fall within at least one of the groupings of abstract ideas enumerated in the 2019 PEG. Specifically, they are “mental steps” and “mathematical steps”:
• training dataset (i.e., in the broadest reasonable interpretation, mathematical data)
• “generating, based on a training dataset, a data-driven model configured to output first model-predicted data associated with at least one process of an industrial plant”/“a data-driven model” dataset (i.e., in the broadest reasonable interpretation, mathematical steps) Applicant’s Specification, paragraph [0036] recites the following:
[0036] The term "data-driven model" may refer to a data entity that describes a model that is generated based on empirical data. In some example, the empirical data may be obtained from historical data, simulations, experiments, a combination thereof, and/or the like.
***
In some embodiments, the data-driven model includes a regression model, such as a linear regression model, a partial least square regression model, a support vector regression model, and/or the like. In some examples, the data-driven model may include one or more regression models that are previously trained, using one or more supervised and/or unsupervised machine learning techniques, to generate model-predicted data for one or more target process variables.
Note that it may be purely mathematical models, such as “linear regression model, a partial least square regression model,…, and/or the like”, as defined in the Specification.
• first model-predicted data associated with at least one process of an industrial plant (i.e., in the broadest reasonable interpretation, mathematical data)
• predicted value for each of one or more target process variables associated with the at least one process (i.e., in the broadest reasonable interpretation, mathematical data)
• integrating the data-driven model within a process simulation model (i.e., as defined in the Specification and in its broadest reasonable interpretation, mental steps, since it may be a “flowsheet”.) Specifically, Applicant’s Specification, paragraph [0034] recites in relevant part:
[0034] The term "process simulation model" may refer to a model-based representation of one or more processes of an industrial plant.
***
In one or more embodiments, a process simulation model embodies a flowsheet (i.e., mental steps) that describes the process flow through an industrial plant. Non-limiting examples of a process simulation model include first principles model, data-driven models, and hybrid simulation models.
• process simulation model (i.e., as defined in the Specification and in its broadest reasonable interpretation, mental steps, since it may be a “flowsheet”.) Specifically, Applicant’s Specification, paragraph [0034] recites in relevant part:
[0034] The term "process simulation model" may refer to a model-based representation of one or more processes of an industrial plant.
***
In one or more embodiments, a process simulation model embodies a flowsheet (i.e., mental steps) that describes the process flow through an industrial plant. Non-limiting examples of a process simulation model include first principles model, data-driven models, and hybrid simulation models.
• operating conditions (i.e., in the broadest reasonable interpretation, mathematical data)
• the first model-predicted data comprise a predicted value for each of one or more target process variables associated with the at least one process (i.e., in the broadest reasonable interpretation, mental steps)
• predict value for each of one or more other process variables relative to the one or more target process variables (i.e., in the broadest reasonable interpretation, mental steps)
• generating, …, the first model-predicted data (i.e., in the broadest reasonable interpretation, mental steps or mathematical steps)
• determining at least one operating parameter for a physical component involved in the at least one process of the industrial plant using the first model-predicted data (i.e., in the broadest reasonable interpretation, mental steps)
Step 2A (Prong Two) inquiry:
Are there additional elements or a combination of elements in the claim that apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that it is more than a drafting effort designed to monopolize the exception?
Applicant’s claims contain the following “additional elements”:
(1) An “execution of the at least one process”
(2) A “deploy the process simulation model”
(3) A “generating, based on a training dataset, a data-driven model”
(4) integrating the data-driven model within a process simulation model
(5) the process simulation model is configured to simulate an execution of the at least one process at one or more operating conditions of a plurality of operating conditions
(6) deploying the process simulation model for use
(7) receiving, from one or more sensors, input data associated with the at least one process of the industrial plant
(8) using the data-driven model
(9) industrial plant
(10) applying the at least one operating parameter to automatically reconfigure the physical component of the industrial plant
(1) A “execution of the at least one process” is a broad term which is described at a high level and includes general purpose computers. M.P.E.P. § 2106.04(d)(I) recites:
The courts have also identified limitations that did not integrate a judicial exception into a practical application:
• Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f);
• Adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g); and
• Generally linking the use of a judicial exception to a particular technological environment or field of use, as discussed in MPEP § 2106.05(h).
This “execution of the at least one process” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(2) A “deploy the process simulation model” is a broad term which is described at a high level. M.P.E.P. § 2106.04(d)(I) recites:
The courts have also identified limitations that did not integrate a judicial exception into a practical application:
• Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f);
• Adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g); and
• Generally linking the use of a judicial exception to a particular technological environment or field of use, as discussed in MPEP § 2106.05(h).
This “deploy the process simulation model” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(3) A “generating, based on a training dataset, a data-driven model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “generating, based on a training dataset, a data-driven model” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(4) A “integrating the data-driven model within a process simulation model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “integrating the data-driven model within a process simulation model” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(5) A “process simulation model is configured to simulate an execution of the at least one process at one or more operating conditions of a plurality of operating conditions” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “the process simulation model is configured to simulate an execution of the at least one process at one or more operating conditions of a plurality of operating conditions” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(6) A “deploying the process simulation model for use” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “deploying the process simulation model for use” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(7) A “receiving, from one or more sensors, input data associated with the at least one process of the industrial plant” is a broad term which is described at a high level. M.P.E.P. § 2106.05(g) recites:
2106.05(g) Insignificant Extra-Solution Activity [R-10.2019]
Another consideration when determining whether a claim integrates the judicial exception into a practical application in Step 2A Prong Two or recites significantly more in Step 2B is whether the additional elements add more than insignificant extra-solution activity to the judicial exception. The term “extra-solution activity” can be understood as activities incidental to the primary process or product that are merely a nominal or tangential addition to the claim. Extra-solution activity includes both pre-solution and post-solution activity.
This “receiving, from one or more sensors, input data associated with the at least one process of the industrial plant” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(8) A “using the data-driven model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “using the data-driven model” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(9) A “industrial plant” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “industrial plant” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
(10) A “applying the at least one operating parameter to automatically reconfigure the physical component of the industrial plant” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
This “applying the at least one operating parameter to automatically reconfigure the physical component of the industrial plant” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
The answer to the inquiry is “NO”, no additional elements integrate the claimed abstract idea into a practical application.
Step 2B inquiry:
Does the claim provide an inventive concept, i.e., does the claim recite additional element(s) or a combination of elements that amount to significantly more than the judicial exception in the claim?
Applicant’s claims contain the following “additional elements”:
(1) An “execution of the at least one process”
(2) A “deploy the process simulation model”
(3) A “generating, based on a training dataset, a data-driven model”
(4) integrating the data-driven model within a process simulation model
(5) the process simulation model is configured to simulate an execution of the at least one process at one or more operating conditions of a plurality of operating conditions
(6) deploying the process simulation model for use
(7) receiving, from one or more sensors, input data associated with the at least one process of the industrial plant
(8) using the data-driven model
(9) industrial plant
(10) applying the at least one operating parameter to automatically reconfigure the physical component of the industrial plant
(1) A “execution of the at least one process” is a broad term which is described at a high level and includes general purpose computers. M.P.E.P. § 2106.05 (I)(A)(i-ii) recites:
Limitations that the courts have found not to be enough to qualify as “significantly more” when recited in a claim with a judicial exception include:
i. Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 573 U.S. at 225-26, 110 USPQ2d at 1984 (see MPEP § 2106.05(f));
ii. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d));
Further, M.P.E.P. § 2016.05(f) recites:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words “apply it” (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer. As explained by the Supreme Court, in order to make a claim directed to a judicial exception patent-eligible, the additional element or combination of elements must do “‘more than simply stat[e] the [judicial exception] while adding the words ‘apply it’”. Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984 (warning against a § 101 analysis that turns on “the draftsman’s art”).
Further, M.P.E.P. § 2106.05(f)(2) recites:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process.
Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
Further, Applicant's execution method is well-understood, routine and conventional. Applicant's Specification, paragraph [0110] recites:
[0110] The processes and logic flows described herein can be performed by one or more programmable processors executing one or more computer programs to perform actions by operating on input information/data and generating output. Processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor will receive instructions and information/data from a read-only memory or a random access memory or both. The essential elements of a computer are a processor for performing actions in accordance with instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive information/data from or transfer information/data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto-optical disks, or optical disks. However, a computer need not have such devices. Devices suitable for storing computer program instructions and information/data include all forms of non-volatile memory, media and memory devices, including by way of example semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices; magnetic disks, e.g., internal hard disks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(2) A “deploy the process simulation model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (I)(A)(i-ii) recites:
Limitations that the courts have found not to be enough to qualify as “significantly more” when recited in a claim with a judicial exception include:
i. Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 573 U.S. at 225-26, 110 USPQ2d at 1984 (see MPEP § 2106.05(f));
ii. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d));
Further, M.P.E.P. § 2016.05(f) recites:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words “apply it” (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer. As explained by the Supreme Court, in order to make a claim directed to a judicial exception patent-eligible, the additional element or combination of elements must do “‘more than simply stat[e] the [judicial exception] while adding the words ‘apply it’”. Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984 (warning against a § 101 analysis that turns on “the draftsman’s art”).
Further, M.P.E.P. § 2106.05(f)(2) recites:
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process.
Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
Applicant's “deploying” is well-understood, routine, and conventional because that deploying operation involves generic receiving, generating/calculating, and applying data. Applicant’s Specification, paragraph [0103] recites:
[0103] At block 606, the apparatus 200 includes first principles-driven prediction circuitry 210,data-driven prediction circuitry 212,optional control circuitry 214,communications circuitry 208,input/output circuitry 206,processor 202, and/or the like, or a combination thereof, that deploys the process simulation model for use. In some embodiments, deploying the process simulation model for use includes receiving input data, generating, using the data- driven model, the first model-predicted data, and applying the model-predicted data in one or more of engineering studies or offline optimization operation. In some embodiments, the input data includes process data associated with the at least one process. In some embodiments, the first model-predicted data is implemented as a constraint in one or more of (i) engineering studies or (ii) optimization operation.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(3) A “generating, based on a training dataset, a data-driven model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(4) A “integrating the data-driven model within a process simulation model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(5) A “the process simulation model is configured to simulate an execution of the at least one process at one or more operating conditions of a plurality of operating conditions” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(6) A “deploying the process simulation model for use” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(7) A “receiving, from one or more sensors, input data associated with the at least one process of the industrial plant” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); …
Further, M.P.E.P. § 2106.05(d)(I)(2) recites in part:
2. A factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity. Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (Fed. Cir. 2018). However, this does not mean that a prior art search is necessary to resolve this inquiry. Instead, examiners should rely on what the courts have recognized, or those in the art would recognize, as elements that are well-understood, routine, conventional activity in the relevant field when making the required determination. For example, in many instances, the specification of the application may indicate that additional elements are well-known or conventional. See, e.g., Intellectual Ventures v. Symantec, 838 F.3d at 1317; 120 USPQ2d at 1359 ("The written description is particularly useful in determining what is well-known or conventional"); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1418 (Fed. Cir. 2015) (relying on specification’s description of additional elements as "well-known", "common" and "conventional"); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 614, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (Specification described additional elements as "either performing basic computer functions such as sending and receiving data, or performing functions ‘known’ in the art.").
Further the claimed receiving of sensor data is generic, well-understood, routine, and conventional. Paragraph [0059] of Applicant’s Specification recites the following:
[0059] In some embodiments, one or more inputs for the first principles model 110 may be fixed input(s), while one or more inputs for the first principles model 110 may be variable input(s).
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Additionally or alternatively, one or more inputs for the first principles model 110 may include process data (e.g., plant data) received from the industrial plant system 104. In some embodiments, process data includes values (e.g., measurements) for one or more selected process variables. Non-limiting examples of process variables may include temperature, feed flow, pressure, and/or the like. In some examples, one or more equipment and/or processes associated with the industrial plant system 104 may include sensor device(s) for measuring and/or providing a portion of the input data (e.g., feed flow, temperature, pressure, and/or the like) for the first principles model 110. In some examples, a portion of the input data is measured in near real-time and provided to the first principles model in near real-time. In some examples, a portion of the input data may
include values for process variables that are periodically measured during plant operating using laboratory techniques (e.g., measured in a laboratory).
Merely using the conventional computer to receive data is well known, understood, and conventional. Thus, it adds nothing significantly more to the judicial exception.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(8) A “using the data-driven model” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(9) A “industrial plant” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Further, the term “an industrial plant” is generic, well-understood, routine, and conventional. Specifically, paragraph [0025] of Applicant’s Specification recites:
[0025] Various embodiments of the present disclosure address technical challenges related to process simulation. Process simulation models may be configured for modelling and/or simulating process(es) associated with, for example, an industrial plant (e.g., gas processing plants, oil refineries, and/or the like).
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
(10) A “applying the at least one operating parameter to automatically reconfigure the physical component of the industrial plant” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (f) recites in part:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
Therefore, the answer to the inquiry is “NO”, no additional elements provide an inventive concept that is significantly more than the claimed abstract ideas the claimed abstract idea into a practical application.
Claim 20 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Reasons for Not Rejecting the Claims on Art
The trained data driven model in the claims is taught by the prior art’s Reinforcement Learning neural network on the left side of Fig. 1. The output of this model, in the prior art, is tuned “Model Parameters,” rather than “model-predicted data.”
Further, in the prior art, the claimed “model-predicted data” (i.e., the predicted plant states labelled “Prediction” in the prior art) are calculated by the “Process Model” (i.e., the clamed “first principles model”), rather than the “data-driven model” in the claim.
Response to Arguments
Applicant's arguments filed 28 APR 2026 have been fully considered but they are not persuasive. Specifically, Applicant argues:
Argument 1
Step 2A, Prong One
Applicant submits that the claims, as amended herein, recite subject matter that is not directed towards mentals steps or mathematical steps. For example, amended independent claim 1 recites inter alia:
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Amended independent claim 1.
There are, in fact, mental steps and mathematical steps in the independent clams. For instance, the amended claims include the following limitation:
“determining at least one operating parameter for a physical component involved in the at least one process of the industrial plant using the first model-predicted data”
This “determining” step, in its broadest reasonable interpretation, is clearly a mental step. The mind may determine which parameters apply to the physical component; the mind may determine the proper units for the parameter; and the mind may determine a value for the parameter, whether it is by calculation, by guessing, or by trial and error. Therefore, there is a “mental step” in the clams.
Applicant’s argument is unpersuasive.
The 35 U.S.C § 101 rejections stand.
Argument 2
Amended independent claims 12 and 20 include similar amendments. Applicant submits that the amended independent claim 1 is not directed to mental steps or a mathematical concept at least because it requires a concrete machine-implemented industrial workflow that ends in an automatic change to physical equipment operation and therefore cannot be performed by a human mind with pen and paper (sic. No period in the original)
Similar amendments are similarly unpersuasive.
The 35 U.S.C § 101 rejections stand.
Argument 3
Moreover, the amended independent claim 1 requires applying the determined operating parameter to automatically reconfigure the physical component of the industrial plant, and that requirement is the opposite of a purely mathematical result because it necessarily entails machine- to-machine interaction between the process simulation system and an industrial plant system to implement control or adjustment of operation of physical components based at least in part on model-predicted data, including automatic configuration or reconfiguration of physical components. Further, such communication and automatic reconfiguration include control circuitry configured to cause automatic reconfiguration of a physical component based on outputs of the process simulation system, first principles model, and data-driven model, which makes clear that the claimed "applying" step is realized through computing and control hardware acting on real- world equipment rather than through human judgment. At least because the amended independent claim 1 requires the afore-mentioned automatic equipment reconfiguration, the amended independent claim 1 cannot be carried out mentally.
Applicant does not specify what physical components are reconfigured. Those physical components may be generic computer memories or transitory computer readable media. The reconfiguration of such components adds nothing significantly more to the original abstract ideas in the claim.
Applicant’s argument is unpersuasive.
The 35 U.S.C § 101 rejections stand.
Argument 4
Furthermore, a person/human mind cannot mentally receive and process industrial plant data streams, execute an integrated first-principles model and machine-learning model within a process simulation environment across multiple operating conditions, compute an operating parameter tied to equipment operation, and then cause the plant system to automatically reconfigure the physical component. These are functions of the described process simulation system architecture and plant-side control integration, not of human cognition. For the same reason, even if assuming arguendo that training, prediction, and optimization internally employ mathematics, the amended independent claim is not "directed to" mathematics because the mathematics is used only as part of an applied industrial process- simulation-and-control implementation that delivers a required physical outcome (automatic reconfiguration of plant equipment), and that outcome supplies the additional technological application that the rejection asserts is missing, namely a concrete use of model output to control or adjust operation of physical components rather than merely generating or reporting computed results.
Accordingly, the amended independent claim 1 is not directed to the alleged judicial exception under Prong One of Step 2A.
The amended claims include the following limitation:
“determining at least one operating parameter for a physical component involved in the at least one process of the industrial plant using the first model-predicted data”
This “determining” step, in its broadest reasonable interpretation, is clearly a mental step. The mind may determine which parameters apply to the physical component; the mind may determine the proper units for the parameter; and the mind may determine a value for the parameter, whether it is by calculation, by guessing, or by trial and error. Therefore, there is a “mental step” in the clams. Further such matter is itemized in the rejections, above.
Applicant’s argument is unpersuasive.
The 35 U.S.C § 101 rejections stand.
Argument 5
The claimed invention is practically realized in domains such as industrial plants, including gas processing plants, oil refineries, and the like, where complex processes must be continuously monitored, analyzed, and optimized to maintain performance and safety. In a typical operating plant, large volumes of process data are generated by field instruments measuring temperatures, pressures, flow rates, and other variables across interconnected physical components. This data is fed into a process simulation system that represents the plant in software and is used by engineers and operators to understand how the plant behaves under different operating conditions. Within this environment, the claimed invention is implemented by integrating a data driven model into the process simulation model alongside a first principles model, enabling the simulation to predict key process variables that are not readily measurable in real time or derivable solely from physical equations. As the simulated plant is exercised across different operating conditions, the integrated models generate predicted values that reflect actual plant behavior between laboratory measurements. These predictions are then used within the simulation to determine improved operating parameters for specific physical components involved in the process. Once identified, those operating parameters are applied back to the industrial plant system, which automatically reconfigures the affected physical components so that the real plant operates according to the optimized conditions identified in the simulation. In this way, the claimed invention is implemented as a continuous loop that connects real plant operation, advanced simulation, and automated equipment adjustment, allowing industrial facilities to operate closer to desired targets while relying on a practical, production level deployment rather than abstract analysis.
Accordingly, Applicant submits that the claims present patent eligible subject matter under at least prong Two of Step 2A of the Alice/Mayo test.
Applicant’s argued “domains” are merely generic fields of use. Specifically, Applicant argues:
“domains such as industrial plants, including gas processing plants, oil refineries, and the like”
Regarding the “additional elements”, Applicant’s argument is conclusory. Examiner itemizes and addresses those elements in the rejection, above.
Applicant’s argument is unpersuasive.
The 35 U.S.C § 101 rejections stand.
Argument 6
Step 2B
Regarding Step 2B, even if one were to arrive at a conclusion satisfying the Step 2A of such analysis, assuming arguendo, to which the Applicant does not concede, the Applicant submits that elements of amended independent claim 1 provide an inventive concept and amounts to significantly more than the alleged judicial exception.
In process simulation of industrial plants, such as gas processing plants, oil refineries, and similar large scale facilities, conventional simulation techniques fail to provide complete and continuous insight into plant performance. In these environments, many key process variables and performance indicators that are critical for monitoring, optimization, and decision-making are either not directly measurable in real time or cannot be accurately computed using first principles, physics based models alone. Instead, such variables are often obtained only through periodic laboratory measurements, leaving substantial gaps in visibility between measurements. This limitation restricts the ability of process simulation and digital twin systems to accurately predict plant behavior, evaluate operating alternatives, or use those variables as constraints in optimization and engineering studies. As a result, important performance calculations are traditionally relegated to separate control or analytics layers, reducing the effectiveness, accuracy, and adoption of process simulation models within industrial plant operations.
A technical solution provided by the claimed invention is to augment a conventional first principles process simulation with an integrated data driven soft sensor model and to operationalize the resulting predictions within an industrial plant environment. Specifically, the solution involves generating a data driven model using historical process and laboratory data to predict target process variables that are not readily measurable in real time or derivable from physics based equations. This data driven model is embedded directly within a process simulation model that also includes a first principles model, enabling the combined simulation to represent plant behavior more accurately across a range of operating conditions. During deployment, the integrated simulation receives live or recorded process input data from the industrial plant, generates predicted values for the target variables, and uses those predicted values within the simulation to perform optimization and determine suitable operating parameters for physical components involved in the process. The determined operating parameters are then applied back to the industrial plant system to automatically reconfigure the relevant physical components, thereby translating the predictive and optimization results into concrete operational changes. In this way, the claimed solution technically addresses the limitations of first principles simulations by enabling continuous prediction and use of otherwise unavailable key performance indicators and by closing the loop between simulation, optimization, and real-world plant operation.
At least one technical advantage of the claimed invention lies in its ability to enhance the accuracy, usefulness, and operational impact of process simulation systems used in industrial plants (i.e., field of use) by overcoming limitations of conventional first principles modeling. By integrating a data driven soft sensor model directly into a process simulation model, the invention enables continuous prediction of key process variables and performance indicators that are otherwise unavailable between laboratory measurements or not derivable from physics based equations. This integration allows the simulation to reflect actual plant behavior more faithfully across a range of operating conditions, improving the reliability of simulations, engineering studies, and optimization results.
A further technical advantage is the closed loop application of simulation outputs, where predicted values are used to determine operating parameters that are automatically applied to reconfigure physical plant components, thereby translating analytical insight into real-world operational changes. As a result, industrial plants can operate closer to desired targets, respond more effectively to changing conditions, and reduce the reliance on separate analytics or control layers, leading to improved performance, efficiency, and adoption of digital twin and process simulation technologies in live industrial environments.
Accordingly, based at least on the above, Applicant submits that the claim elements of amended independent claim 1 individually, and in combination as a whole amounts to significantly more than the alleged judicial exception. Therefore, the Applicant respectfully submits that amended independent claim 1 (and dependents therefrom) recites patent eligible subject matter.
Applicant argues an “inventive concept” rather than a “practical application.” Specifically, Applicant’s argument recites:
“…provide an inventive concept and amounts to significantly more than the alleged judicial exception…”
Since Applicant does not argue that there is a “practical application,” Applicant’s argument is unpersuasive.
The 35 U.S.C § 101 rejections stand.
Argument 7
Further, amended independent claims 12 and 20 (and their respective dependents therefrom) also recite patent eligible subject matter based at least on the reasons stated above with regard to amended independent claim 1. Therefore, the Applicant respectfully requests that the rejection of claims 1-20 under 35 U.S.C. § 101 be withdrawn.
Similar arguments for similar independent claims are similarly unpersuasive.
Since there is no eligible matter to be found in the independent claims, there is no such matter that may be incorporated by reference to the dependent claims in order to cure their defects under 35 U.S.C § 101.
Applicant’s arguments under 35 U.S.C § 101 are unpersuasive.
The rejections stand.
Argument 8
C. Rejection of Dependent Claims
The patentability of the independent claims has been argued as set forth above and thus Applicant will not take this opportunity to argue the merits of the rejection with regard to each dependent claim. However, Applicant does not concede that the dependent claims are not independently patentable and reserves the right to argue the patentability of the dependent claims at a later date if necessary.
The 35 U.S.C § 102 rejections are withdrawn.
Regarding the 35 U.S.C § 101 rejections, similar arguments for similar independent claims are similarly unpersuasive.
Since there is no eligible matter to be found in the independent claims, there is no such matter that may be incorporated by reference to the dependent claims in order to cure their defects under 35 U.S.C § 101.
Applicant’s arguments under 35 U.S.C § 101 are unpersuasive.
The rejections stand.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiries concerning this communication or earlier communications from the examiner should be directed to Wilbert L. Starks, Jr., who may be reached Monday through Friday, between 8:00 a.m. and 5:00 p.m. EST. or via telephone at (571) 272-3691 or email: Wilbert.Starks@uspto.gov.
If you need to send an Official facsimile transmission, please send it to (571) 273-8300.
If attempts to reach the examiner are unsuccessful the Examiner’s Supervisor (SPE), Kakali Chaki, may be reached at (571) 272-3719.
Hand-delivered responses should be delivered to the Receptionist @ (Customer Service Window Randolph Building 401 Dulany Street, Alexandria, VA 22313), located on the first floor of the south side of the Randolph Building.
Finally, information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Moreover, status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have any questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) toll-free @ 1-866-217-9197.
/WILBERT L STARKS/
Primary Examiner, Art Unit 2122
WLS
06 AUG 2026
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