DETAILED ACTION
Status of the Application
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This communication is a non-final action in response to the communications filed on 6/22/2023. Claims 1-16 are currently pending and have been considered below.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. Claims 1-16 are determined to be directed to an abstract idea.
The claims 1-16 are directed to a judicial exception (i.e., law of nature, natural phenomenon, or abstract idea), without providing a practical application integration and without providing significantly more.
As per Step 1 of the subject matter eligibility analysis, Claims 1-11 and 13-16 are directed to a method (i.e., process), system/apparatus which are one of the four statutory categories of invention. Claim 12 fails Step 1 since Claim 12 is directed to signals per se and software per se (See MPEP 2106.03)
As per Step 2A-Prong 1 of the subject matter eligibility analysis, Claims 1, 10 and 12 are directed specifically to the abstract idea of producing a chemical formulation in a chemical production facility, preferably for guiding the production of a chemical formulation, comprising:(a) receiving input data of at least one set of experimental data comprising formulation data and/or process data and/or key physicochemical properties of the components and/or the formulation and a target product profile, TPP, comprising a minimum product requirement (b) performing multicriterial optimization based on a computational model based on experimental data; all of which include mental processes (evaluating input data to make a judgement or opinion optimizing), and certain methods of organizing human activity based on fundamental economic practice (producing a chemical formulation in a chemical production facility), and based on managing personal behavior and interactions between people (following rules and instruction for producing a chemical formulation in a chemical production facility). Claims 2-9, 11, 13-16 are directed to the abstract idea of claim 1 with further details on the parameters/attributes of the abstract idea which includes mental processes and certain methods of organizing human activity for similar reasons as provided above for claim 1. After considering all claim elements, both individually and in combination and in ordered combination, it has been determined that the claims do not amount to significantly more than the abstract idea itself.
As per Step 2A-Prong 2 of the subject matter eligibility analysis, while the claims 1-16 recite additional limitations which are hardware or software elements, such as a computer, input unit, processing unit, providing optimization signal, preferably via an output unit, wherein the optimization signal is configured to control and/or monitor, preferably via a control unit, the production process of the chemical formulation, a web server configured to interface with a user via a webpage and/or an application program served by the web server; wherein the apparatus is configured to provide a graphical user interface, GUI, to a user, by the webpage and/or the application program, computer program element comprising sets of instructions, wherein, when the sets of instructions are executed on a processor of the apparatus, the sets of instructions cause the apparatus or the system to perform the method, these limitations are not enough to qualify as a practical application being recited in the claims along with the abstract idea since these elements are merely invoked as a tool to apply instructions of an abstract idea in a particular technological environment, and mere application of an abstract idea in a particular technological environment and merely limiting the use of an abstract idea to a particular technological field do not integrate an abstract idea into a practical application (MPEP 2106.05(f)&(h)). The claims do not amount to "practical application" for the abstract idea because they neither (1) recite any improvements to another technology or technical field; (2) recite any improvements to the functioning of the computer itself; (3) apply the judicial exception with, or by use of, a particular machine; (4) effect a transformation or reduction of a particular article to a different state or thing; (5) provide other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment. Alternatively, receiving and/or transmitting data between devices is mere data gathering and insignificant extrasolution activity, which does not provide a practical application for the abstract idea (MPEP 2106.05(g)).
As per Step 2B of the subject matter eligibility analysis, while the claims 1-16 recite additional limitations which are hardware or software elements, such as a computer, input unit, processing unit, providing optimization signal, preferably via an output unit, wherein the optimization signal is configured to control and/or monitor, preferably via a control unit, the production process of the chemical formulation, a web server configured to interface with a user via a webpage and/or an application program served by the web server; wherein the apparatus is configured to provide a graphical user interface, GUI, to a user, by the webpage and/or the application program, computer program element comprising sets of instructions, wherein, when the sets of instructions are executed on a processor of the apparatus, the sets of instructions cause the apparatus or the system to perform the method, these limitations are not enough to qualify as “significantly more” being recited in the claims along with the abstract idea since these elements are merely invoked as a tool to apply instructions of an abstract idea in a particular technological environment, and mere application of an abstract idea in a particular technological environment and merely limiting the use of an abstract idea to a particular technological field do provide significantly more to an abstract idea (MPEP 2106.05 (f) & (h)). The claims do not amount to "significantly more" than the abstract idea because they neither (1) recite any improvements to another technology or technical field; (2) recite any improvements to the functioning of the computer itself; (3) apply the judicial exception with, or by use of, a particular machine; (4) effect a transformation or reduction of a particular article to a different state or thing; (5) add a specific limitation other than what is well-understood, routine and conventional in the field; (6) add unconventional steps that confine the claim to a particular useful application; nor (7) provide other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment. Alternatively, receiving and/or transmitting data between devices is mere data gathering and insignificant extrasolution activity, and also is well-understood, routine and conventional which do not provide a practical application for the abstract idea (MPEP 2106.05(g) & (d)).
Therefore, since there are no limitations in the claims 1-16 that transform the exception into a patent eligible application such that the claims amount to significantly more than the exception itself, and looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually, the claims are rejected under 35 USC § 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 12 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends.
The claim does not include all limitations of the parent claim it depends from. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-16 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Bortz et al (M. Bortz, J. Burger, N. Asprion, S. Blagov, R. Böttcher, U. Nowak, A. Scheithauer, R. Welke, K.-H. Küfer, H. Hasse, “Multi-criteria optimization in chemical process design and decision support by navigation on Pareto sets”, Computers & Chemical Engineering, Volume 60, 10 January 2014, Pages 354-363)
As per Claim 1, Bortz teaches a computer implemented method for producing a chemical formulation in a chemical production facility, preferably for guiding the production of a chemical formulation (Abstract, page 355 “graphical user interface” i.e., computer implemented), comprising:
receiving input data, preferably via an input unit, of at least one set of experimental data comprising formulation data and/or process data and/or key physicochemical properties of the components and/or the formulation and a target product profile, TPP, comprising a minimum product requirement (fig. 1 pages 355-356 regarding input variables such as set/free design variables, process variables, objectives, minimal number of points for calculation);
performing multicriterial optimization based on a computational model based on experimental data via a processing unit (Abstract, page 355 “In this work we present a tool, which couples a commercial process simulator with multi-criteria techniques and overcomes the earlier mentioned drawbacks related to calculation speed, accuracy and Pareto set exploration… We calculate the approximation of the Pareto set by using a combination of evolutionary and efficient derivative-based algorithms…”; page 361, “The generation of Pareto sets for multi-criteria optimization problems in chemical process design is a powerful concept. In this work, a novel and effective algorithm to calculate Pareto sets was integrated in a state-of-the art process simulator. For any process for which a simulation can be set up, Pareto sets can be generated after defining a suitable design and objective space. The decision maker then navigates on the Pareto sets to find a process design of his choice. That choice is embedded in the knowledge of the entire set of Pareto-optimal solutions. The navigation is an interactive process, so that the process design method introduced in the present work can be characterized as interactive multi-criteria optimization (IMCO)… The user can explore the trade-offs between objectives, compare different alternatives with respect to different objectives and finally arrive at a well-founded decision. As only optimal compromises are included in the Pareto set a guarantee for optimality can be given”); and
providing optimization signal, preferably via an output unit, wherein the optimization signal is configured to control and/or monitor, preferably via a control unit, the production process of the chemical formulation (page 361, “The generation of Pareto sets for multi-criteria optimization problems in chemical process design is a powerful concept. In this work, a novel and effective algorithm to calculate Pareto sets was integrated in a state-of-the art process simulator. For any process for which a simulation can be set up, Pareto sets can be generated after defining a suitable design and objective space. The decision maker then navigates on the Pareto sets to find a process design of his choice. That choice is embedded in the knowledge of the entire set of Pareto-optimal solutions. The navigation is an interactive process, so that the process design method introduced in the present work can be characterized as interactive multi-criteria optimization (IMCO)… The user can explore the trade-offs between objectives, compare different alternatives with respect to different objectives and finally arrive at a well-founded decision. As only optimal compromises are included in the Pareto set a guarantee for optimality can be given”).
As per Claim 2, Bortz teaches a method as provided in claim 1 above. Bortz further teaches wherein the multi-criteria optimization is based on the set of experimental data, to construct a Pareto frontier, wherein the set of experimental data are evaluated with at least two objectives measuring qualities of the set of experimental data, wherein formulations on the constructed Pareto frontier are Pareto optimal with respect to the objectives (fig. 1 pages 355-356 regarding input variables such as set/free design variables, process variables, objectives, minimal number of points for calculation; page 354 regarding multiple conflicting objectives; page 361, “The generation of Pareto sets for multi-criteria optimization problems in chemical process design is a powerful concept. In this work, a novel and effective algorithm to calculate Pareto sets was integrated in a state-of-the art process simulator. For any process for which a simulation can be set up, Pareto sets can be generated after defining a suitable design and objective space. The decision maker then navigates on the Pareto sets to find a process design of his choice. That choice is embedded in the knowledge of the entire set of Pareto-optimal solutions. The navigation is an interactive process, so that the process design method introduced in the present work can be characterized as interactive multi-criteria optimization (IMCO)… The user can explore the trade-offs between objectives, compare different alternatives with respect to different objectives and finally arrive at a well-founded decision. As only optimal compromises are included in the Pareto set a guarantee for optimality can be given”).
As per Claim 3, Bortz teaches a method as provided in claim 2 above. Bortz further teaches wherein the optimization results are provided in a way that navigation on the pareto frontiers is possible (page 355 “The decision maker can then interactively explore the Pareto set by navigating with a graphical user interface (GUI). Graphical sliders are used for this purpose, each corresponding to one objective. By moving one slider, the other sliders are updated in real time, i.e., information on the trade-offs between the best compromises is directly visualized.”).
As per Claim 4, Bortz teaches a method as provided in claim 1 above. Bortz further teaches wherein the optimization results are provided in a way that the entire class of results covered by the invariant subspace is accessible (page 355 “The decision maker can then interactively explore the Pareto set by navigating with a graphical user interface (GUI). Graphical sliders are used for this purpose, each corresponding to one objective. By moving one slider, the other sliders are updated in real time, i.e., information on the trade-offs between the best compromises is directly visualized.”; page 362-363, regarding navigation).
As per Claim 5, Bortz teaches a method as provided in claim 1 above. Bortz further teaches wherein the input data is generated via Design of Experiments (DoE) technique (Abstract, regarding simulation (i.e., experimental) based design process).
As per Claim 6, Bortz teaches a method as provided in claim 1 above. Bortz further teaches wherein the formulation data comprises formulation components and amounts of formulation components (fig. 1 pages 355-356 regarding input variables such as set/free design variables, process variables, objectives, minimal number of points for calculation; page 354 regarding multiple conflicting objectives).
As per Claim 8, Bortz teaches a method as provided in claim 5 above. Bortz further teaches wherein the Design of experiments (DoE) is based on a kernel model (page 355, “During a short initial evolutionary phase, a variety of starting points [i.e., kernels] close to the expected Pareto surface is generated. From these starting points, a sequential quadratic-programming algorithm is applied to find the Pareto points.”).
As per Claim 9, Bortz teaches a method as provided in claim 1 above. Bortz further teaches wherein the chemical production facility is a chemical plant (Abstract, page 355 “The tool can in principle deal with an arbitrary number of objectives in calculation as well as in visualization. As itis integrated into a state-of-the-art process simulator, its applications range from optimization of single apparatuses up to the design of new plants.”).
Claim 10 recites substantially similar limitations to Claim 1; therefore, Claim 10 is rejected with the same reasoning provided above for claim 1.
As per Claim 13, Bortz teaches a method as provided in claim 1 above. Bortz further teaches providing a target performance characteristic of a chemical formulation; providing a performance characteristic of a produced chemical formulation; and comparing the performance characteristic with the target performance characteristics of the chemical formulation to determine if the produced chemical formulation fulfils predetermined quality criteria (page 355, “the GUI allows a simultaneous visualization of different Pareto sets which enables comparing different variants of the process based on different flow sheets.”; page 361, “The user can explore the trade-offs between objectives, compare different alternatives with respect to different objectives and finally arrive at a well-founded decision. As only optimal compromises are included in the Pareto set a guarantee for optimality can be given”).
As per Claim 14, Bortz teaches a method as provided in claim 1 above. Bortz further teaches providing an existing performance characteristic for a chemical formulation that has been produced from validated precursors; generating a optimization signal based on the existing performance characteristic, wherein the optimization signal comprises an ingredient identifier and related property data, which are associated with at least one new precursor; and comparing a performance characteristic of a chemical formulation produced using the optimization signal and the existing performance characteristic to validate the at least one new precursor (page 357, “Because of the weighted sum scalarization, the approximation quality is valid only for the convex regions of the Pareto set. To detect possible candidate regions which might show non-convex behavior, we take the Pareto points calculated so far and exclude the strictly dominated and non-dominated regions for every Pareto point and thus obtain hyperboxes with Pareto points on some corners”; page 355, “the GUI allows a simultaneous visualization of different Pareto sets which enables comparing different variants of the process based on different flow sheets.”; page 361, “The user can explore the trade-offs between objectives, compare different alternatives with respect to different objectives and finally arrive at a well-founded decision. As only optimal compromises are included in the Pareto set a guarantee for optimality can be given”).
As per Claim 15, Bortz teaches a method as provided in claim 13 above. Bortz further teaches apparatus for monitoring production of a chemical formulation, the apparatus comprising one or more processing unit(s) configured to monitor production, wherein the processing unit(s) include instructions, which when executed on the one or more processing unit(s) execute the method steps (page 355, “the GUI allows a simultaneous visualization of different Pareto sets which enables comparing different variants of the process based on different flow sheets.”; page 361, “The user can explore the trade-offs between objectives, compare different alternatives with respect to different objectives and finally arrive at a well-founded decision. As only optimal compromises are included in the Pareto set a guarantee for optimality can be given”).
As per Claim 16, Bortz teaches a method/apparatus as provided in claim 14 above. Bortz further teaches apparatus for validating production of a chemical formulation, the apparatus comprising one or more processing unit(s) configured to validate production, wherein the processing unit(s) include instructions, which when executed on the one or more processing unit(s) execute the method steps (page 355, “the GUI allows a simultaneous visualization of different Pareto sets which enables comparing different variants of the process based on different flow sheets.”; page 361, “The user can explore the trade-offs between objectives, compare different alternatives with respect to different objectives and finally arrive at a well-founded decision. As only optimal compromises are included in the Pareto set a guarantee for optimality can be given”).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim 11-12 are rejected under 35 U.S.C. 103 as being unpatentable over Bortz et al (M. Bortz, J. Burger, N. Asprion, S. Blagov, R. Böttcher, U. Nowak, A. Scheithauer, R. Welke, K.-H. Küfer, H. Hasse, “Multi-criteria optimization in chemical process design and decision support by navigation on Pareto sets”, Computers & Chemical Engineering, Volume 60, 10 January 2014, Pages 354-363) in view of Palsson et al (CA 2462099 C).
As per Claim 11, Bortz teaches an apparatus as provided in claim 10 above. Bortz further teaches providing assistance for optimizing chemical formulations, comprising: interface with a user via a webpage and/or an application program; wherein the apparatus is configured to provide a graphical user interface, GUI, to a user, by the webpage and/or the application program (page 355 “In this work we present a tool, which couples a commercial process simulator with multi-criteria techniques and overcomes the earlier mentioned drawbacks related to calculation speed, accuracy and Pareto set exploration…The decision maker can then interactively explore the Pareto set by navigating with a graphical user interface (GUI). Graphical sliders are used for this purpose, each corresponding to one objective. By moving one slider, the other sliders are updated in real time, i.e., information on the trade-offs between the best compromises is directly visualized.”; page 361, “The user can explore the trade-offs between objectives, compare different alternatives with respect to different objectives and finally arrive at a well-founded decision. As only optimal compromises are included in the Pareto set a guarantee for optimality can be given”).
Bortz does not teach a web server; however, Palsson teaches providing assistance for optimizing formulations, comprising: a web server configured to interface with a user via a webpage and/or an application program served by the web server (para. 0075, web server and an application, 0079, optimizing equations, 0080, interfaces).
It would be obvious to one of ordinary skill in the art, before the earliest effective filing date of the invention, to modify Bortz with the aforementioned teachings of Palsson, in the field of modeling chemical compositions, with the motivation to provide a secure and user friendly environment for the user.
Claim 12 recites substantially similar limitations to Claim 11; therefore, Claim 12 is rejected with the same reasoning provided above for Claim 11.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Bortz et al (M. Bortz, J. Burger, N. Asprion, S. Blagov, R. Böttcher, U. Nowak, A. Scheithauer, R. Welke, K.-H. Küfer, H. Hasse, “Multi-criteria optimization in chemical process design and decision support by navigation on Pareto sets”, Computers & Chemical Engineering, Volume 60, 10 January 2014, Pages 354-363) in view of Verbeck (CN 108473305 B).
As per Claim 7, Bortz teaches a method as provided in claim 5 above. Bortz does not teach; Verbeck teaches further teaches wherein the Design of experiments (DoE) is based on a Gaussian Process model (“In one embodiment, the stacking model with dynamic backward air of one or more target molecules on the one or more sampling positions of the dispersed can by solving the Gaussian dispersion equation generation based on presence of chemical sensing and/or concentration. In one embodiment, the Gaussian dispersion equation can be used for continuously Gaussian dispersion equation…”).
It would be obvious to one of ordinary skill in the art, before the earliest effective filing date of the invention, to modify Bortz with the aforementioned teachings of Verbeck, in the field of modeling equations for chemical sensing, with the motivation to enable the use of various statistical techniques including the Gaussian model to find the most accurate results.
Conclusion
Additional relevant art not relied upon, specifically related to blockchain and PBFT combination, includes:
Grass (US-20020061540-A1),
Amid (US-20150019173-A1),
Qian (CN-101508768-A),
All regarding multicriteria optimization of formulations.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MEHMET YESILDAG whose telephone number is (571)272-3257. The examiner can normally be reached M-F 8:30 am - 5:00 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jerry O'Connor can be reached on (571) 272-6787. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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Sincerely,
/MEHMET YESILDAG/Primary Examiner, Art Unit 3624