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 .
Priority
Examiner acknowledges Applicant’s claim to priority regarding Provisional Application filed on 10/03/2016 and as a continuation of 15/723,554 filed on 10/03/2017.
Information Disclosure Statement
The information disclosure statement (IDS) filed on 04/22/2025 has been fully considered.
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 1-20 are rejected under 35 USC 101 because the claimed invention is directed to a judicial exception (i.e. abstract idea) without anything significantly more.
Step 1: Claims 1-7 are directed to a method, claims 8-14 are directed to a system, and claims 15-20 are directed to a non-transitory computer readable medium. Therefore, the claims are directed to patent eligible categories of invention.
Step 2A, Prong 1: Independent claims 1, 8, and 15 recite organizing a supply chain network around key process indicators, constituting an abstract idea based on “Certain Methods of Organizing Human Activity” related to commercial interactions including advertising or marketing sales activities or behaviors, as well as business relations. Claim 1 recites limitations, similarly recited in claims 8 and 15, including “identifying one or more supply chain models by assigning a name to the one or more supply chain models; identifying one or more principal key process indicators; assigning the one or more principal key process indicators to vertices of a performance radar; assigning target values to each of the one or more principal key process indicators on the performance radar for each of the one or more supply chain models; and organizing a supply chain network around the one or more principal key process indicators target values for each supply chain model.” These limitations, as drafted, is a process that, under its broadest reasonable interpretation, but for the language of “a computer comprising a processor and memory and configured to,” covers an abstract idea but for the recitation of generic computer components. That is, other than reciting “a computer comprising a processor and memory and configured to,” nothing in the claim elements preclude the steps from being interpreted as an abstract idea. For example, with the exception of the “a computer comprising a processor and memory and configured to” language, the claim steps in the context of the claim encompass an abstract idea directed to “Certain Methods of Organizing Human Activity.”
Dependent claims 2-7, 9-14, and 16-20 further narrow the abstract idea identified in the independent claims and do not introduce further additional elements for consideration.
Step 2A, Prong 2: Independent claims 1, 8, and 15 do not integrate the judicial exception into a practical application. Claim 1 recites “a computer-implemented method for defining one or more supply chain models to support customer business models by a computer comprising a processor and a memory, comprising” in the preamble of the claim. Claim 8 recites “a system for defining one or more supply chain models to support customer business models, comprising: a computer comprising a processor and a memory and configured to.” Claim 15 recites “a non-transitory computer-readable medium embodied with software, the software when executed configured for defining one or more supply chain models to support customer business models by” within the preamble of the claim. These additional elements are mere instructions to implement an abstract idea using a computer in its ordinary capacity, or merely uses the computer as a tool to perform the identified abstract idea. Use of a computer or other machinery in its ordinary capacity for 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., certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f). Therefore, the additional elements of the independent claims, when considered both individually and in combination, are not sufficient to prove integration into a practical application.
Dependent claims 2-7, 9-14, and 16-20 further narrow the abstract idea identified in the independent claims and do not introduce further additional elements for consideration, which does not integrate the judicial exception into a practical application.
Step 2B: Independent claims 1, 8, and 15 do not comprise anything significantly more. Claim 1 recites “a computer-implemented method for defining one or more supply chain models to support customer business models by a computer comprising a processor and a memory, comprising” in the preamble of the claim. Claim 8 recites “a system for defining one or more supply chain models to support customer business models, comprising: a computer comprising a processor and a memory and configured to.” Claim 15 recites “a non-transitory computer-readable medium embodied with software, the software when executed configured for defining one or more supply chain models to support customer business models by” within the preamble of the claim. These additional elements are mere instructions to implement an abstract idea using a computer in its ordinary capacity, or merely uses the computer as a tool to perform the identified abstract idea. Use of a computer or other machinery in its ordinary capacity for 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., certain methods of organizing human activity) is not anything significantly more. See MPEP 2106.05(f). Therefore, the additional elements of the independent claims, when considered both individually and in combination, are not anything significantly more.
Dependent claims 2-7, 9-14, and 16-20 further narrow the abstract idea identified in the independent claims and do not introduce further additional elements for consideration, which is not anything significantly more.
Accordingly, claims 1-20 are rejected under 35 USC 101.
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 (i.e., changing from AIA to pre-AIA ) 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Srivastava et al. (US 20180144277 A1) in view of Mbaga et al. ("A comparative study of dates export supply chain performance: the case of Oman and Tunisia." 2011).
Regarding claim 1, Srivastava teaches a computer-implemented method for defining one or more supply chain models to support customer business models by a computer comprising a processor and a memory (Fig. 3 and [0032-0033] teach a computer system comprising a processor and memory), comprising (Fig. 2):
identifying one or more supply chain models by assigning a name to the one or more supply chain models ([0010] teaches a plurality of product lifecycle models are used to select the new optimal design for the product by identifying a plurality of model alternatives for each of the plurality of product lifecycle models, wherein the model alternatives are created, wherein each combination includes a model alternative for each product lifecycle stage, wherein a simulation is generated of each of the plurality of alternative combinations of the model alternatives and the optimal design is selected based on the plurality of simulation results, wherein [0021] teaches there are several stages associated with a product including design, manufacturing planning, manufacturing execution, supply chain, storage, operations, and recycle/disposal, wherein the number and type of stages is product dependent, and wherein Fig. 1 and [0022] teach each PL stage and the associated information with each stage; see also: [0025-0030]);
identifying one or more principal key process indicators ([0010] teaches a plurality of product lifecycle models are used to select the new optimal design for the product by identifying a plurality of model alternatives for each of the plurality of product lifecycle models, wherein the model alternatives are created, wherein each combination includes a model alternative for each product lifecycle stage, wherein a simulation is generated of each of the plurality of alternative combinations of the model alternatives and the optimal design is selected based on the plurality of simulation results, wherein [0025] teaches a plurality of models are developed for desired key performance indicators including cost and quality for each product lifecycle, wherein the desired KPIs can measure the various aspects of the model, wherein [0027] teaches the alternative spaces represent the various possible combinations of model alternative from different PL stages will be automatically created and the models for each option of each PL stage will be used to simulate each scenario, wherein the multi-objective optimization problem will be carried out in this space to optimize the considered KPIs for the overall PL, accounting for each stage, while adhering to product design constraints, wherein [0029] teaches a score is computer for each alternative path based on the aggregated KPIs over the product lifecycle, wherein the score is a cost function based on the computer KPIs; see also: [0026, 0030]);
assigning the one or more principal key process indicators to vertices of a performance radar ([0010] teaches a plurality of product lifecycle models are used to select the new optimal design for the product by identifying a plurality of model alternatives for each of the plurality of product lifecycle models, wherein the model alternatives are created, wherein each combination includes a model alternative for each product lifecycle stage, wherein a simulation is generated of each of the plurality of alternative combinations of the model alternatives and the optimal design is selected based on the plurality of simulation results, wherein [0025] teaches a plurality of models are developed for desired key performance indicators including cost and quality for each product lifecycle, wherein the desired KPIs can measure the various aspects of the model, wherein [0027] teaches the alternative spaces represent the various possible combinations of model alternative from different PL stages will be automatically created and the models for each option of each PL stage will be used to simulate each scenario, wherein the multi-objective optimization problem will be carried out in this space to optimize the considered KPIs for the overall PL, accounting for each stage, while adhering to product design constraints, wherein [0029] teaches a score is computer for each alternative path based on the aggregated KPIs over the product lifecycle, wherein the score is a cost function based on the computer KPIs; see also: [0026, 0030]; Examiner’s Note: See the 35 USC 103 combination below for teachings pertaining to the unbolded claim language.);
assigning target values to each of the one or more principal key process indicators on the performance radar for each of the one or more supply chain models ([0010] teaches a plurality of product lifecycle models are used to select the new optimal design for the product by identifying a plurality of model alternatives for each of the plurality of product lifecycle models, wherein the model alternatives are created, wherein each combination includes a model alternative for each product lifecycle stage, wherein a simulation is generated of each of the plurality of alternative combinations of the model alternatives and the optimal design is selected based on the plurality of simulation results, wherein [0025] teaches a plurality of models are developed for desired key performance indicators including cost and quality for each product lifecycle, wherein the desired KPIs can measure the various aspects of the model, wherein [0027] teaches the alternative spaces represent the various possible combinations of model alternative from different PL stages will be automatically created and the models for each option of each PL stage will be used to simulate each scenario, wherein the multi-objective optimization problem will be carried out in this space to optimize the considered KPIs for the overall PL, accounting for each stage, while adhering to product design constraints, wherein [0029] teaches a score is computer for each alternative path based on the aggregated KPIs over the product lifecycle, wherein the score is a cost function based on the computer KPIs; see also: [0026, 0030]; Examiner’s Note: See the 35 USC 103 combination below for teachings pertaining to the unbolded claim language.); and
organizing a supply chain network around the one or more principal key process indicators target values for each supply chain model ([0010] teaches a plurality of product lifecycle models are used to select the new optimal design for the product by identifying a plurality of model alternatives for each of the plurality of product lifecycle models, wherein the model alternatives are created, wherein each combination includes a model alternative for each product lifecycle stage, wherein a simulation is generated of each of the plurality of alternative combinations of the model alternatives and the optimal design is selected based on the plurality of simulation results, wherein [0025] teaches a plurality of models are developed for desired key performance indicators including cost and quality for each product lifecycle, wherein the desired KPIs can measure the various aspects of the model, wherein [0027] teaches the alternative spaces represent the various possible combinations of model alternative from different PL stages will be automatically created and the models for each option of each PL stage will be used to simulate each scenario, wherein the multi-objective optimization problem will be carried out in this space to optimize the considered KPIs for the overall PL, accounting for each stage, while adhering to product design constraints, wherein [0029] teaches a score is computer for each alternative path based on the aggregated KPIs over the product lifecycle, wherein the score is a cost function based on the computer KPIs, wherein the optimal series of alternatives for design are selected based on their individual scores; see also: [0026, 0030]).
However, Srivastava does not explicitly teach assigning the one or more principal key process indicators to vertices of a performance radar; assigning target values to each of the one or more principal key process indicators on the performance radar.
From the same or similar field of endeavor, Mbaga teaches assigning the one or more principal key process indicators to vertices of a performance radar (Pgs. 395-396 teach results from the benchmarking exercise being presented at a glance through the use of a spider web or radar chart, wherein the spider web diagram shows multiple targets and gaps, and as a result captures the tradeoffs that occur between goals and their achievements, wherein this information is displayed for the various portions of the supply chain in both Oman and Tunisia, wherein Fig. 1 displays the benchmarking results on the coordination of the export SCM practices, wherein Pgs. 401-402 teach Fig. 3 is a spider web or radar chart that presents a visual summary of the eight KPIs of dimension 3, as well as in Pg. 403 teaches the results of the benchmarking exercise are summarized in the radar chart to visualize the multiple targets and gaps; see also: Pgs. 399-400);
assigning target values to each of the one or more principal key process indicators on the performance radar (Pgs. 395-396 teach results from the benchmarking exercise being presented at a glance through the use of a spider web or radar chart, wherein the spider web diagram shows multiple targets and gaps, and as a result captures the tradeoffs that occur between goals and their achievements, wherein this information is displayed for the various portions of the supply chain in both Oman and Tunisia, wherein Fig. 1 displays the benchmarking results on the coordination of the export SCM practices, wherein Pgs. 401-402 teach Fig. 3 is a spider web or radar chart that presents a visual summary of the eight KPIs of dimension 3, as well as in Pg. 403 teaches the results of the benchmarking exercise are summarized in the radar chart to visualize the multiple targets and gaps; see also: Pgs. 397-400).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify Srivastava to incorporate the teachings of Mbaga to include assigning the one or more principal key process indicators to vertices of a performance radar; assigning target values to each of the one or more principal key process indicators on the performance radar. One would have been motivated to do so in order to clearly present and compare results at a glance that shows the multiple targets and gaps (Mbaga, Pg. 395). By incorporating the teachings of Mbaga, one would have been able to visualize the multiple targets and gaps by summarizing the KPIs into a radar chart diagram (Mbaga, Pg. 403).
Regarding claims 8 and 15, the claims recite limitations already addressed by the rejection of claim 1. Regarding claim 8, Srivastava teaches a system for defining one or more supply chain models to support customer business models (Figs. 2-3), comprising: a computer comprising a processor and a memory and configured to ( Fig. 3 and [0032-0033] teach a computer system comprising a processor and memory). Regarding claim 15, Srivastava teaches a non-transitory computer-readable medium embodied with software, the software when executed configured for defining one or more supply chain models to support customer business models by ([0033-0037] teach a computer readable medium with instructions programmed to perform the invention when executed by the processors). Accordingly, the claims are rejected as being unpatentable over the combination of Srivastava in view of Mbaga.
Regarding claims 2, 9, and 16, the combination of Srivastava and Mbaga teaches all the limitations of claims 1, 8, and 15 above.
However, Srivastava does not explicitly teach wherein the target values establish minimums, maximums, or ranges of values for each principal key process indicator for each of the supply chain models.
From the same or similar field of endeavor, Mbaga further teaches wherein the target values establish ranges of values for each principal key process indicator for each of the supply chain models (Pgs. 395-396 teach results from the benchmarking exercise being presented at a glance through the use of a spider web or radar chart, wherein the spider web diagram shows multiple targets and gaps, and as a result captures the tradeoffs that occur between goals and their achievements, wherein this information is displayed for the various portions of the supply chain in both Oman and Tunisia, wherein Pg. 398 teaches the spider web presents a visual graphical summary of the eight KPIs of a given dimension, which provides scores from 0-3, wherein most scores lie between 1-2, wherein Fig. 1 displays the benchmarking results on the coordination of the export SCM practices, wherein Pgs. 401-402 teach Fig. 3 is a spider web or radar chart that presents a visual summary of the eight KPIs of dimension 3, as well as in Pg. 403 teaches the results of the benchmarking exercise are summarized in the radar chart to visualize the multiple targets and gaps; see also: Pgs. 397, 399-400).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the combination Srivastava and Mbaga to incorporate the further teachings of Mbaga to include wherein the target values establish minimums, maximums, or ranges of values for each principal key process indicator for each of the supply chain models. One would have been motivated to do so in order to clearly present and compare results at a glance that shows the multiple targets and gaps (Mbaga, Pg. 395). By incorporating the teachings of Mbaga, one would have been able to visualize the multiple targets and gaps by summarizing the KPIs into a radar chart diagram (Mbaga, Pg. 403).
Regarding claims 3, 10, and 17, the combination of Srivastava and Mbaga teaches all the limitations of claims 1, 8, and 15 above.
However, Srivastava does not explicitly teach wherein the vertices correspond to a polygon.
From the same or similar field of endeavor, Mbaga further teaches wherein the vertices correspond to a polygon (Pgs. 395-396 teach results from the benchmarking exercise being presented at a glance through the use of a spider web or radar chart, wherein the spider web diagram shows multiple targets and gaps, and as a result captures the tradeoffs that occur between goals and their achievements, wherein this information is displayed for the various portions of the supply chain in both Oman and Tunisia, wherein Pg. 398 teaches the spider web presents a visual graphical summary of the eight KPIs of a given dimension, which provides scores from 0-3, wherein most scores lie between 1-2, wherein Fig. 1 displays the benchmarking results on the coordination of the export SCM practices, wherein Pgs. 401-402 teach Fig. 3 is a spider web or radar chart that presents a visual summary of the eight KPIs of dimension 3, as well as in Pg. 403 teaches the results of the benchmarking exercise are summarized in the radar chart to visualize the multiple targets and gaps; see also: Pgs. 397, 399-400; Examiner’s Note: See the polygonal shapes in Figs. 1-3 of Mbaga.).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the combination Srivastava and Mbaga to incorporate the further teachings of Mbaga to include wherein the vertices correspond to a polygon. One would have been motivated to do so in order to clearly present and compare results at a glance that shows the multiple targets and gaps (Mbaga, Pg. 395). By incorporating the teachings of Mbaga, one would have been able to visualize the multiple targets and gaps by summarizing the KPIs into a radar chart diagram (Mbaga, Pg. 403).
Regarding claims 4, 11, and 18, the combination of Srivastava and Mbaga teaches all the limitations of claims 1, 8, and 15 above.
However, Srivastava does not explicitly teach wherein the performance radar represents each supply chain model by graphing polygons inside the performance radar.
From the same or similar field of endeavor, Mbaga further teaches wherein the performance radar represents each supply chain model by graphing polygons inside the performance radar (Pgs. 395-396 teach results from the benchmarking exercise being presented at a glance through the use of a spider web or radar chart, wherein the spider web diagram shows multiple targets and gaps, and as a result captures the tradeoffs that occur between goals and their achievements, wherein this information is displayed for the various portions of the supply chain in both Oman and Tunisia, wherein Pg. 398 teaches the spider web presents a visual graphical summary of the eight KPIs of a given dimension, which provides scores from 0-3, wherein most scores lie between 1-2, wherein Fig. 1 displays the benchmarking results on the coordination of the export SCM practices, wherein Pgs. 401-402 teach Fig. 3 is a spider web or radar chart that presents a visual summary of the eight KPIs of dimension 3, as well as in Pg. 403 teaches the results of the benchmarking exercise are summarized in the radar chart to visualize the multiple targets and gaps; see also: Pgs. 397, 399-400).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the combination Srivastava and Mbaga to incorporate the further teachings of Mbaga to include wherein the performance radar represents each supply chain model by graphing polygons inside the performance radar. One would have been motivated to do so in order to clearly present and compare results at a glance that shows the multiple targets and gaps (Mbaga, Pg. 395). By incorporating the teachings of Mbaga, one would have been able to visualize the multiple targets and gaps by summarizing the KPIs into a radar chart diagram (Mbaga, Pg. 403).
Regarding claims 5, 12, and 19, the combination of Srivastava and Mbaga teaches all the limitations of claims 4, 11, and 18 above.
However, Srivastava does not explicitly teach wherein each polygon sets a boundary for each subsequent value.
From the same or similar field of endeavor, Mbaga further teaches wherein each polygon sets a boundary for each subsequent value. (Pgs. 395-396 teach results from the benchmarking exercise being presented at a glance through the use of a spider web or radar chart, wherein the spider web diagram shows multiple targets and gaps, and as a result captures the tradeoffs that occur between goals and their achievements, wherein this information is displayed for the various portions of the supply chain in both Oman and Tunisia, wherein Pg. 398 teaches the spider web presents a visual graphical summary of the eight KPIs of a given dimension, which provides scores from 0-3, wherein most scores lie between 1-2, wherein Fig. 1 displays the benchmarking results on the coordination of the export SCM practices, wherein Pgs. 401-402 teach Fig. 3 is a spider web or radar chart that presents a visual summary of the eight KPIs of dimension 3, as well as in Pg. 403 teaches the results of the benchmarking exercise are summarized in the radar chart to visualize the multiple targets and gaps; see also: Pgs. 397, 399-400; Examiner’s Note: As can be seen in at least Figs. 1-3 of Mbaga, each shape, here represented as octagons, move outward from the center of the radar chart set a boundary for each subsequent value (i.e. the first octagon value is 1, the second octagon value is 2, and so on, to the outside perimeter of the performance radar, which equals to a value of 3, which is akin to that of paragraph [0106] of the instant application.).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the combination Srivastava and Mbaga to incorporate the further teachings of Mbaga to include wherein each polygon sets a boundary for each subsequent value. One would have been motivated to do so in order to clearly present and compare results at a glance that shows the multiple targets and gaps (Mbaga, Pg. 395). By incorporating the teachings of Mbaga, one would have been able to visualize the multiple targets and gaps by summarizing the KPIs into a radar chart diagram (Mbaga, Pg. 403).
Regarding claims 6, 13, and 20, the combination of Srivastava and Mbaga teaches all the limitations of claims 1, 8, and 15 above.
Srivastava further teaches wherein each assigned name is linked to at least one of the customer business models ([0010] teaches a plurality of product lifecycle models are used to select the new optimal design for the product by identifying a plurality of model alternatives for each of the plurality of product lifecycle models, wherein the model alternatives are created, wherein each combination includes a model alternative for each product lifecycle stage, wherein a simulation is generated of each of the plurality of alternative combinations of the model alternatives and the optimal design is selected based on the plurality of simulation results, wherein [0021] teaches there are several stages associated with a product including design, manufacturing planning, manufacturing execution, supply chain, storage, operations, and recycle/disposal, wherein the number and type of stages is product dependent, and wherein Fig. 1 and [0022] teach each PL stage and the associated information with each stage; see also: [0025-0030]).
Regarding claims 7 and 14, the combination of Srivastava and Mbaga teaches all the limitations of claims 1 and 8 above.
Srivastava further teaches wherein the principal key process indicators are associated with customer preferences ([0014] teaches the optimal design is selected from the pareto-optimal set based on the one or more user defined preferences, as well as in [0025] teaches a plurality of models are developed for desired key performance indicators including cost and quality for each product lifecycle, wherein the desired KPIs can measure the various aspects of the model, wherein [0027] teaches the alternative spaces represent the various possible combinations of model alternative from different PL stages will be automatically created and the models for each option of each PL stage will be used to simulate each scenario, wherein the multi-objective optimization problem will be carried out in this space to optimize the considered KPIs for the overall PL, accounting for each stage, while adhering to product design constraints; see also: [0010, 0022, 0026, 0029-0030]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Ghosh et al. (US 20170372248 A1) discloses a radar chart that depicts the impact of varying priorities and the quality of service rendered for each client
Ebert (US 20050093866 A1) discloses utilizing a radar chart to visualize KPIs
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/SARA GRACE BROWN/Primary Examiner, Art Unit 3625
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