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 .
Drawings
The drawings filed on 8/4/23 are accepted by the examiner.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 8/4/23 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more. The claim(s) recite(s) mental steps involving identifying one or more components of the one or more industrial assets for solid state battery integration based on the simulated performance of the digital twin, wherein the solid state battery integration includes the replacement of the one or more components with a solid state battery or the addition of the solid state battery to the one or more components (claims 1, 8 and 15), ranking the one or more components which may be replaced with the solid state battery using a machine learning based recommendation system (claims 3, 10 and 17), generating 3D printing instructions based on the at least one of the one or more components selected (claims 5, 12 and 19), monitoring a performance of the at least one of the one or more components within an industrial floor (claims 6, 13 and 20), these limitations as described in [0038]-[0040], [0052]-[0053] and [0055] is recited in high level of generality constitutes as a mental process, such as an evaluation or judgement, that can be performed in the human mind and mathematical concepts of generating a digital twin for each of the one or more industrial assets; simulating a performance of the digital twin for each of the one or more industrial assets, the performance of the digital twin is simulated under a plurality of conditions based on data stored in a knowledge corpus and one or more processes identified by a user, the performance of the digital twin is simulated (claims 1-2, 7-9, 14-16), these limitations as described in [0042]-[0048] constitutes details of mathematical calculations of the performance of the digital twin, thus, it falls into the “mathematical concepts” group of abstract ideas see MPEP 2106.04(a)(2).
This judicial exception is not integrated into a practical application because the additional limitations of receiving data for one or more industrial assets; receiving a selection of at least one of the one or more components; receiving a selection of at least one of the one or more components from a user within a component optimization interface; receiving feedback on the at least one of the one or more components from the user within the component optimization interface (claims 1, 5-6, 8, 12-13, 15 and 19-20) represent mere data collection which is an insignificant extrasolution activity. The displaying data to a user within a component optimization interface, one or more processors, one or more computer-readable memories, and one or more computer-readable storage media; program instructions, stored on at least one of the one or more computer-readable storage media for execution by at least one of the one or more processors via at least one of the one or more memories, program instructions, stored on at least one of the one or more computer-readable storage media (claims 4, 8, 10-13, 15, 17, and 19-20) are recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications that they represent no more than mere instructions to apply the judicial exception on a computer. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer. It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of these computer components does not affect this analysis. See MPEP 2106.05(I) for more information on this point, including explanations from judicial decisions including Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 224-26 (2014). Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system (Alice Corp. Pty. Ltd. v. CLS Bank Int’l 573 U.S. __, 134 S. Ct. 2347, 110 U.S.P.Q.2d 1976 (2014)). Accordingly, these additional element does not integrate the abstract idea into a practical application. The “retraining the machine learning based recommendation system based on the performance of and the feedback received for the at least one of the one or more components” (claims 6, 13 and 20) represent mere retraining the machine learning system based on performance and feedback, it is an insignificant extrasolution activity. The “using one or more machine learning model and one or more simulation models” (claims 7 and 14) provide nothing more than mere instructions to implement an abstract idea on a generic computer, see MPEP2106.05(f).
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the insignificant extra-solution activity of data collection is considered well-understood, routine, and conventional, see mpep 2106.05(d), infra applied prior art, references cited. The displaying data to a user within a component optimization interface, one or more processors, one or more computer-readable memories, and one or more computer-readable storage media; program instructions, stored on at least one of the one or more computer-readable storage media for execution by at least one of the one or more processors via at least one of the one or more memories, program instructions, stored on at least one of the one or more computer-readable storage media are recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications, which cannot provide an inventive concept. Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system (Alice Corp. Pty. Ltd. v. CLS Bank Int’l 573 U.S. __, 134 S. Ct. 2347, 110 U.S.P.Q.2d 1976 (2014)). The retraining the machine learning based recommendation system based on the performance of and the feedback received for the at least one of the one or more components is considered well-understood, routine, and conventional, see background section of US20250013913. The additional elements of using one or more machine learning model and one or more simulation models are at best, mere instructions to “apply” the abstract ideas, which cannot provide an inventive concept, and it is therefore well-understood, routine, and conventional, see MPEP2106.05(f).
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation "the replacement of the one or more components" in line 8. There is insufficient antecedent basis for this limitation in the claim.
Claim 1 recites the limitation "the addition of the solid state battery " in line 9. There is insufficient antecedent basis for this limitation in the claim.
Claim 8 recites the limitation "the replacement of the one or more components" in page 2 line 13. There is insufficient antecedent basis for this limitation in the claim.
Claim 8 recites the limitation "the addition of the solid state battery " in page 2 line 14. There is insufficient antecedent basis for this limitation in the claim.
Claim 15 recites the limitation "the replacement of the one or more components" in line 13. There is insufficient antecedent basis for this limitation in the claim.
Claim 15 recites the limitation "the addition of the solid state battery " in line 14. There is insufficient antecedent basis for this limitation in the claim.
Claims 15-20 recite “program instructions, stored on at least one of the one or more computer-readable storage media” to perform varies actions (receiving data, simulate the performance of a digital twin, identify component and replace a battery etc.), it is not clear how mere program instructions stored on the computer readable storage media can perform these steps without the instructions being executed by a processor, therefore, claims 15-20 are indefinite. The examiner suggests adding “program instructions, stored on at least one of the one or more computer-readable storage media, when executed by a/the processor” to perform actions to overcome this particular rejection.
Claims 2-7 and 9-15, included in the statement of rejection but not specifically addressed in the body of the rejection have inherited the deficiency of their parent claim and have not resolved the deficiencies. Therefore, they are rejected based on the same rationale as applied to their parent claim above.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries 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.
Claim(s) 1-2, 7-9 and 14-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over US20250021084 to Sakurai et al. (hereinafter “Sakurai”), in view of WO2022221719 to Cella et al. (hereinafter “Cella”).
As for claim 1, Sakurai substantially discloses a method for battery component identification (Sakurai, see abstract, [0033] and [0036], it is noted that by identifying that a work machine 50 needing a replacement of the battery, the battery component of the work machine must be identified first), the method comprising:
receiving data for one or more industrial assets (Sakurai, see [0025]-[0026]);
generating a digital twin for each of the one or more industrial assets (Sakurai, see Fig. 1 and [0025]-[0026]);
simulating a performance of the digital twin for each of the one or more industrial assets (Sakurai, see abstract, [0025]-[0026] and [0036]); and
identifying one or more components of the one or more industrial assets for battery integration based on the simulated performance of the digital twin, wherein the battery integration includes the replacement of the one or more components with a battery (Sakurai, see abstract, [0025]-[0026] and [0036]).
Sakurai does not explicitly disclose the battery being a solid state battery. However, Cella in an analogous art discloses the battery being a solid state battery (Cella, see [2683]).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate teaching of Cella into the method of Sakurai. The modification would be obvious because one of the ordinary skill in the art would want to allow enterprises not only to obtain data, but to convert the data into insights and to translate the insights into well-informed decisions and timely execution of efficient operations in the field of energy system that includes solid-state batteries (Cella, see [0006] and [2683]).
Claim 8 is an apparatus claim corresponds to the method claim 1, it is therefore rejected under similar reasons set forth in the rejection of claim 1. Sakurai further discloses a computer system comprising: one or more processors, one or more computer-readable memories, and one or more computer-readable storage media (Sakurai, see [0007]);
program instructions, stored on at least one of the one or more computer-readable storage media for execution by at least one of the one or more processors via at least one of the one or more memories to perform steps (Sakurai, see [0007]).
Claim 15 is a computer-readable storage media claim corresponds to the method claim 1, it is therefore rejected under similar reasons set forth in the rejection of claim 1.
As per claim 2, the rejection of claim 1 is incorporated, Cella further discloses the performance of the digital twin is simulated under a plurality of condition based on data stored in a knowledge corpus and one or more processes identified by a user (Cella, see [0254]-[0259]).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate teaching of Cella into the method of Sakurai. The modification would be obvious because one of the ordinary skill in the art would want to allow enterprises not only to obtain data, but to convert the data into insights and to translate the insights into well-informed decisions and timely execution of efficient operations in the field of energy system that includes solid-state batteries (Cella, see [0006] and [2683]).
Claim 9 is an apparatus claim corresponds to the method claim 2, it is therefore rejected under similar reasons set forth in the rejection of claim 2.
Claim 16 is an computer-readable storage media claim corresponds to the method claim 2, it is therefore rejected under similar reasons set forth in the rejection of claim 2.
As per claim 7, the rejection of claim 1 is incorporated, Cella further discloses wherein the performance of the digital twin is simulated using one or more machine learning models and one or more simulation models (Cella, see [0253]-[0254] and [0272]).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate teaching of Cella into the method of Sakurai. The modification would be obvious because one of the ordinary skill in the art would want to allow enterprises not only to obtain data, but to convert the data into insights and to translate the insights into well-informed decisions and timely execution of efficient operations in the field of energy system that includes solid-state batteries (Cella, see [0006] and [2683]).
Claim 14 is an apparatus claim corresponds to the method claim 7, it is therefore rejected under similar reasons set forth in the rejection of claim 7.
Claim(s) 1-2, 7-9 and 14-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sakurai, in view of Cella, further in view of US20210169740 to Janzen et al. (hereinafter “Janzen”).
As per claim 3, the rejection of claim 1 is incorporated, Cella further discloses battery being solid state battery (Cella, see [2683]).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate teaching of Cella into the method of Sakurai. The modification would be obvious because one of the ordinary skill in the art would want to allow enterprises not only to obtain data, but to convert the data into insights and to translate the insights into well-informed decisions and timely execution of efficient operations in the field of energy system that includes solid-state batteries (Cella, see [0006] and [2683]).
The combination of Sakurai and Cella does not explicitly disclose ranking the one or more components which may be replaced with the battery using a machine learning based recommendation system. However, Janzen in an analogous art discloses ranking the one or more components which may be replaced with the battery using a machine learning based recommendation system (Janzen, see [0052]-[0054], “score” can be interpreted as ranking as claimed).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate teaching of Janzen into the above combination of Sakurai and Cella. The modification would be obvious because one of the ordinary skill in the art would want to achieve predictable results of cost reduction by using machine learning based recommendation system.
As per claim 4, the rejection of claim 3 is incorporated, Cella further discloses the output the machine learning system is displayed to a user within a component optimization interface (Cella, see [2349]-[2353]).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate teaching of Cella into the method of Sakurai. The modification would be obvious because one of the ordinary skill in the art would want to allow enterprises not only to obtain data, but to convert the data into insights and to translate the insights into well-informed decisions and timely execution of efficient operations in the field of energy system that includes solid-state batteries (Cella, see [0006] and [2683]).
Janzen further discloses the ranking of the one or more components (Janzen, see [0052]-[0054]).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate teaching of Janzen into the above combination of Sakurai and Cella. The modification would be obvious because one of the ordinary skill in the art would want to achieve predictable results of cost reduction by using machine learning based recommendation system.
As per claim 5, the rejection of claim 3 is incorporated, Cella further discloses receiving a selection of at least one of the one or more components and generating 3D printing instructions based on the at least one of the one or more component (Cella, see [1325]-[1327]).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate teaching of Cella into the method of Sakurai. The modification would be obvious because one of the ordinary skill in the art would want to allow enterprises not only to obtain data, but to convert the data into insights and to translate the insights into well-informed decisions and timely execution of efficient operations (Cella, see [0006] and [2683]).
As per claim 6, the rejection of claim 3 is incorporated, Cella further discloses receiving a selection of at least one of the one or more components from a user within a component optimization interface (Cella, see [0651]-[0652]); monitoring a performance of the at least one of the one or more components within an industrial floor (Cella, see [0651]-[0652] and [0771]-[0774]); receiving feedback on the at least one of the one or more components from the user within the component optimization interface (Cella, see [0651]-[0656]); and retraining the machine learning based recommendation system based on the performance of and the feedback received for the at least one of the one or more components (Cella, see [0651]-[0656]).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate teaching of Cella into the method of Sakurai. The modification would be obvious because one of the ordinary skill in the art would want to allow enterprises not only to obtain data, but to convert the data into insights and to translate the insights into well-informed decisions and timely execution of efficient operations (Cella, see [0006] and [2683]).
Claims 10-13 are system claims correspond to the method claims 3-6, respectively, they are therefore rejected under similar reasons set forth in the rejections of claims 3-6.
Claims 17-20 are computer readable medium claims correspond to the method claims 3-6, respectively, they are therefore rejected under similar reasons set forth in the rejections of claims 3-6.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
US20240370000 discloses an intelligent scheduling method and system. The intelligent scheduling method includes the following steps. A work order assignment module is used to assign multiple work orders to one of multiple production lines respectively. A work order form batching module is used to perform a form batch for the work orders assigned to each production line, so that the work orders are divided into multiple work order groups. A work order detailed scheduling module is used to solve for each work order included in each batch of each production line to obtain a schedule plan, wherein the schedule plan includes an assigned production line of each work order and an operation sequence. The schedule plan is sent to an output device.
US20070198135 discloses the actual performance of the production system is compared to a planned level of performance of the production system. One or more short-term production constraints in the production system are identified in response to the actual performance being more than a threshold value away from the planned level of performance. A corrective action for the production system is determined to mitigate one or more of the short-term production constraints. The corrective action is applied to the production system.
US20200103469 discloses a charging method and apparatus which is optimized based on an electrochemical model, the charging method includes estimating an internal state of a battery, determining a charging limitation condition corresponding to a plurality of charging areas based on the internal state, and charging the battery based on the charging limitation condition.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JASON LIN whose telephone number is (571)270-3175. The examiner can normally be reached on Monday-Friday 9:30 a.m. – 6:00 p.m. PST.
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/JASON LIN/
Primary Examiner, Art Unit 2117