DETAILED ACTION
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 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 an abstract idea without significantly more.
Claim 1 is directed towards the four statutory categories in that it recites a method. The claim(s) recite(s) generating, with the analysis model, a predicted power consumption of the chiller system; and comparing the predicted power consumption to the measured power consumption. These limitations, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than the analysis model being claimed as performing the function of generating a predicted power consumption of the chiller system, nothing in the claim element precludes the step from practically being performed in the mind. Without any specific limitation narrowing the process of generating a predicted power consumption of the chiller system, a human mind mentally or with pen and paper is capable of performing the function of generating a predicted power consumption of the chiller system. Reciting an analysis model as a tool to perform the process does not overcome the mental process nature of the limitation (see MPEP 2106.04(a)(2)). Similarly, a human mind mentally or with pen and paper is capable of comparing the predicted power consumption to the measured power consumption. Thus, the claim recites a mental process.
This judicial exception is not integrated into a practical application. Claim recites additional elements directed to chilling, with a chiller system, a load associated with a semiconductor fabrication facility; receiving, with a control system associated with the chiller system, a measured power consumption of the chiller system; providing, to an analysis model of the control system, a plurality of operating parameters associated with the chiller system. Limitation directed to a chiller system, is directed to using the abstract idea in the field of use or technological environment of chillers associated with fabrication facility. This limitation does not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use, therefore it fails to integrate the judicial exception into a practical application (see MPEP 2106.05(h)). Limitation directed to receiving… a measured power consumption and providing,… a plurality of operating parameters are directed to mere data gathering and outputting, which are insignificant extra solution activities for the purpose of executing the abstract idea. Therefore, these limitations do not integrate a judicial exception into a practical application. (see MPEP 2106.05(g)).
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Claim recites additional elements directed to chilling, with a chiller system, a load associated with a semiconductor fabrication facility; receiving, with a control system associated with the chiller system, a measured power consumption of the chiller system; providing, to an analysis model of the control system, a plurality of operating parameters associated with the chiller system. Limitation directed to a chiller system, is directed to using the abstract idea in the field of use or technological environment of chillers associated with fabrication facility. This limitation does not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use, therefore it fails to integrate the judicial exception into a practical application (see MPEP 2106.05(h)). Limitation directed to receiving… a measured power consumption and providing,… a plurality of operating parameters, are directed to mere data gathering and outputting. These elements are recited in a generic manner and are directed to activity that are well-understood, routine and conventional in the field of computer implemented processes. Courts have found receiving or transmitting data over a network (Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 and buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014)) to be well‐understood, routine, and conventional when recited as insignificant extra-solution activity (see MPEP 2106.05(d). Therefore, these limitations do not provide significantly more than the judicial exception. (see MPEP 2106.05(d)).
Claim 2 depends on claim 1 therefore it recites the abstract idea of claim 1. Claim 2 further recites, “outputting, with the control system, an alert if the predicted power consumption is different from the measured power consumption by more than a threshold difference.” Determining whether a predicted power consumption is different than the measured power consumption by more than a threshold difference is a function that can be practically performed by human. Other than the control system being claimed as performing the function, nothing in the claim element precludes the step from practically being performed in the mind. Therefore it recites a mental process. Merely outputting an alert based on the determination of predicted power consumption being different than the measured power consumption is directed to data outputting, which is an insignificant extra solution activities for the purpose of executing the abstract idea. Therefore, it does not integrate a judicial exception into a practical application. (see MPEP 2106.05(g)). This element is recited in a generic manner and are directed to activity that are well-understood, routine and conventional in the field of computer implemented processes. Courts have found receiving or transmitting data over a network (Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 and buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014)) to be well‐understood, routine, and conventional when recited as insignificant extra-solution activity (see MPEP 2106.05(d). Therefore, these limitations do not provide significantly more than the judicial exception. (see MPEP 2106.05(d)).
Claim 3 depends on claim 2 therefore it recites the abstract idea of claim 2. Claim 3 further recites, wherein the alert indicates that maintenance should be performed on one or more components of the chiller system. This limitation merely attempts to link the judicial exception regarding the alert to a field of use of chiller system. Limitation that does not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use, fails to integrate the judicial exception into a practical application or provide significantly more (see MPEP 2106.05(h)).
Claim 4 depends on claim 2 therefore it recites the abstract idea of claim 2. Claim 4 further recites, wherein the alert indicates that maintenance should be performed on a sensor associated with the chiller system. This limitation merely attempts to link the judicial exception regarding the alert to a field of use of chiller system. Limitation that does not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use, fails to integrate the judicial exception into a practical application or provide significantly more (see MPEP 2106.05(h)).
Claim 5 depends on claim 1 therefore it recites the abstract idea of claim 1. Claim 5 further recites, wherein the input parameters include one or more of a refrigeration ton of the chiller system; a refrigerant fluid evaporation pressure, a refrigerant fluid condensing pressure; and a power consumption of a compressor of the chiller system. This limitation is directed to narrowing the parameters gathered in claim 1 to specific parameter. Merely limiting the parameters gathered to be used in the mental process to specific parameters related to a technological environment, does not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use, and therefore fails to integrate the judicial exception into a practical application or provide significantly more (see MPEP 2106.05(h)).
Claim 6 depends on claim 1 therefore it recites the abstract idea of claim 1. Claim 6 further recites, wherein the analysis model includes a polynomial regression model. This limitation merely links the analysis model to a polynomial regression model. Merely limiting the model used in the mental process to a specific model, does not amount to more than generally linking the use of a judicial exception to a particular technological environment of statistical modeling, and therefore fails to integrate the judicial exception into a practical application or provide significantly more (see MPEP 2106.05(h)).
Claim 7 depends on claim 1 therefore it recites the abstract idea of claim 1. Claim 7 further recites, wherein the polynomial regression model has a degree of two or higher. This limitation merely links the analysis model to a polynomial regression model. Merely limiting the model used in the mental process to a specific model, does not amount to more than generally linking the use of a judicial exception to a particular technological environment of statistical modeling, and therefore fails to integrate the judicial exception into a practical application or provide significantly more (see MPEP 2106.05(h)).
Claim 8 is directed towards the four statutory categories in that it recites a system/machine. The claim(s) recite(s) determining, with the analysis model based on the input parameters, a number of the plurality of chiller systems to utilize in cooling the load. These limitations, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than the analysis model being claimed as performing the function of determining , a number of the plurality of chiller systems to utilize in cooling the load, nothing in the claim element precludes the step from practically being performed in the mind. Without any specific limitation narrowing the process, a human mind mentally or with pen and paper is capable of performing the function of determining , a number of the plurality of chiller systems to utilize in cooling the load. Reciting an analysis model as a tool to perform the process does not overcome the mental process nature of the limitation (see MPEP 2106.04(a)(2)). Thus, the claim recites a mental process.
This judicial exception is not integrated into a practical application. Claim recites additional elements directed to a plurality of chiller systems each configured to be selectively activated for cooling a load; a control system communicatively coupled to the plurality of chiller systems and including: one or more computer memories configured to store software instructions; one or more processors configured to execute the software instructions, wherein executing the software instructions performs a method comprising: receiving, at an analysis model of the control system, input parameters associated with the plurality of chiller systems; processing the input parameters with the analysis model; and. Limitation directed to a chiller system, is directed to using the abstract idea in the field of use or technological environment of chillers associated with fabrication facility. This limitation does not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use, therefore it fails to integrate the judicial exception into a practical application (see MPEP 2106.05(h)). Limitation directed to receiving, at an analysis model of the control system, input parameters associated with the plurality of chiller systems , is directed to mere data gathering, which are insignificant extra solution activities for the purpose of executing the abstract idea. Therefore, these limitations do not integrate a judicial exception into a practical application. (see MPEP 2106.05(g)). Limitations directed to “a control system communicatively coupled to the plurality of chiller systems and including: one or more computer memories configured to store software instructions; one or more processors configured to execute the software instructions”, amounts to simply adding a general purpose computer or computer components after the fact to an abstract idea and does not integrate a judicial exception into a practical application (see MPEP 2106.05(f)(2)). Limitation directed to “processing the input parameters with the analysis model” attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". (see MPEP 2106.05(f)(1))
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Claim recites additional elements directed to a plurality of chiller systems each configured to be selectively activated for cooling a load; a control system communicatively coupled to the plurality of chiller systems and including: one or more computer memories configured to store software instructions; one or more processors configured to execute the software instructions, wherein executing the software instructions performs a method comprising: receiving, at an analysis model of the control system, input parameters associated with the plurality of chiller systems; processing the input parameters with the analysis model; and. Limitation directed to a chiller system, is directed to using the abstract idea in the field of use or technological environment of chillers associated with fabrication facility. This limitation does not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use, therefore it fails to provide significantly more than the judicial exception(see MPEP 2106.05(h)). Limitation directed to receiving, at an analysis model of the control system, input parameters associated with the plurality of chiller systems , is directed to mere data gathering, which are insignificant extra solution activities for the purpose of executing the abstract idea. These elements are recited in a generic manner and are directed to activity that are well-understood, routine and conventional in the field of computer implemented processes. Courts have found receiving or transmitting data over a network (Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 and buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014)) to be well‐understood, routine, and conventional when recited as insignificant extra-solution activity (see MPEP 2106.05(d). Therefore, these limitations do not provide significantly more than the judicial exception. (see MPEP 2106.05(d)). Limitations directed to “a control system communicatively coupled to the plurality of chiller systems and including: one or more computer memories configured to store software instructions; one or more processors configured to execute the software instructions”, amounts to simply adding a general purpose computer or computer components after the fact to an abstract idea and does not provide significantly more than the judicial exception (see MPEP 2106.05(f)(2)). Limitation directed to “processing the input parameters with the analysis model” attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not provide significantly more because this type of recitation is equivalent to the words "apply it". (see MPEP 2106.05(f)(1))
Claim 9 depends on claim 8 therefore it recites the abstract idea of claim 8. Claim 9 further recites, wherein the analysis model includes a neural network trained with a machine learning process to generate a predicted power consumption for each number of chiller systems. This limitation fails to provide any details regarding how the neural network is trained or how it is used in generating a predicted power consumption. A limitation that attempts to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate the judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". (see MPEP 2106.05(f)(1))
Claim 10 depends on claim 8 therefore it recites the abstract idea of claim 8. Claim 10 further recites, wherein determining the number of the plurality of chiller systems to utilize includes selecting the number of chiller systems that results in the lowest predicted power consumption. This limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. Without any specific limitation narrowing the process, a human mind mentally or with pen and paper is capable of performing the function of, determining the number of the plurality of chiller systems to utilize includes selecting the number of chiller systems that results in the lowest predicted power consumption. Thus, the claim recites a mental process.
Claim 11 depends on claim 8 therefore it recites the abstract idea of claim 8. Claim 11 further recites, wherein the analysis model includes a decision tree model coupled to the neural network model. This limitation merely links the analysis model to a decision tree model. Merely limiting the model used in the mental process to a specific model, does not amount to more than generally linking the use of a judicial exception to a particular technological environment of statistical modeling, and therefore fails to integrate the judicial exception into a practical application or provide significantly more (see MPEP 2106.05(h)).
Claim 12 depends on claim 8 therefore it recites the abstract idea of claim 8. Claim 12 further recites, wherein the analysis model is configured to generate a predicted average load current for each number of chiller systems. This limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. Without any specific limitation narrowing the process, a human mind mentally or with pen and paper is capable of performing the function of, generating a predicted average load current for each number of chiller systems. Thus, the claim recites a mental process.
Claim 13 depends on claim 8 therefore it recites the abstract idea of claim 8. Claim 13 further recites, wherein determining the number of the plurality of chiller systems to utilize includes selecting the number of chiller systems that results in the lowest predicted average load current. This limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. Without any specific limitation narrowing the process, a human mind mentally or with pen and paper is capable of performing the function of, electing the number of chiller systems that results in the lowest predicted average load current. Thus, the claim recites a mental process.
Claim 14 depends on claim 8 therefore it recites the abstract idea of claim 8. Claim 14 further recites, wherein the analysis model includes a linear regression model configured to generate the predicted average load current. This limitation merely links the analysis model to a linear regression model. Merely limiting the model used in the mental process to a specific model, does not amount to more than generally linking the use of a judicial exception to a particular technological environment of statistical modeling, and therefore fails to integrate the judicial exception into a practical application or provide significantly more (see MPEP 2106.05(h)).
Claim 15 depends on claim 8 therefore it recites the abstract idea of claim 8. Claim 15 further recites, wherein the analysis model includes: a neural network trained with a machine learning process to generate a predicted power consumption for each number of chiller systems; and a linear regression model configured to generate a predicted average load current for each number of chiller systems. Limitation regarding generating a predicted power consumption for each number of chiller systems fails to provide any details regarding how the neural network is trained or how it is used in generating a predicted power consumption. A limitation that attempts to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate the judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". (see MPEP 2106.05(f)(1)). Limitation directed to generating a predicted average load current, merely links the analysis model to a linear regression model. Merely limiting the model used in the mental process to a specific model, does not amount to more than generally linking the use of a judicial exception to a particular technological environment of statistical modeling, and therefore fails to integrate the judicial exception into a practical application or provide significantly more (see MPEP 2106.05(h)).
Claim 16 depends on claim 8 therefore it recites the abstract idea of claim 8. Claim 16 further recites, wherein the method includes determining the number of the plurality of chiller systems to utilize in cooling the load based on the predicted power consumption for each number of chiller systems and the predicted average load current each number of chiller systems. This limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. Without any specific limitation narrowing the process, a human mind mentally or with pen and paper is capable of performing the function of, determining the number of the plurality of chiller systems to utilize in cooling the load based on the predicted power consumption for each number of chiller systems and the predicted average load current each number of chiller systems. Thus, the claim recites a mental process.
Claim 17 is directed towards the four statutory categories in that it recites a method. The claim(s) recite(s) generating, with the analysis model, operating parameter adjustments for reducing power consumption of the chiller system. These limitations, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than the analysis model being claimed as performing the function of, generating, operating parameter adjustments for reducing power consumption of the chiller system, nothing in the claim element precludes the step from practically being performed in the mind. Without any specific limitation narrowing the process, a human mind mentally or with pen and paper is capable of performing the function of, generating, operating parameter adjustments for reducing power consumption of the chiller system. Reciting an analysis model as a tool to perform the process does not overcome the mental process nature of the limitation (see MPEP 2106.04(a)(2)). Similarly, a human mind mentally or with pen and paper is capable of comparing the predicted power consumption to the measured power consumption. Thus, the claim recites a mental process.
This judicial exception is not integrated into a practical application. Claim recites additional elements directed to chilling, with a water chiller system, a load associated with a semiconductor fabrication facility; providing, to an analysis model of a control system, a plurality of operating parameters associated with the chiller system. Limitation directed to a chiller system, is directed to using the abstract idea in the field of use or technological environment of chillers associated with fabrication facility. This limitation does not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use, therefore it fails to integrate the judicial exception into a practical application (see MPEP 2106.05(h)). Limitation directed to providing, to an analysis model of a control system, a plurality of operating parameters associated with the chiller system, is directed to mere data gathering and outputting, which are insignificant extra solution activities for the purpose of executing the abstract idea. Therefore, these limitations do not integrate a judicial exception into a practical application. (see MPEP 2106.05(g)).
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Claim recites additional elements directed to chilling, with a water chiller system, a load associated with a semiconductor fabrication facility; providing, to an analysis model of a control system, a plurality of operating parameters associated with the chiller system. Limitation directed to a chiller system, is directed to using the abstract idea in the field of use or technological environment of chillers associated with fabrication facility. This limitation does not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use, therefore it fails to provide significantly more than the judicial exception (see MPEP 2106.05(h)). Limitation directed to providing, to an analysis model of a control system, a plurality of operating parameters associated with the chiller system, is directed to mere data gathering and outputting. These elements are recited in a generic manner and are directed to activity that are well-understood, routine and conventional in the field of computer implemented processes. Courts have found receiving or transmitting data over a network (Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 and buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014)) to be well‐understood, routine, and conventional when recited as insignificant extra-solution activity (see MPEP 2106.05(d). Therefore, these limitations do not provide significantly more than the judicial exception. (see MPEP 2106.05(d)).
Claim 18 depends on claim 17 therefore it recites the abstract idea of claim 17. Claim 18 further recites, comprising training the analysis model with a machine learning process. This limitation fails to provide any details regarding how the analysis model is trained. A limitation that attempts to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate the judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". (see MPEP 2106.05(f)(1))
Claim 19 depends on claim 17 therefore it recites the abstract idea of claim 17. Claim 19 further recites, generating, with the analysis model, a first predicted power consumption of the chiller system based on the input parameters; adjusting, with the analysis model, values of the input parameters; generating, with the analysis model, a second predicted power consumption of the chiller system based on the adjust values; and generating the operating parameter adjustments based on the second predicted power consumption. These limitations, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than the analysis model being claimed as performing the function of, generating.., a first predicted power consumption of the chiller system based on the input parameters; adjusting…, values of the input parameters; generating…, a second predicted power consumption of the chiller system based on the adjust values; and generating the operating parameter adjustments based on the second predicted power consumption, nothing in the claim element precludes the step from practically being performed in the mind. Without any specific limitation narrowing the process, a human mind mentally or with pen and paper is capable of performing the function of, generating a first predicted power consumption of the chiller system based on the input parameters; adjusting values of the input parameters; generating a second predicted power consumption of the chiller system based on the adjust values; and generating the operating parameter adjustments based on the second predicted power consumption. Reciting an analysis model as a tool to perform the process does not overcome the mental process nature of the limitation (see MPEP 2106.04(a)(2)). Similarly, a human mind mentally or with pen and paper is capable of comparing the predicted power consumption to the measured power consumption. Thus, the claim recites a mental process.
Claim 20 depends on claim 17 therefore it recites the abstract idea of claim 17. Claim 20 further recites, wherein the operating parameter adjustments include a pressure difference adjustment for a chilled water pipe of the chiller system. This limitation merely attempts to link the judicial exception regarding the alert to a field of use of chiller system. Limitation that does not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use, fails to integrate the judicial exception into a practical application or provide significantly more (see MPEP 2106.05(h)).
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.
Claim 5 is 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 5 recites “The method of claim 2, wherein the input parameters include one or more of:” in the preamble. However there is no recitation of a input parameter in any of the claims this claims depends on. Therefore, there is insufficient antecedent basis for this limitation in the claim. For the sake of compact prosecution the limitation is being interpreted to recite “operating parameters”.
Claim Rejections - 35 USC § 102
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 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.
Claim(s) 8 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Asmus (US20130345880A1)
Regarding claim 8,
Asmus teaches, A system, comprising:
a plurality of chiller systems each configured to be selectively activated for cooling a load; (¶0028-¶0029 teaches, Chiller plant subsystems 130 are illustrated to include a plurality of chillers 132)
a control system communicatively coupled to the plurality of chiller systems and including: (¶0028-¶0029 teaches, chiller plant controller 102)
one or more computer memories configured to store software instructions; (¶0032 teaches, Chiller plant controller 102 includes memory 108 is communicably connected to processor 106 via processing circuit 104 and includes computer code for executing (e.g., by processing circuit 104 and/or processor 106) one or more processes)
one or more processors configured to execute the software instructions, (¶0032 teaches, Chiller plant controller 102 to processor 106 configured to execute computer code)
wherein executing the software instructions performs a method comprising:
receiving, at an analysis model of the control system, input parameters associated with the plurality of chiller systems; (¶0050 teaches chiller plant controller 102 receives operating conditions about the chiller plant devices)
processing the input parameters with the analysis model; and (¶0052 teaches, Step 302 may utilize binary optimization to determine one or more feasible combinations of devices that will satisfy the plant load at a time and for an actual or expected set of conditions (e.g., load conditions, weather conditions, etc.)
determining, with the analysis model based on the input parameters, a number of the plurality of chiller systems to utilize in cooling the load. (¶0052 teaches, determine one or more feasible combinations of devices that will satisfy the plant load)
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.
Claim(s) 1-2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee (US20160103475A1) in view of Seki (US20200132344A1)
Regarding claim 1,
Lee teaches, A method, comprising:
receiving, with a control system associated with the chiller system, a measured power consumption of the chiller system; (¶0215 teaches, receiving an actually measured amount of power consumed by the facility through the data collection module 121. ¶0264 teaches facility includes a chiller.)
providing, to an analysis model of the control system, a plurality of operating parameters associated with the chiller system; (¶0303 teaches, The system setting module 122 may supply information of facilities, to the energy use amount simulation module 123. ¶0304 teaches, The information of the facilities may be information necessary for modeling the facilities and may include specifications of the facilities such as configurations, capacities, kinds, and/or the like of the facilities. ¶0264 teaches facility includes a chiller.)
generating, with the analysis model, a predicted power consumption of the chiller system; and (¶0305 teaches, in operation S30 the energy use amount simulation module 123 may model the at least one facility, based on the information of the at least one facility and may simulate the consumption power of the modeled at least one facility that operates according to the control scenario.)
comparing the predicted power consumption to the measured power consumption. (¶0361 teaches, operation S62 of determining whether a difference between the actual measurement consumption amount and the prediction use amount is out of a predetermined range)
Lee doesn’t teach, chilling, with a chiller system, a load associated with a semiconductor fabrication facility; (Seki in ¶0043 teaches a chiller system being used in a semiconductor manufacturing apparatus involving plasma etching as described later, and is configured to perform control so as to maintain, for example, a temperature of a semiconductor wafer)
Seki is an art in the area of interest as it teaches a chiller device 100 is used for, for example, a semiconductor manufacturing apparatus. A combination of Seki with Lee would allow the system to be used in a chiller system associated with a semiconductor fabrication facility. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the teaching of Seki with Lee. One would have been motivated to do so because doing so would allow the system to maintain a temperature of a semiconductor wafer to a constant temperature in the plurality of steps of fabrication as taught by Seki in ¶0043.
Regarding claim 2,
Lee and Seki teaches, The method of claim 1, comprising outputting, with the control system, an alert if the predicted power consumption is different from the measured power consumption by more than a threshold difference. (Lee in ¶0361 teaches, operation S62 of determining whether a difference between the actual measurement consumption amount and the prediction use amount is out of a predetermined range and operation S63 of displaying alarm on the screen when the difference between the actual measurement consumption amount and the prediction use amount is out of the predetermined range)
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee (US20160103475A1) in view of Seki (US20200132344A1) and further in view of Subbloie (US20210173358A1)
Regarding claim 3,
Lee and Seki doesn’t teach, The method of claim 2, wherein the alert indicates that maintenance should be performed on one or more components of the chiller system. (Subbloie in ¶0123 teaches, The measured actual power usage is then compared to the expected power usage signature 408 and a determination is made if the measured usage exceeds the threshold deviation value 410. ¶0124 teaches, If, however, it is determined that the measured power usage does exceed the threshold deviation, the system will move to generate and alert 412. ¶0125 teaches, the alert could comprise a text or email message to maintenance personnel that the system needs to be checked)
Subbloie is an art in the area of interest as it relates to monitoring power consumption. Lee already teaches, displaying alarm on the screen when the difference between the actual measurement consumption amount and the prediction use amount is out of the predetermined range (see Lee ¶0361). However it doesn’t teach, the alarm to indicate a maintenance should be performed. Subbloie teaches an alert which comprises a message that the system needs to be checked, when the measured power usage exceeds expected power usage. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the teaching of Subbloie with Lee and Seki to include an indication in the alert that the maintenance should be performed . One would have been motivated to do so because doing so would allow the system to notify a service personnel of potential problems with the equipment that needs to be checked and serviced, as taught by Subbloie in ¶0125.
Claim(s) 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee (US20160103475A1) in view of Seki (US20200132344A1) and further in view of Pedder (US20230341827A1)
Regarding claim 4,
Lee and Seki doesn’t teach, The method of claim 2, wherein the alert indicates that maintenance should be performed on a sensor associated with the chiller system. (Pedder in ¶0079 teaches, A deviation condition may be detected based on excessive deviation from the expected (or reference) behavior. ¶0121 teaches the control unit may determine which of the sensors generated the sensors on which the deviating monitored values and/or variations may be based, and may flag these sensors. Furthermore, the control unit may estimate a cause of the deviation condition based at least in part on sensor measurements generated by these particular sensors. If the estimated cause may be a malfunctioning sensor, then the control unit may flag that sensor for repair or replacement, notify the operator, substitute the sensor, or the like.)
Pedder is an art in the area of interest as it teaches, determining sensor malfunction (¶0121). Lee already teaches, displaying alarm on the screen when the difference between the actual measurement consumption amount and the prediction use amount is out of the predetermined range (see Lee ¶0361). However it doesn’t teach, the alarm to indicate a maintenance should be performed on a sensor. Pedder in ¶0079 and ¶0121 teaches determining deviation is caused by sensor fault and notifying the operator. A combination of Pedder with Lee and Seki would allow the system to determine sensor as cause of the difference between actual measurement consumption amount and the prediction use amount and issuing an alert regarding sensor maintenance. One would have been motivated to combine the teaching of Pedder with Lee and Seki because doing so would allow flagging the sensor for replacement, as taught by Pedder in ¶0141.
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee (US20160103475A1) in view of Seki (US20200132344A1) and further in view of Wenzel (US20230350365A1)
Regarding claim 5,
Lee and Seki doesn’t teach, The method of claim 2, wherein the input parameters include one or more a refrigeration ton of the chiller system; a refrigerant fluid evaporation pressure, a refrigerant fluid condensing pressure; and a power consumption of a compressor of the chiller system. (Wenzel in ¶0144 teaches, parameter related to equipment includes expresses the capacity (e.g., in tons).)
Wenzel is an art in the area of interest as it relates to a chiller (¶0010). A combination of Wenzel with Lee and Seki would allow the information of the facilities to include refrigeration ton. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the teaching of Wenzel with Lee and Seki. Lee in already teaches, information necessary for modeling the facilities include capacities. However it doesn’t teach the information to include capacity in tons. Wenzel teaches, parameter related to chiller equipment includes capacity in tons. One of ordinary skill in the art could substitute the capacity in Lee with capacity in tons as taught by Wenzel. The simple substitution of one known element for another producing a predictable result renders the claim obvious.
Claim(s) 6-7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee (US20160103475A1) in view of Seki (US20200132344A1) and further in view of Madhusudanan (A MACHINE LEARNING FRAMEWORK FOR ENERGY CONSUMPTION PREDICTION)
Regarding claim 6,
Lee and Seki doesn’t teach, The method of claim 1, wherein the analysis model includes a polynomial regression model. (Madhusudanan in Page 25 section 3. METHODS teaches, statistical regression modelling for energy consumption forecasting. Page 48 section 4.6. MODULES USED teaches, using Polynomial Regression)
Madhusudanan is an art in the area of interest as it teaches energy consumption forecasting. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the teaching of Madhusudanan with Lee and Seki in order to use polynomial regression model to predict power consumption. One would have been motivated to do so because it was found that second degree polynomial had the least deviation (as taught by Madhusudanan in Page 49 section 4.6. MODULES USED and polynomial regression performs better in determining expected energy consumption as taught by Madhusudanan in Page iii section ABSTRACT.
Regarding claim 7,
Lee, Seki and Madhusudanan teaches, The method of claim 6, wherein the polynomial regression model has a degree of two or higher. (Madhusudanan in Page 25 section 3. METHODS teaches, statistical regression modelling for energy consumption forecasting. Page 48-49 section 4.6. MODULES USED teaches, using second degree polynomial Regression)
Claim(s) 9-11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Asmus (US20130345880A1) in view of Moon (Hybrid Short-Term Load Forecasting Scheme Using Random Forest and Multilayer Perceptron)
Regarding claim 9,
Asmus doesn’t teach, The system of claim 8, wherein the analysis model includes a neural network trained with a machine learning process to generate a predicted power consumption for each number of chiller systems. (Moon in Abstract teaches a hybrid short-term load forecast model to predict power consumption. Page 7-8 section Building a Hybrid Forecasting Model teaches using an artificial neural network to build the hybrid model.)
Moon is an art in the area of interest as teaches a model to predict power consumption (Abstract). A combination of Moon with Asmus would allow the system to use neural network trained with a machine learning process to generate a predicted power consumption. Asmus in ¶0060 already teaches, estimating power consumption of chillers. However it doesn’t teach using a neural network to generate the estimated power consumption. Moon teaches using a neural network to generate the estimated power consumption. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the teaching of Moon with Asmus, and use a neural network to estimate power consumption. One would have been motivated to do so because an hybrid model with neural network is able to provide good performance in predictions regardless of diverse external factors, as taught by Moon in Page 15 section 5.3.ComparisonofForecastingTechniques)
Regarding claim 10,
Asmus and Moon teaches, The system of claim 9, wherein determining the number of the plurality of chiller systems to utilize includes selecting the number of chiller systems that results in the lowest predicted power consumption. (Asmus in ¶0061 teaches, turning on the devices of the combination with optimum energy consumption (310). According to an exemplary embodiment, the optimum energy consumption is the lowest energy consumption for devices that will meet the plant load and satisfy constraints on the system)
Regarding claim 11,
Asmus and Moon teaches, The system of claim 9, wherein the analysis model includes a decision tree model coupled to the neural network model. (Moon in Abstract teaches a hybrid short-term load forecast model to predict power consumption. Page 7-8 section Building a Hybrid Forecasting Model teaches using an artificial neural network and a decision tree model to build the hybrid model.)
Claim(s) 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Asmus (US20130345880A1) in view of Estelle (US20220373614A1)
Regarding claim 12,
Asmus doesn’t teach, The system of claim 8, wherein the analysis model is configured to generate a predicted average load current for each number of chiller systems. (Estelle in ¶0078 teaches determining a predicted current or voltage measurement)
Estelle is an art in the area of interest as it teaches, predicting current measurement. A combination of Estelle with Asmus would teach generating a predicted average load current for each number of chiller systems. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the teaching of Estelle with Asmus. One would have been motivated to do so because doing so would allow the system to identify fault conditions relating to excessive, insufficient, or absent current.
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Asmus (US20130345880A1) in view of Estelle (US20220373614A1) and further in view of Wallace (US20200408447A1)
Regarding claim 13,
Asmus and Estelle doesn’t teach, The system of claim 12, wherein determining the number of the plurality of chiller systems to utilize includes selecting the number of chiller systems that results in the lowest predicted average load current. (Wallace in ¶0124 teaches, power consumption formula which shows that power consumption has a linear relationship with current. Asmus in ¶0061 already teaches, selecting a chiller with lowest energy consumption. A combination of Asmus’s teaching of selecting chiller with lowest energy consumption and Wallace’s teaching regarding the linear relationship between power consumption and current, would teach selecting chiller with lowest load current.)
Wallace is an art in the area of interest as it teaches a relationship between power consumption and current (see ¶0124). A combination of Asmus and Estelle’s teaching of selecting chiller with lowest energy consumption and Wallace’s teaching regarding the linear relationship between power consumption and current, would teach selecting chiller with lowest load current. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the teaching of Wallace with Asmus and Estelle since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 14,
Asmus, Estelle and Wallace teaches, The system of claim 13, wherein the analysis model includes a linear regression model configured to generate the predicted average load current. (Estelle in ¶0062 teaches predictive analyses include linear regression)
Claim(s) 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Asmus (US20130345880A1) in view of Moon (Hybrid Short-Term Load Forecasting Scheme Using Random Forest and Multilayer Perceptron) and further in view of Estelle (US20220373614A1)
Regarding claim 15,
Asmus doesn’t teach, The system of claim 8, wherein the analysis model includes: a neural network trained with a machine learning process to generate a predicted power consumption for each number of chiller systems; and (Moon in Abstract teaches a hybrid short-term load forecast model to predict power consumption. Page 7-8 section Building a Hybrid Forecasting Model teaches using an artificial neural network to build the hybrid model.)
Moon is an art in the area of interest as teaches a model to predict power consumption (Abstract). A combination of Moon with Asmus would allow the system to use neural network trained with a machine learning process to generate a predicted power consumption. Asmus in ¶0060 already teaches, estimating power consumption of chillers. However it doesn’t teach using a neural network to generate the estimated power consumption. Moon teaches using a neural network to generate the estimated power consumption. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the teaching of Moon with Asmus, and use a neural network to estimate power consumption. One would have been motivated to do so because an hybrid model with neural network is able to provide good performance in predictions regardless of diverse external factors, as taught by Moon in Page 15 section 5.3.ComparisonofForecastingTechniques)
However Asmus and Moon as combined doesn’t teach, a linear regression model configured to generate a predicted average load current for each number of chiller systems. (Estelle in ¶0078 teaches determining a predicted current or voltage measurement. ¶0062 teaches predictive analyses include linear regression)
Estelle is an art in the area of interest as it teaches, predicting current measurement. A combination of Estelle with Asmus and Moon would teach generating a predicted average load current for each number of chiller systems. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the teaching of Estelle with Asmus and Moon. One would have been motivated to do so because doing so would allow the system to identify fault conditions relating to excessive, insufficient, or absent current.
Claim(s) 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Asmus (US20130345880A1) in view of Moon (Hybrid Short-Term Load Forecasting Scheme Using Random Forest and Multilayer Perceptron) and further in view of Estelle (US20220373614A1) and further in view of Wallace (US20200408447A1)
Regarding claim 16,
Asmus, Moon and Estelle teaches, The system of claim 15, wherein the method includes determining the number of the plurality of chiller systems to utilize in cooling the load based on the predicted power consumption for each number of chiller systems (Asmus in ¶0052 teaches, determine one or more feasible combinations of devices that will satisfy the plant load at a time and for an actual or expected set of conditions (e.g., load conditions, weather conditions, etc.). ¶0061 teaches, turning on the devices of the combination with optimum energy consumption (310). According to an exemplary embodiment, the optimum energy consumption is the lowest energy consumption for devices that will meet the plant load and satisfy constraints on the system)
Asmus, Moon and Estelle doesn’t teach, and the predicted average load current each number of chiller systems. (Wallace in ¶0124 teaches, power consumption formula which shows that power consumption has a linear relationship with current. Asmus in ¶0061 already teaches, selecting a chiller with lowest energy consumption. A combination of Asmus’s teaching of selecting chiller with lowest energy consumption and Wallace’s teaching regarding the linear relationship between power consumption and current, would teach selecting chiller with lowest load current.)
Wallace is an art in the area of interest as it teaches a relationship between power consumption and current (see ¶0124). A combination of Asmus, Moon and Estelle’s teaching of selecting chiller with lowest energy consumption and Wallace’s teaching regarding the linear relationship between power consumption and current, would teach selecting chiller with lowest load current. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the teaching of Wallace with Asmus, Moon and Estelle since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim(s) 17-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rousselet (US20210180891A1) in view of Seki (US20200132344A1)
Regarding claim 17,
Rousselet teaches, A method, comprising:
providing, to an analysis model of a control system, a plurality of operating parameters associated with the chiller system; and (¶0056-¶0057 and Fig. 2 and 3A teaches providing collected sensor data and set points data to a providing 84 which includes machine learning models 94. ¶0025 teaches, a chiller)
generating, with the analysis model, operating parameter adjustments for reducing power consumption of the chiller system. (¶0075 and Fig. 3B teaches searching for optimal operating mode and set points for minimizing energy consumption)
Rousselet doesn’t teach, chilling, with a water chiller system, a load associated with a semiconductor fabrication facility; (Seki in ¶0043 teaches a chiller system being used in a semiconductor manufacturing apparatus involving plasma etching as described later, and is configured to perform control so as to maintain, for example, a temperature of a semiconductor wafer)
Seki is an art in the area of interest as it teaches a chiller device 100 is used for, for example, a semiconductor manufacturing apparatus. A combination of Seki with Rousselet would allow the system to be used in a chiller system associated with a semiconductor fabrication facility. It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the teaching of Seki with Rousselet. One would have been motivated to do so because doing so would allow the system to maintain a temperature of a semiconductor wafer to a constant temperature in the plurality of steps of fabrication as taught by Seki in ¶0043.
Regarding claim 18,
Rousselet and Seki teaches, The method of claim 17, comprising training the analysis model with a machine learning process. (Rousselet in ¶0094-¶0095 teaches training the model using machine learning process)
Regarding claim 19,
Rousselet and Seki teaches, The method of claim 17, comprising: generating, with the analysis model, a first predicted power consumption of the chiller system based on the input parameters; (Rousselet in ¶0070 teaches energy consumption for input parameters)
adjusting, with the analysis model, values of the input parameters; (Rousselet in ¶0070 teaches, cycling 154 through potential parameters including operating modes (wet, dry, hybrid or adiabatic) of the cooling tower 16, values for the leaving process fluid temperature (LPFT) and/or pressure, and the process fluid flow rate)
generating, with the analysis model, a second predicted power consumption of the chiller system based on the adjust values; (Rousselet in ¶0070 teaches, cycling 154 through potential parameters including operating modes (wet, dry, hybrid or adiabatic) of the cooling tower 16, values for the leaving process fluid temperature (LPFT) and/or pressure, and the process fluid flow rate to calculate 160 system energy, water consumption, and operating cost for possible combinations of potential parameters such as every possible combination of potential parameters)
and generating the operating parameter adjustments based on the second predicted power consumption. (Rousselet in ¶0084 and Fig. 3B teaches, providing or returning 172 one or more optimal parameters of the cooling subsystem 14 to achieve the target optimizing criterion, e.g., minimized energy consumption, minimized water consumption, or minimized operating cost.)
Regarding claim 20,
Rousselet and Seki teaches, The method of claim 17, wherein the operating parameter adjustments include a pressure difference adjustment for a chilled water pipe of the chiller system. (Rousselet in ¶0029 teaches optimal operating parameter includes an optimal pressure of the process fluid leaving the heat rejection apparatus)
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ISTIAQUE AHMED whose telephone number is (571)272-7087. The examiner can normally be reached Monday to Thursday 10AM -6PM and alternate Fridays.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kamini Shah can be reached at (571) 272-2279. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/ISTIAQUE AHMED/ Examiner, Art Unit 2116
/KAMINI S SHAH/ Supervisory Patent Examiner, Art Unit 2116