DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
The amendment filed on 05/12/2026 has been entered. Claim(s) 1-15 is/are now pending in the application. Applicant's amendments have addressed all informalities as previously set forth in the non-final action mailed on 02/13/2026.
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(s) 1-15 is/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(s) 1 states
“…
computing at least one of a volatility score and an activity score,
wherein
the signal time series score is associated with a measure of a degree of variation of the signal time series data over time,
wherein
the volatility score characterizes the degree of variation of the signal time series over time
and
the activity score characterizes the likelihood of unique values in the signal time series over time
…”.
It is unclear if the underline claim language should be interpreted as computing at least one of each/both a volatility score and an activity score (e.g., requiring at least one volatility score and at least one activity score) or computing at least one of a volatility score or an activity score (e.g., requiring only one of a volatility score or an activity score). Amendment is necessary.
For examination purposes, examiner will take the broadest reasonable interpretation (e.g., requiring only one of a volatility score or an activity score).
Claim(s) 2-15 are rejected as for being dependent on rejected claim(s) 1.
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.
Claim(s) 1-15 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more (See 2019 Update: Eligibility Guidance).
Independent Claim(s) 1 recites
A method
for
determining operating states of a chemical plant, in particular of operating states in a process group,
the method comprising:
providing signal time series data associated with a first measurement point in a chemical plant,
determining, based on the signal time series data associated with the first measurement point in a chemical plant, a respective signal time series score
by
computing at least one of a volatility score and an activity score,
wherein
the signal time series score is associated with a measure of a degree of variation of the signal time series data over time,
wherein
the volatility score characterizes the degree of variation of the signal time series over time
and
the activity score characterizes the likelihood of unique values in the signal time series over time,
determining the operating state based on the respective signal time series score associated with a measure of a degree of variation of the signal time series data over time,
generating data associated with the operating state of the chemical plant to monitor and/or control the chemical plant
[Mathematical Concepts – mathematical relationships; mathematical formulas or equations or mathematical calculation] and/or [Mental Processes - concepts performed in the human mind (including an observation, evaluation, judgement, opinion)].
Independent Claim(s) 12 recites
determining operating states of a chemical plant,
receive signal time series data associated with a first measurement point in a chemical plant,
determine based on the signal time series data associated with the first measurement point in a chemical plant a respective signal time series score associated with a measure of a degree of variation of the signal time series data over time
determine the operating state based on respective signal time series score associated with a measure of a degree of variation of the signal time series data over time
and
generate data associated with the operating state of the chemical plant, to monitor and/or control the chemical plant
[Mathematical Concepts – mathematical relationships; mathematical formulas or equations or mathematical calculation] and/or [Mental Processes - concepts performed in the human mind (including an observation, evaluation, judgement, opinion)].
In combination with Independent Claim(s) 1, Claim(s) 2-11, 13-15 recite(s)
providing signal time series data associated with a second measurement point in a chemical plant,
determining based on the signal time series data associated with the second measurement point respective signal time series score associated with a measure of a degree of variation of the second signal time series data over time,
determining the operating state comprises
determining the operating state based on the respective signal time series scores of the first time series data and the second time series data.
measurement point information is provided for the first and the second measurement point
and
the measurement point information comprises
a technical relation indicator.
determining the operating state is further based on the technical relation indicator in particular,
determining the operating state comprises
determining the operating state based on the respective signal time series score associated with a measure of a degree of variation of the signal time series data over time of the first signal time series data and the second time series data only if the technical relation indicator indicates that the measurement points are technically related, in particular belong to one process group.
determining the operating state is based on the respective signal time series score associated with a measure of a degree of variation of the signal time series data over time and a respective cluster classifier.
determining the operating state comprises
determining an on or an off state.
the data associated with the operating state of the chemical plant, to monitor and/or control the chemical plant is indicative of an on state or an off state.
selecting signal time series data associated with an ON-state and determining a stability score on the selected signal time series.
determining stable operations based on the stability score.
determining an event based on the stability score.
providing signal time series data from a measurement point
and
receiving data associated with the operating state of the chemical plant generated according to claim l, to monitor and/or control the chemical plant.
determining operating states of a chemical plant is disclosed,
determining the operating states of a chemical plant
according to claim 1.
monitoring and/or controlling a chemical plant,
comprising
receiving the data associated with the operating state of the chemical plant to monitor and/or control the chemical plant as generated according to claim l
and
providing a control signal based on the received data,
in particular
when the received data is indicative of an instable operation state,
annotating signal time series data associated with a first measurement point in a chemical plant,
comprising
receiving the data associated with the operating state of the chemical plant,
generated according to claim 1 to monitor and/or control the chemical plant as generated according to the method
for
determining operating states of a chemical plant
and
storing the data associated with the operating state of the plant together with the signal time series data
[Mathematical Concepts – mathematical relationships; mathematical formulas or equations or mathematical calculation] and/or [Mental Processes - concepts performed in the human mind (including an observation, evaluation, judgement, opinion)].
This judicial exception is not integrated into a practical application. Limitations that are not indicative of integration into a practical application:
Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP § 2106.05(f)) (i.e. A computer implemented method; A system comprising an unit time series acquisition unit configured to; an on/off score unit configured to; an operating state determining unit configured to; an output unit configured to; A computer program product for; the computer program product comprising instructions, which, when executed on computing devices of a computing environment, is configured to carry out the steps of the method of);
Adding insignificant extra-solution activity to the judicial exception (see MPEP § 2106.05(g)) (i.e. generic data acquisition & computer function to facilitate the identified abstract idea (e.g., providing signal time series data associated with a first measurement point in a chemical plant,)); or
Generally linking the use of the judicial exception to a particular technological environment or field of use (MPEP § 2106.05(h)) (i.e. of a chemical plant; to monitor and/or control the chemical plant; for stopping the plant).
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because looking at the additional elements as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. The additional elements simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 134 S. Ct. at 2359-60, 110 USPQ2d at 1984 (see MPEP § 2106.05(d)) (i.e. See Alice Corp. and cited references for evidence of additional elements (i.e., generic computer structure)).
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-15 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by MA ET AL. (US 20190227504 A1) (hereinafter “MA”).
With respect to Claim(s) 1, MA teaches computer methods and systems that build and deploy a pattern model to detect an operating event in an online plant process. To build the pattern model, the methods and systems define a signature of the operating event, such that the defined signature contains a time series pattern for a KPI associated with the operating event. The methods and systems deploy the pattern model to automatically monitor, during online execution of the plant process, trends in movement of the KPI as a time series. The methods and systems determine, in real-time, a distance score between a range of the monitored time series and the time series pattern contained in the defined signature. The methods and systems automatically detect the operating event in the online industrial process based on the determined distance score, and alter parameters of the process (e.g., valves, actuators, etc.) to prevent the operating event and the BRI of:
A computer implemented method (See, e.g., Fig(s). 4)
for
determining operating states of a chemical plant, in particular of operating states in a process group (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D),
the method comprising:
providing signal time series data (See, e.g., ¶ 0006-0020, 0081; See also, e.g., Fig(s). Fig(s). 1-3, 5D)
associated with
a first measurement point in a chemical plant (See, e.g., ¶ 0006-0020, 0081; See also, e.g., Fig(s). Fig(s). 1-3, 5D),
determining, based on the signal time series data associated with the first measurement point in a chemical plant, a respective signal time series score (See, e.g., ¶ 0006-0020, 0081; See also, e.g., Fig(s). Fig(s). 1-3, 5D)
by
computing at least one of a volatility score and an activity score (See, e.g., ¶ 0009, 0017, 0049, 0076),
wherein
the signal time series score is associated with a measure of a degree of variation of the signal time series data over time (See, e.g., ¶ 0009, 0017, 0049, 0076),
wherein
the volatility score characterizes the degree of variation of the signal time series over time and the activity score characterizes the likelihood of unique values in the signal time series over time (See, e.g., ¶ 0009, 0017, 0049, 0076),
determining the operating state based on the respective signal time series score (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D)
associated with
a measure of a degree of variation of the signal time series data over time (See, e.g., ¶ 0009, 0017, 0049, 0076),
generating data (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D)
associated with
the operating state of the chemical plant (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D)
to
monitor and/or control the chemical plant (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D).
With respect to Claim(s) 12, MA teaches computer methods and systems that build and deploy a pattern model to detect an operating event in an online plant process. To build the pattern model, the methods and systems define a signature of the operating event, such that the defined signature contains a time series pattern for a KPI associated with the operating event. The methods and systems deploy the pattern model to automatically monitor, during online execution of the plant process, trends in movement of the KPI as a time series. The methods and systems determine, in real-time, a distance score between a range of the monitored time series and the time series pattern contained in the defined signature. The methods and systems automatically detect the operating event in the online industrial process based on the determined distance score, and alter parameters of the process (e.g., valves, actuators, etc.) to prevent the operating event and the BRI of:
determining operating states of a chemical plant (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D),
the system comprising
an unit time series acquisition unit (See, e.g., Fig(s). 4)
configured to
receive signal time series data associated with a first measurement point in a chemical plant (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D),
an on/off score unit (See, e.g., Fig(s). 4)
configured to
determine based on the signal time series data associated with the first measurement point in a chemical plant a respective signal time series score (See, e.g., ¶ 0006-0020, 0081; See also, e.g., Fig(s). Fig(s). 1-3, 5D)
associated with
a measure of a degree of variation of the signal time series data over time (See, e.g., ¶ 0009, 0017, 0049, 0076)
an operating state determining unit (See, e.g., Fig(s). 4)
configured to
determine the operating state based on respective signal time series score (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D)
associated
with a measure of a degree of variation of the signal time series data over time (See, e.g., ¶ 0009, 0017, 0049, 0076)
and
an output unit (See, e.g., Fig(s). 4)
configured to
generate data associated with the operating state of the chemical plant (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D),
to
monitor and/or control the chemical plant (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D).
With respect to Claim(s) 2, MA teaches the BRI of the parent claim(s).
MA further teaches the BRI of:
providing signal time series data (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D)
associated with
a second measurement point in a chemical plant (See, e.g., ¶ 0006-0020, 0081; See also, e.g., Fig(s). Fig(s). 1-3, 5D),
determining, based on the signal time series data associated with the second measurement, point respective signal time series score (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D)
associated with
a measure of a degree of variation of the second signal time series data over time (See, e.g., ¶ 0049),
wherein
determining the operating state comprises
determining the operating state based on the respective signal time series scores of the first time series data and the second time series data (See, e.g., ¶ 0006-0020, 0081; See also, e.g., Fig(s). Fig(s). 1-3, 5D).
With respect to Claim(s) 3, MA teaches the BRI of the parent claim(s).
MA further teaches the BRI of:
wherein
measurement point information is provided for the first and the second measurement point (See, e.g., ¶ 0006-0020, 0081; See also, e.g., Fig(s). Fig(s). 1-3, 5D)
and
wherein
the measurement point information comprises
a technical relation indicator (See, e.g., ¶ 0010, 0018, 0037, 0039, 0042, 0044, 0047, 0057, 0058, 0079).
With respect to Claim(s) 4, MA teaches the BRI of the parent claim(s).
MA further teaches the BRI of:
wherein
determining the operating state is further based on the technical relation indicator in particular (See, e.g., ¶ 0010, 0018, 0037, 0039, 0042, 0044, 0047, 0057, 0058, 0079),
the step of
determining the operating state comprises
determining the operating state based on the respective signal time series score associated with a measure of a degree of variation of the signal time series data over time of the first signal time series data and the second time series data only if the technical relation indicator indicates that the measurement points are technically related, in particular belong to one process group (See, e.g., ¶ 0010, 0018, 0037, 0039, 0042, 0044, 0047, 0057, 0058, 0079).
With respect to Claim(s) 5, MA teaches the BRI of the parent claim(s).
MA further teaches the BRI of:
wherein
determining the operating state is based on
the respective signal time series score (See, e.g., ¶ 0006-0020, 0081; See also, e.g., Fig(s). Fig(s). 1-3, 5D)
associated with
a measure of a degree of variation of the signal time series data over time (See, e.g., ¶ 0006-0020, 0081; See also, e.g., Fig(s). Fig(s). 1-3, 5D)
and
a respective cluster classifier (See, e.g., ¶ 0006-0020, 0081; See also, e.g., Fig(s). Fig(s). 1-3, 5D).
With respect to Claim(s) 6, MA teaches the BRI of the parent claim(s).
MA further teaches the BRI of:
wherein
determining the operating state comprises
determining an on or an off state (See, e.g., ¶ 0051).
With respect to Claim(s) 7, MA teaches the BRI of the parent claim(s).
MA further teaches the BRI of:
wherein
the data associated with the operating state of the chemical plant,
to
monitor and/or control the chemical plant is indicative of an on state or an off state (See, e.g., ¶ 0051).
With respect to Claim(s) 8, MA teaches the BRI of the parent claim(s).
MA further teaches the BRI of:
selecting signal time series data associated with an ON-state (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D)
and
determining a stability score on the selected signal time series (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D).
With respect to Claim(s) 9, MA teaches the BRI of the parent claim(s).
MA further teaches the BRI of:
determining stable operations based on the stability score (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D).
With respect to Claim(s) 10, MA teaches the BRI of the parent claim(s).
MA further teaches the BRI of:
determining an event based on the stability score (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D).
With respect to Claim(s) 11, MA teaches the BRI of the parent claim(s).
MA further teaches the BRI of:
providing signal time series data from a measurement point (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D)
and
receiving data associated with the operating state of the chemical plant generated (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D)
according to claim l,
to
monitor and/or control the chemical plant (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D).
With respect to Claim(s) 13, MA teaches the BRI of the parent claim(s).
MA further teaches the BRI of:
A non-transitory computer readable medium (See, Fig(s). 4)
for
determining operating states of a chemical plant is disclosed (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D),
the computer readable medium comprising instructions, which, when executed on computing devices of a computing environment,
is configured to carry out the steps of the method of
determining the operating states of a chemical plant (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D)
according to claim 1.
With respect to Claim(s) 14, MA teaches the BRI of the parent claim(s).
MA further teaches the BRI of:
monitoring and/or controlling a chemical plant (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D),
comprising
receiving the data associated with the operating state of the chemical plant (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D),
to
monitor and/or control the chemical plant (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D)
as
generated according to claim l
and
providing a control signal based on the received data (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D),
in particular
when the received data is indicative of an instable operation state (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D),
in particular
providing a control signal for stopping the plant (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D).
With respect to Claim(s) 15, MA teaches the BRI of the parent claim(s).
MA further teaches the BRI of:
annotating signal time series data associated with a first measurement point in a chemical plant (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D),
comprising
receiving the data associated with the operating state of the chemical plant (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D),
generated according to claim 1
to
monitor and/or control the chemical plant as generated according to the method (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D)
for
determining operating states of a chemical plant (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D)
and
storing the data associated with the operating state of the plant together with the signal time series data (See, e.g., ABSTRACT; See, e.g., ¶ 0002, 0038, 0042; See also, e.g., Fig(s). 1-3, 5D).
Response to Arguments
Applicant’s amendments, filed on 05/12/2026, have been entered and fully considered. In light of the applicant’s amendments changing the scope of the claimed invention, the rejection(s) have been withdrawn or updated. However, upon further consideration, a new or updated ground(s) of rejection(s) have been made, and applicant's argument(s)/remark(s) pertaining to the amended language have been rendered moot.
Applicant's argument(s)/remark(s), see page(s) 6, filed 05/12/2026, with respect to the 112 rejection(s) has/have been fully considered.
-Applicant states
“Claim Rejections under 35 USC 112(b)
Claims 1, 12, 14 and 15 were rejected under 35 USC 112(b) as allegedly being indefinite. The Action contended that it was "unclear if claim(s) 12, 14, 15 include all the limitations of the claim upon which it depends." Applicant disagrees, but in an effort to expedite prosecution, claim 1 is amended to recite "generating data" rather than "providing data" to clarify that the method produces output data associated with the operating state. Claims 14 and 15 are amended to ensure proper antecedent basis with respect to the data generated according to claim 1. Claim 12 is also amended to be of independent form. Accordingly, Applicant submits the claims are clear and definite as amended and requests withdrawal of the present claim rejection under 35 USC 112(b).”.
Examiner agrees with the underlined argument(s)/remark(s).
Said rejection(s) has/have been withdrawn.
Necessitated by amendment, updated 112(b) rejection(s) have been made. See above.
-Applicant states
“Claim Rejections under 35 USC 112(d)
Claims 12, 14 and 15 were rejected under 35 USC 112(d) as allegedly being of improper dependent form. Applicant disagrees and as noted above, that claim 12 is amended to be of independent form while claims 14 and 15 are amended to ensure proper antecedent basis in view of the amendments to claim 1. Accordingly, Applicant submits that the present claims are of proper dependent form and requests withdrawal of the present claim rejections under 35 USC 112(d).”.
Examiner agrees with the underlined argument(s)/remark(s).
Said rejection(s) has/have been withdrawn.
Applicant's argument(s)/remark(s), see page(s) 6-8, filed 05/12/2026, with respect to the 101 rejection(s) has/have been fully considered.
-Applicant states
“Claim Rejections under 35 USC 101
The Action issued the following rejections under 35 USC 101:
* Claim 13 was rejected as allegedly being directed to non-statutory subject matter.
* Claims 1-15 were rejected as allegedly being directed to an abstract idea.
Applicant respectfully submits that the claims, as amended, are directed to patent eligible subject matter. As an initial matter, with respect to claim 13, the claim has been amended to recite "[a] non-transitory computer readable medium" as suggested in the Action. Accordingly, claim 13 is directed to patentable eligible subject matter and withdrawal of the rejection to claim 13 is requested.
With respect to the rejection of claims 1-15, the Action contends that the subject matter is directed to an abstract idea without anything more. Applicant disagrees. Claim 1, as amended, recites:
…
It is submitted that the as amended, the method includes "determining, based on the signal time series data associated with the first measurement point in a chemical plant, a respective signal time series score by computing at least one of a volatility score and an activity score, wherein the signal time series score is associated with a measure of a degree of variation of the signal time series data over time, wherein the volatility score characterizes the degree of variation of the signal time series over time and the activity score characterizes the likelihood of unique values in the signal time series over time." These specific techniques are not generic mathematical operations and/or an abstract idea, but specific signal processing techniques tied to the particular technical problem of determining operating states of a chemical plant. These specific computations relating to time series data from physical measurement points in a chemical plant cannot practically be performed in the human mind, and are not merely an abstract idea.
Moreover, the claimed method is directed to monitor and/or control the chemical plant by generating data associated with the operating state which transforms the method into a practical application. As claimed, the determination of the volatility score and activity score is applied to real-world signal time series data acquired from physical measurement points in a chemical plant, and the resulting operating state determination is used to generate data to monitor and/or control the chemical plant. Thus, the claims improve the technical field of chemical plant process control and also provide a practical application to the chemical plant. (See, e.g., Diamond v. Diehr, 450 U.S. 175, 192 (1981) (claims directed to a process for curing rubber that employed a mathematical equation were patent eligible because the equation was applied in a specific manner to achieve a practice result).
For at least the reasons described herein, Applicant submits the claims are not directed to an abstract idea, are directed to patent eligible subject matter. Accordingly, Applicant requests withdrawal of the present rejection under 35 USC 101.”.
Examiner respectfully disagrees with the underlined argument(s)/remark(s).
Examiner’s BRI of the claimed inventions is generic computer structure being used as a tool to mathematically process generically acquired data generally corresponding to a ‘chemical plant’ to generate a resulting data.
When examining step 2A Prong 1, Examiner determines if there is an abstract idea present. One skilled in the art can at least perform the identified abstract idea utilizing Mathematical Concepts – mathematical relationships; mathematical formulas or equations or mathematical calculation. One skilled in the art can at least perform the identified abstract idea utilizing Mental Processes - concepts performed in the human mind (including an observation, evaluation, judgement, opinion). The arguments, in light of the specification, fail to convince the Examiner that utilizing Mathematical Concepts and/or Mental Processes does not fit within the scope of the identified abstract limitations.
When examining step 2A Prong 2, Examiner examines the additional elements to determine if the identified abstract idea has been practically applied in a particular way in a particular technology. Limitations that are not indicative of integration into a practical application: Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP § 2106.05(f)); Adding insignificant extra-solution activity to the judicial exception (see MPEP § 2106.05(g)); or Generally linking the use of the judicial exception to a particular technological environment or field of use (MPEP § 2106.05(h)). The additional elements, when viewed individually and in combination with the identified abstract idea, do not add anything beyond mere instructions to implement an abstract idea on a computer, adding generic ‘apply it’ language, and generically linking the identified abstract idea to a technological environment or field of use.
When examining step 2B, Examiner examines the additional elements to determine if they amount to significantly more than the abstract idea. The only additional element(s) is/are the generic computer structure being used as a tool to perform the abstract idea. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because looking at the additional elements as an ordered combination adds nothing that is not already present when looking at the elements taken individually.
It is important to note, the judicial exception alone cannot provide the improvement. An improved abstract idea is still an abstract idea.
Examiner relies on the 2019 Patent Eligibility Guidance (2-Prong Analysis) and precedential cases utilizing said guidance. Any remarks pertaining to case law not utilizing the most current Patent Eligibility Guidance is moot. Any remarks pertaining to non-precedential case law is also moot.
Applicant compares the claimed invention to Court Decision Diamond v. Diehr, 450 U.S. 175, 209 U.S.P.Q. 1 (1981). In contrast to the claimed invention, the Diehr courts found the invention to be patent eligible because the claimed steps act in concert to transform raw, uncured rubber to cured molded rubber (improving a manufacturing process).
See updated rejection(s) necessitated by amendment.
Applicant's argument(s)/remark(s), see page(s) 8-9, filed 05/12/2026, with respect to the art rejection(s) has/have been fully considered.
-Applicant states
“Claim Rejections under 35 USC 102
Claims 1-15 were rejected under 35 USC 102(a)(1) as allegedly being anticipated by Ma et al. (US Pub. No. 2019/0227504) (hereinafter "Ma"). Applicant traverses the rejection. As noted above, claim 1 has been amended to recite "computing at least one of a volatility score and an activity score" and that "the volatility score characterizes the degree of variation of the signal time series over time and the activity score characterizes the likelihood of unique values in the signal time series over time."
It is submitted that Ma fails to teach each and every limitation of the claimed invention as amended. Anticipation requires that each element be disclosed in a single prior art reference. Here, Ma is directed to deploying a pattern model to automatically monitor, during online execution of the plant process, trends in movement of the KPI as a time series. (See Abstract of Ma.) Ma further describes determining a "distance score" between a range of the monitored time series and a time series pattern contained in a defined signature and then detecting the operating event based on the determined distance score. (See [0006] to [0020] of Ma.) Thus, Ma's distance score quantifies how closely the current data matches a stored pattern and cannot reasonably correspond to the claimed "volatility score" and "activity score." That is, Ma compares a current signal to a known pattern to detect a pre-defined event, whereas the present claims compute characteristics of the signal itself to determine an operating state. There is nothing in Ma to teach the specific computation of a volatility score or an activity score as claimed.
Accordingly, Ma fails to teach each and every limitation and cannot anticipate the claimed invention. Further, there is nothing to teach or suggest computing a volatility score or an activity score as claimed based on Ma. Accordingly, Applicant requests withdrawal of the present anticipation rejection.”.
The underlined argument(s)/remark(s) are moot because the arguments do not apply to any of the previous rejected limitations.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RAYMOND NIMOX whose telephone number is (469)295-9226. The examiner can normally be reached Mon-Thu 10am-8pm CT.
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RAYMOND NIMOX
Primary Examiner
Art Unit 2857
/RAYMOND L NIMOX/Primary Examiner, Art Unit
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