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 .
This Office action is responsive to the communication received on 08/29/2023. The claims 1-20 are pending, of which the claim(s) 1, 11, & 19 is/are in independent form.
This application also claims priority to U.S. Provisional Application Serial No. 63/505,579, filed on June 1, 2023.
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 rejected under 35 U.S.C. 101 because the claimed invention is directed to Judicial Exception (“abstract idea”) without significantly more.
As to claim 1, the claim is reproduced below.
1. a method comprising:
[a] receiving, by a batch analytic system, batch data of a batch generated in an industrial process, wherein the batch data includes a set of samples associated with the batch, the batch is complete and has a first batch length;
[b] determining, by the batch analytic system, a reference batch based on a plurality of non-anomalous batches generated in the industrial process, wherein each non-anomalous batch has a same second batch length;
[c] generating, by the batch analytic system, a batch representation of the batch based on the batch data of the batch and the reference batch, wherein the batch representation of the batch aligns with the reference batch and has the second batch length associated with the reference batch; and
[d] performing, by the batch analytic system, an operation using the batch representation of the batch.
1. Step 1: Yes. The claim is to a method with series of steps, which is one of the four categories of patent eligible subject matter.
2. Step 2A, Prong 1: Yes. The claim(s) recite(s) limitations [b] - [d] shown above without bold emphasis. These limitations of determining, generating, and performing (shown without bold emphasis), under BRI as drafted, cover performance of the limitation in the mind but for the recitation of generic computer components, namely by a batch analytic system (see spec, para. 0226). That is, other than reciting of “by a batch analytic system”, nothing in these limitations preclude each of these steps from practically being performed manually in the mind without the use of any computing device. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas.
In this instance, the step of determining and generating of limitations [b] and [c] require human user to determine/select a reference data to be used to generate a batch representation using simple mathematical calculations at most with the aid of a pen and paper. See, Spec, paras. 0233-0234, 0237 that describes additional details about how determining and generating can be performed. This is particularly true when the sample size is small, e.g., 10 samples and the claim is broad enough to cover very small number of samples to large number of samples. Just because the data samples represent the values for an industrial process do not mean human’s mind cannot process them since they all represent mathematical variables. When the sample size is small, it is possible to determine a reference batch by considering multiple batches having non-anomalous operation and generating a batch representation (aligned batch in time length) using time interpolation. Applicant’s specification describes using of an exemplary algorithm (i.e., Dynamic Time Warping (DTW) matrix) to align batch data and reference batch. Human’s mind can practically compute each elements of this DTW matrix/grid by performing mathematical calculations between the collected batch data and the represent data. See spec, para. 075. Human mind can identify the time-wrapping elements and the path between batch data and determined reference batch.
Furthermore, the limitation [d] as claimed is broad enough to cover performing every possible operations for the generated batch operation. See para. 0236 of the spec that states: “determine an anomaly metric…particular batch to perform other operations.” For example, mere deciding to use the generated batch representation or calculating some anomaly values/metrics using the generated batch representation (time aligned batch data sequence) can be also called performing an operation under BRI. Such mere calculating of some value using the generated batch representation can be performed in human’s mind as required by the performing step.
In summary, the limitations [b] to [d] cover performance of the limitations in mind but for the recitation of the generic computer element, namely batch analytic system. Accordingly, the claim recites an abstract idea.
3. Step 2A, Prong 2: No. This judicial exception is not integrated into a practical application. In particular, as shown above with bold emphasis, the claim recites the additional elements of:
1) “receiving, by a batch analytic system, batch data of a batch generated in an industrial process, wherein the batch data includes a set of samples associated with the
batch, the batch is complete and has a first batch length” and
2) “by the batch analytic system” in each determining, generating, and performing step.
The 2nd additional element, i.e., using of “batch analytic system” is akin to mere implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). This is so because in all three steps of determining, generating, and performing, the batch analytic system is recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component. Put differently, even without the using of the batch analytic system ( a computer), these steps can be performed manually.
The 1st additional element (i.e., receiving step) is akin to adding a pre-solution insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g). This is so because receiving limitation is recited at a high level of generality (i.e., data gathering step) required to perform determining and generating steps. The batch analytic system used to receive batch data is also recited at a high level of generality, that merely automates the receiving step. Accordingly, even in combination when viewed the claim as a whole, these additional elements fail to integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea other than using a computer to implement the abstract idea using extra solution activity. The claim is directed to the abstract idea.
4. Step 2B: No. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of “by the batch analytic system” in all four steps amounts no more than using computer as a tool to execute the abstract idea. The first additional element of receiving step is akin to adding an insignificant extra solution activity. Furthermore, this entire receiving step is well-understood, routine, and conventional activity in a batch processing art and examiner takes an Official notice to that effect by relying on the cited 1references as evidence for Berkheimer memo. Accordingly, the additional elements when considered separately and in combination, do not add significantly more (also known as an “inventive concept”) to the exception since they require using of well-understood, routine, and conventional insignificant extra solution activity and using computer as a tool to perform the abstract idea. The claim is not patent eligible under 101.
As to claim 11
11. A method comprising:
[a] receiving, by a batch analytic system, batch data of a batch generated in an industrial process, wherein the batch is ongoing and has a first batch length at a sample point during the batch, the batch data includes a set of samples associated with the batch at the sample point;
[b] generating, by the batch analytic system based on the batch data of the batch and a reference batch that has a second batch length, a batch representation corresponding to the sample point of the batch using a first Dynamic Time Warping (DTW) matrix and a second DTW matrix, wherein the second DTW matrix is determined based on the first DTW matrix, and the batch representation corresponding to the sample point of the batch aligns with a batch portion of the reference batch and has a third batch length associated with the batch portion of the reference batch; and
[c] performing, by the batch analytic system, an operation using the batch representation corresponding to the sample point of the batch.
1. Step 1: Yes. The claim is to a process/method, which is one of the four categories of patent eligible subject matter.
2. Step 2A, Prong 1: Yes. The claim(s) recite(s) steps of limitations [b] and [c] shown above without bold emphasis. These steps [b] and [c] are considered an abstract idea based exception because they can be practically performed in human’s mind using observation, evaluation, judgment, opinion but for the recitation of generic computer elements, namely “the batch analytic system”.
Specifically, when the sample size to be evaluate is small (e.g., 5 samples), the generating of representation step as claimed cover performing a simple mathematical calculation at most with the aid of pen and paper. The using of “first Dynamic Time Warping (DTW)” algorithm which inherently uses warping (DTW) matrix between two sequences (like “batch data of a batch generated in an industrial process, wherein the batch is ongoing and has a first batch length at a sample point during the batch,” and “reference batch that has a second batch length”) in order to align (make them of same time length). The using of first DTW matrix and second DTW matrix as claimed herein cover using one of the DTW matrix (e.g., second DTW matrix) as submatrix of another matrix (first DTW matrix). These types of the calculations also can be practically performed in human’s mind.
Furthermore, the limitation of “performing, an operation using the batch representation corresponding to the sample point of the batch” as described in the specification, cover mere performing of data calculation such as generating of a health score for the generated batch representation (time sequence aligned batch data). This type of the steps can be performed with user’s judgment. If claim limitations, under their broadest reasonable interpretation, cover performance of the limitation in the mind but for the recitation of generic computer components, as in this case, then they fall within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
3. Step 2A, Prong 2: No. This judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements shown above with bold emphasis. That is,
(1) receiving, by a batch analytic system, batch data of a batch generated in an industrial process, wherein the batch is ongoing and has a first batch length at a sample point during the batch, the batch data includes a set of samples associated with the batch at the sample point;
(2) “by the batch analytic system” in both generating and performing steps.
Here, 1st additional element of “receiving” step is recited at a high level of generality as part of data gathering step from an ongoing batch having a first batch length, and hence amounts to no more than data gathering step. This type of step is a form of a pre-solution insignificant extra-solution activity. The limitation requires using of “batch analytic system” to perform the receiving step but this too is recited at a high level of generality, and merely automates the receiving steps. Furthermore, the 2nd additional element of “by the batch analytic system” in generating and performing step also is recited at high level of generality, and merely automates the generating and performing step. Each of the additional limitations individually or in combination is no more than mere instructions to apply the exception using a generic computer component (batch analytic system) and performing of data gathering step. Accordingly, the individual/combination of additional element(s) fail(s) to integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the above abstract idea shown without bold emphasis. The claim is directed to an abstract idea.
4. Step 2B: No. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the 1st additional element amounts to no more than adding an insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g) and 2nd additional elements is akin to adding instructions to implement an abstract idea on a computer. Furthermore, the step of “receiving, by a batch analytic system, batch data of a batch generated in an industrial process, wherein the batch is ongoing and has a first batch length at a sample point during the batch, the batch data includes a set of samples associated with the batch at the sample point;” is a well-understood, routine, conventional activity and examiner takes an Official notice to that effect by relying on the cited references as 2evidence- for Berkheimer memo. The additional elements when considered separately and in combination do not add significantly more (also known as an “inventive concept”) to the exception. The claim is not patent eligible under 101.
As to claim 19
19. A system comprising:
a memory storing instructions; and
a processor communicatively coupled to the memory and configured to execute the instructions to:
[a] receive batch data of a batch generated in an industrial process, wherein the batch data includes a set of samples associated with the batch, the batch is complete and has a first batch length;
[b] determine a reference batch based on a plurality of non-anomalous batches generated in the industrial process, wherein each non-anomalous batch has a same second batch length;
[c] generate a batch representation of the batch based on the batch data of the batch and the reference batch, wherein the batch representation of the batch aligns with the reference batch and has the second batch length associated with the reference batch; and
[d] perform an operation using the batch representation of the batch.
1. Step 1: Yes. The claim is to a system, which is one of the four categories of patent eligible subject matter.
2. Step 2A, Prong 1: Yes. The claim(s) recite(s) limitations of
“determine a reference batch based on a plurality of non-anomalous batches generated in the industrial process, wherein each non-anomalous batch has a same second batch length”;
“ generate a batch representation of the batch based on the batch data of the batch and the reference batch, wherein the batch representation of the batch aligns with the reference batch and has the second batch length associated with the reference batch”; and
“perform an operation using the batch representation of the batch”.
In light of applicant’s specification, these all limitations (shown without bold emphasis) can be considered an abstract idea based exception because they all can be practically performed in human’s mind at most with the aid of pen and paper for the similar reasons set forth above in claim 1. While a processor and memory are being used to execute these limitations, they merely cover performance of the limitations in the mind but for the recitation of generic computer components. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
3. Step 2A, Prong 2: No. This judicial exception is not integrated into a practical application. In particular, the claim recites the additional element(s) shown above with bold emphasis. That is, the additional elements are:
(1) a memory storing instructions; and
a processor communicatively coupled to the memory
(2) receive batch data of a batch generated in an industrial process, wherein the batch data includes a set of samples associated with the batch, the batch is complete and has a first batch length.
Here, both additional elements are recited at high level of generality. Thus, 1st additional element is akin to implementing an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea - see MPEP 2106.05(f) and 2nd additional element is akin to adding an insignificant extra-solution activity (due to mere data gathering (receiving of the batch data from a complete batch)) to the judicial exception - see MPEP 2106.05(g). Even when viewed the claim as a whole, it still fails to integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the above abstract idea. The claim is directed to an abstract idea.
4. Step 2B: No. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the both additional elements amount to no more than using computer as a tool and adding insignificant extra-solution activity to the judicial exception respectively. Furthermore, the receiving step is well-understood, routine, conventional activity and examiner takes an Official notice to that effect by relying on the cited prior arts as evidence-- Berkheimer memo. Accordingly, the additional elements when considered separately and in combination do not add significantly more (also known as an “inventive concept”) to the exception since they continue to remain using computer as a tool to perform the abstract idea and performing of pre-solution insignificant extra-solution activity. The claim is not patent eligible.
Regarding claims 2- 10, these claims depend on claim 1 and recite the same abstract idea and additional elements set forth above in claim 1. The claims 2- 10 recite other new limitations not required in claim 1. However, these new limitations also can be practically performed in human’s mind at most with the aid of pen and paper. This is so because applicant’s specification broadly describes them as part of simple mathematical operations or actions that can are capable of being performed via user’s observation, evaluation, judgment, opinion. Therefore, the added limitations of the claims 2- 10 are also abstract and therefore they do not add any new additional elements. The claims 2- 10 do not provide a practical application in step 2A prong 2 and an inventive concept in Step 2B. The claims are not eligible under 101.
Regarding claims 12- 18, these claims depend on claim 11 and recite the same abstract idea and additional elements set forth above in claim 1. The claims 12- 18 recite other new limitations not required in claim 11. However, these new limitations also can be practically performed in human’s mind at most with the aid of pen and paper. This is so because applicant’s specification broadly describes them as part of simple mathematical operations or actions that can are capable of being performed via user’s observation, evaluation, judgment, opinion. Therefore, the added limitations of the claims 12- 18 are also abstract and therefore they do not add any new additional elements. The claims 12- 18 do not provide a practical application in step 2A prong 2 and an inventive concept in Step 2B. The claims are not eligible under 101.
Regarding claim 20, this claim depends on claim 19 and recites the same abstract idea and additional elements set forth above in claim 19. This claim further adds new limitations but that too can be practically performed in human’s mind at most with the aid of pen and paper. Accordingly, the claim 20 also fails to provide a practical application in Step 2A Prong 1 and an inventive concept in Step 2B. The claim is not patent eligible.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 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.
Regarding claim 1, the claim recites “generating, by the batch analytic system, a batch representation of the batch based on the batch data of the batch” in lines 8-9. The claim also recites “receiving, by a batch analytic system, batch data of a batch generated in an industrial” in line 2 and “determining, by the batch analytic system, a reference batch based on a plurality of” in line 5. However, “the batch” of the lines 8-9 fails to clarify whether this batch corresponds to batch of the line 2 (received batch data of a batch) or the batch of the line 8 (a reference batch) thereby rendering the scope of the claim indefinite.
For the examination purpose, “the batch” of line 8 is interpreted as batch of the line 2 that is received rather than reference batch of line 5.
Regarding claim 11, the claim fails to clarify which batch (batch of line 2 that is received or batch of line 7 for “reference batch”) is represented when recited as “the batch” in line 8 thereby rendering the scope of claim indefinite.
For the examination purpose, “the batch” of line 8 is interpreted as batch of line 2 for received batch data of a batch generated in an industrial process.
Regarding claim 19, in line 11, the claim fails to clarify which batch is represented by recitation of “the batch” out of batch of line 5 or reference batch of line 8 thereby rendering the scope of claim indefinite.
For the examination purpose, “the batch” of line 11 is interpreted as batch of line 5 for generated batch in an industrial process rather than of reference batch.
Regarding claims 2- 10, 12- 18, & 20, these claims are also rejected to at least by virtue of their dependency with rejected claims 1, 11, & 19 respectively.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1- 10 & 19 -20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tsuduki (US 20220276130 A1) in view of Castillo et al. (US 2019/0332101 A1).
Regarding claim 1, Tsuduki teaches a method comprising: ([009]);
[a] receiving, by a batch analytic system [a computer 200 of fig. 10 that implements “a measurement data recording apparatus 4” or “a generation apparatus 5” of fig. 1], batch data [“the target batch data” from the facility 2] of a batch generated in an industrial process [“facility 2 is provided with one or more sensors 20”], wherein the batch data includes a set of samples [timeseries measured by sensors 20] associated with the batch, the batch is complete [“the trigger signal…batch processing is completed in the facility 2”] and has a first batch length [inherent length for the batch data stored in the batch file 430 of recording apparatus 4/generating apparatus 5] ([030, 043-044, 092, 098], fig. 1);
[b] determining, by the batch analytic system, a reference batch [“the reference batch data may be selected from batch data in a state where the facility 2 is good”] based on a plurality of non-anomalous [“the reference batch data may be selected from batch data in a state where the facility 2 is good,”] batches generated in the industrial process,
[c] generating [performing of the DTW processing either in the recording apparatus 4 with “DTW processing portion 46” to provide an output to the item 48 or in generation apparatus 5 with “DTW processing portion 46” to provide output to the item 532], by the batch analytic system, a batch representation [“perform processing of aligning the time width of the target batch data with respect to the reference batch data”. The result of “perform the DTW processing” to the “target batch” with “reference batch” because a batch representation or aligned data having same length as that of the reference batch] of the batch based on the batch data of the batch and the reference batch, wherein the batch representation of the batch aligns with the reference batch and has the second batch length associated with the reference batch ([042-044, 065-067, 092-094, 0180]); and
[d] performing [Fig. 2, S29-S31: “determination portion 48 may perform determination from each batch data in the batch file 430 subjected to the DTW processing by the DTW processing portion 46” and “in Step S31, the determination portion 48 outputs the determination result and at least the latest health index.” The batch file 430 subjected to the DTW is aligned (batch representation) batch data file], by the batch analytic system, an operation using the batch representation of the batch ([096, 0120-0121], fig. 1).
In summary, Tsuduki teaches acquiring sensor data from a facility 2 at measurement data recording apparatus 4, wherein the sensor data saved as a batch file 430 and can undergo DTW processing to align the acquired batch data with “the reference batch data” to provide the DTW processed batch data to the determination portion 48 that outputs health of the facility 2. Additionally, the measurement data 1 also can be transmitted to the generation apparatus 5 that too can perform DTW processing to the batch data against reference data before generating a determination model 431 using the aligned batch data (Fig. 1 & associated texts).
While Tsuduki teaches selecting of “the reference batch data” when the facility is in good condition so that the batch data typically can be with same second length as can be clear to PHOSITA. Nevertheless, it can be argued that even the good condition facility produced batch data may not necessarily have same length for each batch. Thus, Tsuduki may or may not teach “each non-anomalous batch has a same second batch length” as claimed and may not anticipate the claim 1.
Castillo relates to computer-implemented method (and system) for performing automated batch data alignment for modeling, monitoring, and control of an industrial batch process during offline and online (Abstract Figs. 3S). Castillo teaches generating a batch representation [aligned data 324] of the batch based on the batch data of a batch and the reference batch [“selects a reference batch as basis of the batch alignment”] (Abstract, [0439]). Specifically, Castillo teaches a method comprising:
determining, by the batch analytic system [computer system of fig. 7], a reference batch [“the method (and system) 100 may select a reference batch 106”] based on a plurality of non-anomalous batches [“subset preferably has between 10 and 30 representative good batches”] generated in the industrial process, wherein each non anomalous batch has a same [“construct the average batch, preliminary data alignment is required. This is done with DTW” .PHOSITA knows that algorithm used by DTW makes two sequences with equal length, i.e., second length] second batch length ([187-0189, 0216], Fig. 1B, Step 140).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to (1) combine Castillo and Tsuduki because they both related to a batch analyzing computer system selecting reference batch to perform batch aligning for the batch data of an industrial process and (2) modify the method/system of Tsuduki to have each non-anomalous batch considered in order to determine reference batch with batches having same second batch length as in Castillo. Doing so would allow to pick an optimal batch as the reference batch by considering various measures for alignment of two sequences and improving the quality of the batch data utilized to determine quality of the state of the facility 2 (Castillo [008] & Tsuduki Fig. 1).
Regarding claim 2, Tsuduki in view of Castillo further teaches/suggests the method of claim 1, wherein: each non-anomalous batch is verified as not including [“selected from batch data in a state where the facility 2 is good”] an anomaly throughout a batch duration of the non-anomalous batch; and the reference batch includes one or more samples corresponding to one or more sample points at which one or more samples of the non-anomalous batch are respectively collected and the reference batch has the second batch length (Tsuduki, [066] & Castillo [0188]).
Regarding claim 3, Tsuduki in view of Castillo teaches/suggests the method of claim 1, wherein determining the reference batch includes: identifying, for each sample point, a plurality of samples [“acquire a plurality of types (also referred toas channels) of measurement data”. Thus, any measured time, there will be multiple samples from each channel for each variable/process] corresponding to the sample point in the plurality of non-anomalous batches; and determining a sample [“the average and variance of the measurement values”] corresponding to the sample point for the reference batch based on the plurality of samples corresponding to the sample point in the plurality of non-anomalous batches (Tsuduki [040, 052, 070]).
Regarding claim 4, Tsuduki in view of Castillo teaches/suggests the method of claim 3, wherein determining the sample corresponding to the sample point for the reference batch includes: determining, for each process variable of the industrial process, an average value [“the average and variance of the measurement values”] of the process variable in the plurality of samples corresponding to the sample point in the plurality of non-anomalous batches; and determining a value of the process variable in the sample corresponding to the sample point in the reference batch to be the average value (Tsuduki [040, 052, 070, 096]).
Regarding claim 5, Tsuduki in view of Castillo teaches/suggests the method of claim 1, wherein determining [“the reference batch data may be selected” of Tsuduki/ “Select Reference Batch” of Castillo Fig. 1B] the reference batch includes:
determining, for each non-anomalous batch among the plurality of non-anomalous batches, one or more batch parameters [“method (and system) 100 computes 126 xp … xp, is the sum of the squared relative differences w.r. t. to each median phase length for a single batch”] of the non-anomalous batch (Castillo [0139]);
computing a batch score [steps 144- 146] of the non-anomalous batch based on the one or more batch parameters of the non-anomalous batch and one or more weight values [step S130 “variable weightings equal to 1 for one or more variables”] of the one or more batch parameters [“variables”]; and selecting the reference batch [reference batch is batch with minimum Bci of step 146] from the plurality of non-anomalous batches based on batch scores of the plurality of non-anomalous batches (Tsuduki [094] & Castillo [032, 0201-0204]).
Regarding claim 6, Tsuduki in view of Castillo further teaches the method of claim 5, wherein determining the one or more batch parameters of the non-anomalous batch includes one or3 more of:
determining an average value [“for each channel of the measurement data, the average and the variance of the time-series measurement data and the parameters”] of a particular process variable in the non-anomalous batch; determining a production rate of the non-anomalous batch based on a total amount of products generated during the non-anomalous batch and a batch duration of the non-anomalous batch (Tsuduki [096, 0114]).
Regarding claim 7, Tsuduki in view of Castillo teaches/suggests the method of claim 1, further comprising: identifying one or more additional non-anomalous batches that are generated subsequent to the plurality of non-anomalous batches in the industrial process; and re-determining [“the reference batch data may be selected from batch data in a state where the facility 2 is good” condition can be understood by PHOSITA to have occurred when operator sees new batch data coming in and liking the results of the batch and changing the prior selected reference batch] the reference batch based at least on the one or more additional non-anomalous batches (Tsuduki [066, 094]).
Regarding claim 8, Tsuduki in view of Castillo teaches/suggests the method of claim 1, wherein generating the batch representation of the batch includes: determining a Dynamic Time Warping (DTW) matrix [“DTW processing” algorithm inherently uses DTW matrix (“Filling out a grid of size IxJ” of Castillo) to “determining a DTW path”4] between a first sequence [“target batch” measured from sensors] including the set of samples associated with the batch and a second sequence [“as reference batch data”] including a set of samples associated with the reference batch, wherein the first sequence has the first batch length and the second sequence has the second batch length; determining a warping path [“DTP processing” of Tsuduki, using “the optimal warping path on the grid by backtracking from point (I,J) to point (1, 1)”] between the first sequence and the second sequence based on the DTW matrix, wherein the warping path maps each sample of the batch in the first sequence to one or more samples of the reference batch in the second sequence and maps each sample of the reference batch in the second sequence to one or more samples of the batch in the first sequence; and determining one or more representation samples [values of the grid/matrix in the path of the warping path as part of “the optimal warping path on the grid by backtracking”] based on the set of samples associated with the batch in the first sequence and the warping path, wherein each representation sample corresponds to a respective sample point associated with a sample in the reference batch and the one or more representation samples form the batch representation of the batch (Tsuduki [065-068, 096] & Castillo [0301-0304]).
Regarding claim 9, Tsuduki in view of Castillo teaches/suggests the method of claim 1, wherein performing the operation using the batch representation of the batch includes one or more of:
generating [“build a principal component analysis (PCA) model based on unfolding of the screened batch data.”] one or more principal component analysis (PCA) models of the industrial process using the batch representation of the batch (Castillo [031]); or
training one or more machine learning models [“determination model 431” being trained/updated/created with DTW processed batch data] using the batch representation of the batch (Tsuduki, [050-051, 095]).
Regarding claim 10, Tsuduki in view of Castillo teaches/suggests the method of claim 1, wherein performing the operation using the batch representation of the batch includes one or more of: determining an anomaly metric of the batch using the batch representation of the batch and a PCA model of the industrial process; or providing the batch representation of the batch to a machine learning model [“learning processing portion 532”] as an input (Tsuduki, [051-053, 095]).
Regarding claims 19- 20, Tsuduki in view of Castillo teaches/suggests inventions of these system claims for the similar reasons set forth above in method claims 1 & 3 respectively. Please note that the computer 200 of Tsuduki’s fig.10 that implements its “a measurement data recording apparatus 4, and a generation apparatus 5” is mapped with claimed “A system comprising: a memory storing instructions; and a processor”.
Claim(s) 11 & 15-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ma et al., (US 20220035348 A1,) in view of Seo (KR 20220105972 A).
Note: Ma et al., (US 20220035348 A1) incorporates US 20190332101 A1 to Castillo, see para. 005 of Ma. Hence, the office action also refers to Castillo’s paragraphs for citation which are part of the Ma’s disclosure.
Regarding claim 11, Ma teaches a method comprising: (Ma, 5[005, 0131] & Castillo [006]);
receiving, by a batch analytic system [“computer-based system 2440 that may be used to perform automated batch data time alignment”], batch data of a batch generated in an industrial process, wherein the batch is ongoing [“online batch data alignment for process monitoring and control”] and has a first batch length [the number of samples at a particular maturity percentage] at a sample point [“the percentage” or “batch maturity percentage at each sampling point”] during the batch, the batch data includes a set of samples associated with the batch at the sample point (Ma, [043, 092, 0251, 0274] & Castillo Fig. 1A, [008, 0179]);
generating, by the batch analytic system based on the batch data of the batch and a reference batch [“entire reference batch”] that has a second batch length [Castillo: [0118]:“and J is the number of points of the entire reference batch”], a batch representation [“If batch maturity is unchecked, such an embodiment guesses the percentage completion of each phase in each batch, and only aligns against the corresponding portion of the reference batch.” The online batch that is aligned using the reference batch’s portion per para. 091 of Ma] corresponding to the sample point of the batch using the offline dynamic warping alignment method as the base alignment method.” Inherently uses cost matrix/grid when aligning the completed batch and selected reference batch] the grid/matrix used when aligning the batch data with “the corresponding portion of the reference batch”],
the batch representation corresponding to the sample point of the batch aligns with a batch portion [“an embodiment guesses the percentage completion of each phase in each batch, and only aligns against the corresponding portion of the reference batch”] of the reference batch and has a third batch length associated with the batch portion of the reference batch (Ma, [023-024, 091]); and
performing [“the best-so-far alignment condition and its aligned dataset are ready to be consumed by other processes…to rebuild the supervised machine learning model” or any using of the aligned batch data.], by the batch analytic system, an operation using the batch representation corresponding to the sample point of the batch (Ma [033] & Castillo [030]).
In summary, Ma teaches aligning of incomplete batch data in online mode using a portion of the reference batch and also aligning of the completed batch in offline mode using selected reference batch”. In offline mode (Ma, para. 091, “each phase is aligned against the entire reference batch phase”) Ma’s aligning of the batch data computes a first Dynamic Time Warping (DTW) matrix and uses the computed first DTW matrix to determine aligned batch data (a batch representation which is “a warping path”) (Castillo, Fig. 1D, [0304-0306]). In this way, Ma’s offline aligning uses first DTW matrix (also known as DTW cost matrix in art) to generate the batch representation.
Ma further teaches if the aligned results of the batch aligning (generation of the batch representation) do not satisfy the performance metric, performing of the batch alignment again for multiple iterations (Ma, [049]). PHOSITA knows that when the batch sequences are long, the calculating of the cost grid/matrix as part of using DTW algorithm to align sequences or determining similarities is computationally expensive operation6. PHOSITA also knows the second DTW matrix with portion of the reference batch is a subset matrix/table of the first DTW matrix that considers the given batch data and the entire reference batch. Nevertheless, Ma does not teach utilizing the already computed first DTW matrix’s results in subsequent generation of the second DTW matrix.
Thus, Ma does not teach its generating of the batch representation corresponding to the sample point is based on using a first Dynamic Time Warping (DTW) matrix and “the second DTW matrix is determined based on the first DTW matrix” as claimed. That is, Ma does not teach using the information prior computed DTW matrix (first DTW matrix) to fill up a second DTW matrix (for a portion of the reference batch with the given batch under alignment) required as part of generating multiple rounds of alignments between sample batch and reference batch.
Seo teaches repeatedly generating a computationally expensive cost matrix (fig. 2) in order to accurately determine the position of a terminal device 10 when it is in a GPS shadow area (tunnel) (page 9, Fig. 1). Seo teaches during subsequent generation of the computationally expensive cost matrix as part of repeated generation of the cost matrix, reusing the cost matrix for each actual measurement already stored in previous session’s cost matrix in order to drastically reduce the amount of computation (Page 10). More specifically, Seo teaches A method comprising:
generating, by a batch analytic system [“terminal positioning device 100” is a general purpose computer as in Ma] , position determination, using a first Dynamic Time Warping (DTW) matrix [“cost matrix of FIG. 2 stored in advance by calculating all distances”] and a second DTW matrix [“in the present invention, the cost matrix shown in FIG. 3 is stored/stored so that it can be reused at the next terminal location.” The reused cost matrix], wherein the second DTW matrix is determined based on the first DTW matrix (Pages 10-11).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to (1) combine Seo and Ma because they both related to similar problem solving area to the claimed invention, namely calculating of the computationally expensive cost matrix in a computing device having a large storage capacity and (2) modify the method of Ma’s online aligning to generate the batch representation using a second DTW matrix that is generated by reusing information of the prior generated first DTW matrix as in Seo that reuses cost matrix rather than computing new cost matrix in every iteration. Doing so the computational burden during calculating of the DTW cost matrix in its iterative online batch aligning can be drastically reduced (Seo page 10). Thus, the generated batch representation of Ma and Seo would be by using a first Dynamic Time Warping (DTW) matrix and a second DTW matrix, where the second DTW matrix is computed using the information already calculated for the first DTW matrix. Accordingly, Ma in view of Seo teaches each elements of the claim and renders invention of this claim obvious to PHOSITA.
Regarding claims 15, Ma in view of Seo teaches the method of claim 11, wherein generating the batch representation [the aligned online batch data using DTW algorithm] corresponding to the sample point of the batch includes:
determining a warping path [“Finding the optimal warping path on the grid by backtracking from point to point following the lowest values in the grid in a monotonic fashion”] between a first sequence [the samples of loaded batch data for aligning as in Ste 102 of Castillo] including the set of samples associated with the batch at the sample point and a third sequence [samples of the portion of “corresponding portion of the reference batch”] including the batch portion of the reference batch based on the second DTW matrix, wherein the warping path maps each sample of the batch in the first sequence to one or more samples of the batch portion of the reference batch in the third sequence and maps each sample of the batch portion of the reference batch in the third sequence to one or more samples [computed elements of DTW grid/matrix that fall into the warping path] of the batch in the first sequence; and determining one or more representation samples based on the set of samples associated with the batch at the sample point in the first sequence and the warping path, wherein each representation sample corresponds to a respective sample point associated with a sample in the batch portion of the reference batch and the one or more representation samples form the batch representation corresponding to the sample point of the batch (Castillo (part of the MA), Fig. 1A, 1D [0188]).
Regarding claim 16, Ma in view of Seo teaches/suggests the method of claim 11, further comprising: determining, by the batch analytic system based on the first DTW matrix, a different DTW matrix [using of the stored DTW matrix again (with the technique of Seo) in 3rd or4th iterations when more samples are collected during “online dynamic alignment” and the percentage of the completion increases and trying to align batch data at another percentage completion such as about to reaching 90% percentage] between a different sequence including a set of samples associated with the batch at a different sample point subsequent to the sample point and a second sequence including a set of samples associated with the reference batch; and generating, by the batch analytic system, a batch representation [aligned batch at greater percentage of completion than that in claim 11] corresponding to the different sample point of the batch using the different DTW matrix (Ma, [091, 0103] & Seo pages 9-10).
Claim(s) 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ma in view of Seo as applied to claim 11 above, and further in view of Blevins (US 20110288837 A1).
Regarding claim 18, Ma in view of Seo teaches the method of claim 11, wherein performing the operation using the batch representation corresponding to the sample point of the batch including generating of the PCA models.
However, Ma in view of Seo fails to teach performing the operation using the batch representation corresponding to the sample point of the batch includes:
determining an anomaly metric corresponding to the sample point of the batch using the batch representation corresponding to the sample point of the batch and a PCA model of the industrial process corresponding to a reference sample point.
Blevins teaches a method comprising:
generating, by the batch analytic system batch representation and performing, by the batch analytic system, an operation using the batch representation, wherein performing the operation using the batch representation corresponding to the sample point of the includes determining an anomaly metric corresponding to the sample point of the batch using the batch representation corresponding to the sample point of the batch and a PCA model [As is known, the PCA modeling technique develops a set of principle components for the batch modeling data and PCA model matrix, which can then be used to analyze other batch data] of the industrial process corresponding to a reference sample point ([010, 079-082], Fig. 3).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to (1) combine Blevins and ma in view of Seo because they both related to generating PCA models using the aligned batch data sets and (2) modify the method of Ma in view of Seo to include missing limitations as in Blevins. Doing so would allow the generated PCA models of the Ma based on the aligned batch data can be used for fault detection and prediction of quality parameters (Blevins [011]).
Allowable Subject Matter
Claim 12- 14 & 17 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph and 35 U.S.C. 101, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
1) Palmer (WO 2012092649 A1) teaches an optional second limitation of claim 6 (i.e., determining a production rate [“the average production rate can be calculated for a prescribed or selected period or duration of time”] of the non-anomalous batch based on a total amount of products generated during the non-anomalous batch and a batch duration of the non-anomalous batch) ([085]).
2) Cinar (US 20160354543 A1) teaches glucose trajectories are aligned based on a reference batch (Batch 12) such that they have same length and similar profiles ([0186]).
3) Lu (US 20200250413 A1) discloses determining warping path while aligning first sequence and second sequence (Fig. 4, [052]).
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/SANTOSH R POUDEL/ Primary Examiner, Art Unit 2115
1 See Castillo (US 2019/0332101 A1, Fig. 1A).
2 See e.g., Castillo (US 2019/0332101 A1 for collecting data in online mode para. 007, 0182)
3 Claim requires only one option.
4 see US 20200250413 A1, fig. 4, [060] as additional details about how DTW algorithm works
5 “See U.S. patent application Ser. No. 15/967,099, entitled “Computer System and Method For Automated Batch Data Alignment In Batch Process Modeling, Monitoring And Control” the contents of which are incorporated herein by reference in their entirety…. or both offline batch data alignment for modeling and online batch data alignment for process monitoring and control.” and “additional hyperparameters that may be employed in embodiments are described in U.S. patent application Ser. No. 15/967,099, the contents of which are herein incorporated by reference”. Hence, the disclosure of US No. 15/967,099 or US 20190332101 A1 to Castillo are part of the disclosure of Ma.
6 See US 20150346834 A1 to Martinez, para. [0181-0186: “DTW algorithm generally requires O(N̂ 2), N being the number of sequence samples.”]
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