DETAILED ACTION
The following is a Final Office Action in response to the Amendment/Remarks received on 7 August 2026. Claims 1 and 4-7 have been amended. Claims 1-7 are pending in this application.
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 .
Response to Arguments
Applicant’s arguments, see Remarks, pg. 6, filed 7 August 2026, with respect to objected claims 4 and 6 have been fully considered and are persuasive in light of the claim amendments filed on 7 August 2026. The objections of claims 4 and 6 have been withdrawn.
Applicant's arguments, see Remarks, pgs. 6-8, filed 7 August 2026, with respect to rejected claims 1-7 under 35 U.S.C. 101 have been fully considered but they are not persuasive.
With respect to the applicant’s argument,
As a first consideration, independent claims 1 and 6 have been amended to recite that "a recipe for the semiconductor process includes at least hundreds of processing steps using a plurality of processing equipment." Applicant submits that this limitation pervades all other limitations such that they cannot practically be performed in the human mind. The human mind is not equipped to do all the following, as a comprehensive approach to such a large number of processing steps and equipment: (i) compute transition probabilities for hundreds of processing steps; (ii) aggregate the transition probabilities; (iii) identify an anomalous sequence based on the transition probabilities; (iv) then go back to evaluate the individual transition probabilities for each step of the anomalous sequence; (v) and finally, identify the specific transition(s) that account(s) for the anomalous sequence. See SRI Int 'l, Inc. v. Cisco Systems, Inc., 930 F.3d 1295, 1304 (Fed. Cir. 2019) (declining to identify the claimed collection and analysis of network data as abstract because "the human mind is not equipped to detect suspicious activity by using network monitors and analyzing network packets as recited by the claims"). (see Remarks, pg. 7, paragraph 3)
The examiner respectfully disagrees.
The applicant’s argument is moot in light of the current 35 U.S.C. 101 rejection of claim 1 below. The examiner respectfully notes the none of the limitations are currently identified as belonging to the abstract grouping of “Mental Processes”. Hence, the applicant’s argument is found unpersuasive.
In regards to the applicant’s argument,
Additionally, applicant submits that claim 1 reflects an improvement in the technical field of anomaly detection, and more specifically, an improvement in the functioning of a computer programmed to detect anomalies. The specification sets forth specific technical details explaining how to implement the multi-step complex method to obtain and evaluate data for at least hundreds of processing steps. (Specification, at ¶¶ 0015 - 0018). These details are also set forth in dependent claim 3-4. (see Remarks, pg. 8, paragraph 3)
The examiner respectfully disagrees.
The applicant has only set forth a broad and conclusionary statement the claimed combination of limitations provided an advantage of use (i.e. a benefit of “… claim 1 reflects an improvement in the technical field of anomaly detection, and more specifically, an improvement in the functioning of a computer programmed to detect anomalies”) and not an improvement (i.e. an enhancement) to the functioning of a computer or an improvement to any other technology or technical field (per MPEP 2106.05(a)(II); i.e. “anomaly detection”). In addition, the applicant has merely set forth a citations from the specification directed to how the claimed invention is implemented, without providing any arguments/rationales/evidence to what improvement (i.e. enhancement) is made to the functioning of a computer or to another technology or technical field (see MPEP 2106.05(a)(II); i.e. “anomaly detection”) by the previously presented and newly presented elements. Therefore, the applicant’s argument is found unpersuasive since the claims are directed to an abstract idea and the additional elements neither integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea (Step 2A, prong two of the subject matter eligibility requirement) nor provide significantly more than the abstract idea (Step 2B of the subject matter eligibility requirement). Hence, the applicant’s argument is found unpersuasive.
With respect to the applicant’s arguments,
Claims 2-5 are dependent from claim 1 and, for the same reasons, recite patentable subject matter. Independent claim 6 also recites patentable subject matter, for all the same reasons as claim 1. Claim 7 is dependent from claim 6 and, for the same reasons, recites patentable subject matter. (see Remarks, pgs. 8, paragraph 4)
The examiner respectfully disagrees.
The Examiner refers to the above response, pg. 2, paragraph 4 - pg. 3, paragraph 5 of this Office action, and the arguments herein as addressed.
Claims 1-7 stand rejected under 35 U.S.C. 101.
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 1-7 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1:
At step 1, the claim recites a method for comprising of a plurality of “actions”; and therefore is a process, which is a statutory category of invention.
At step 2A, prong one the claim recites “(c) computing, by the trained MLM based on the equipment history data, a plurality of transition probabilities for a production run of the semiconductor process, each transition probability representing wafer quality at each of a plurality of transitions between processing steps for each of the plurality of different processing sequences”; “(d) aggregating, by the trained MLM, each of the plurality of computed transition probabilities for each of the plurality of different processing sequences”; “(e) identifying, by the trained MLM based on the transition probabilities, at least one processing sequence of the plurality of different processing sequences as having an anomalous quality result”; “(f) evaluating, by the trained MLM, each of the computed transition probabilities for the at least one processing sequence”; “(g) determining, by the trained MLM based on the computed transition probabilities, that a specific transition of the plurality of transitions for the at least one processing sequence from a first piece of processing equipment to a second piece of processing equipment accounts for the anomalous quality result”; and “(h) determining, by the MLM based on the equipment history, a root cause of the anomalous quality result for the specific transition”.
The limitation of “(c) computing, by the trained MLM based on the equipment history data, a plurality of transition probabilities for a production run of the semiconductor process, each transition probability representing wafer quality at each of a plurality of transitions between processing steps for each of the plurality of different processing sequences”, as drafted, is a process performed by use of a mathematical calculation(s).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitations per use of mathematical calculations, then it falls within the “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The limitation of “(d) aggregating, by the trained MLM, each of the plurality of computed transition probabilities for each of the plurality of different processing sequences”, as drafted, is a process performed by use of a mathematical calculation(s).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitations per use of mathematical calculations, then it falls within the “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The limitation of “(e) identifying, by the trained MLM based on the transition probabilities, at least one processing sequence of the plurality of different processing sequences as having an anomalous quality result” , as drafted, is a process performed by use of a mathematical calculation(s).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitations per use of mathematical calculations, then it falls within the “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The limitation of “(f) evaluating, by the trained MLM, each of the computed transition probabilities for the at least one processing sequence”, as drafted, is a process performed by use of a mathematical calculation(s).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitations per use of mathematical calculations, then it falls within the “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The limitation of “(g) determining, by the trained MLM based on the computed transition probabilities, that a specific transition of the plurality of transitions for the at least one processing sequence from a first piece of processing equipment to a second piece of processing equipment accounts for the anomalous quality result”, as drafted, is a process performed by use of a mathematical calculation(s).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitations per use of mathematical calculations, then it falls within the “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The limitation of “(h) determining, by the MLM based on the equipment history, a root cause of the anomalous quality result for the specific transition”, as drafted, is a process performed by use of a mathematical calculation(s).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitations per use of mathematical calculations, then it falls within the “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
At step 2A, prong two, the judicial is not integrated into a practical application. In particular, the claim recites “(a) training, by a computer, the MLM based on input data and a selected training algorithm to generate a trained MLM, wherein the selected training algorithm includes a classification algorithm and an anomaly detection algorithm, and wherein the input data is equipment history data for a plurality of processing equipment used in a semiconductor process” and “(b) wherein a recipe for the semiconductor process includes plurality at least hundreds of processing steps using a plurality of processing equipment, selected ones of the plurality of processing steps having a plurality of parallel processing paths thereby forming a plurality of different processing sequences for performing the semiconductor process”.
The limitation of “(b) wherein a recipe for the semiconductor process includes plurality at least hundreds of processing steps using a plurality of processing equipment, selected ones of the plurality of processing steps having a plurality of parallel processing paths thereby forming a plurality of different processing sequences for performing the semiconductor process” is generally recited at a high level of generality and merely limits the abstract idea to a field of use. The courts have found “a claim directed to a judicial exception cannot be made eligible ‘simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use.’ Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.” (MPEP 2106.05(h)).
The limitations of “… a computer …”; “… a machine learning model (MLM) …”; and “… the trained MLM …” are recited at a high level of generality and recited so generically that they represent no more than mere instructions to apply the judicial exception on a computer component (see MPEP 2106.05(f)).
The limitation of “(a) training, by a computer, the MLM based on input data and a selected training algorithm to generate a trained MLM, wherein the selected training algorithm includes a classification algorithm and an anomaly detection algorithm, and wherein the input data is equipment history data for a plurality of processing equipment used in a semiconductor process” represents mere data gathering. The limitation of “training” is recited at a high level of generally and recited so generically it represents no more than an insignificant extra-solution activity of gathering data (see MPEP 2106.05(g)).
Accordingly, these additional elements neither individually nor in combination integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus, the claim is directed to an abstract idea.
At step 2B, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As previously discussed with respect to the integration of the abstract idea into a practical application, the addition of the elements of “… a computer …”; “… a machine learning model (MLM) …”; and “… the trained MLM …” amount to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. See MPEP 2106.05(d)(II), “Courts have held computer‐implemented processes not to be significantly more than an abstract idea (and thus ineligible) where the claim as a whole amounts to nothing more than generic computer functions merely used to implement an abstract idea, such as an idea that could be done by a human analog (i.e., by hand or by merely thinking).”
The limitation of “(b) wherein a recipe for the semiconductor process includes a plurality of processing steps using the processing equipment, selected ones of the plurality of processing steps having a plurality of parallel processing paths thereby forming a plurality of different processing sequences for performing the semiconductor process” merely limits the abstract idea to a field of use. Wherein, limiting the invention to a field of use cannot provide an inventive concept. Thus, the claim is not patent eligible. (MPEP 2106.05(h)).
The limitation of “(a) training, by a computer, the MLM based on input data and a selected training algorithm to generate a trained MLM, wherein the selected training algorithm includes a classification algorithm and an anomaly detection algorithm, and wherein the input data is equipment history data for a plurality of processing equipment used in a semiconductor process”, as discussed above, amounts to no more than mere data gathering. In addition, the limitation is well-understood, routine and conventional; wherein the courts have found limitations directed to obtaining data, recited at high level of generality, to be well-understood, routine and conventional. See MPEP 2106.05(d)(II), “storing and retrieving information in memory”.
Considering the additional elements individually and in combination and the claim as a whole, the additional elements do not provide significantly more than the abstract idea. The claim is not patent eligible.
Claim 2:
At step 2A, prong one the claim recites “… configuring the MLM based on a Markov chain stochastic model to evaluate each of the plurality of transitions as a plurality of state changes from one generalized state i representing one of the plurality of processing equipment to a next generalized state j representing a next one of the plurality of processing equipment in the respective processing sequence, with each of the plurality of processing sequences having a final state k at an end point of the semiconductor process”.
The limitation of “… configuring the MLM based on a Markov chain stochastic model to evaluate each of the plurality of transitions as a plurality of state changes from one generalized state i representing one of the plurality of processing equipment to a next generalized state j representing a next one of the plurality of processing equipment in the respective processing sequence, with each of the plurality of processing sequences having a final state k at an end point of the semiconductor process”, as drafted, is a process performed by use of a mathematical calculation(s).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitations per use of mathematical calculations, then it falls within the “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Claim 3:
At step 2A, prong one the claim recites “… for each of the plurality of state changes: (i) computing a fraction T1 equal to a first count of normal quality wafers that pass from state i to state j, divided by the sum of second counts of normal quality wafers that pass from state i to the final state k”; “… for each of the plurality of state changes: … (ii) computing a fraction T2 equal to a third count of off-quality wafers that pass from state i to state j, divided by the sum of fourth counts of off-quality wafers that pass from state i to the final state k”; “for each of the plurality of processing sequences, aggregating the plurality of state changes as a sum of log-odd transitions of the computed T1 fractions divided by the computed T2 fractions; wherein a positive aggregated sum indicates a likelihood of normal quality wafers from the corresponding processing sequence, and a more positive aggregated sum indicates a higher likelihood of normal quality wafers from the corresponding processing sequence; and wherein a negative aggregated sum indicates a likelihood of off-quality wafers from the corresponding processing sequence, and a more negative aggregated sum indicates a higher likelihood of off-quality wafers from the corresponding processing sequence”; and “evaluating the processing sequences that result in negative aggregated sums”.
The limitation of “… for each of the plurality of state changes: (i) computing a fraction T1 equal to a first count of normal quality wafers that pass from state i to state j, divided by the sum of second counts of normal quality wafers that pass from state i to the final state k”, as drafted, is a process performed by use of a mathematical calculation(s).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitations per use of mathematical calculations, then it falls within the “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The limitation of “… for each of the plurality of state changes: … (ii) computing a fraction T2 equal to a third count of off-quality wafers that pass from state i to state j, divided by the sum of fourth counts of off-quality wafers that pass from state i to the final state k; for each of the plurality of processing sequences”, as drafted, is a process performed by use of a mathematical calculation(s).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitations per use of mathematical calculations, then it falls within the “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The limitation of “for each of the plurality of processing sequences, aggregating the plurality of state changes as a sum of log-odd transitions of the computed T1 fractions divided by the computed T2 fractions; wherein a positive aggregated sum indicates a likelihood of normal quality wafers from the corresponding processing sequence, and a more positive aggregated sum indicates a higher likelihood of normal quality wafers from the corresponding processing sequence; and wherein a negative aggregated sum indicates a likelihood of off-quality wafers from the corresponding processing sequence, and a more negative aggregated sum indicates a higher likelihood of off-quality wafers from the corresponding processing sequence”, as drafted, is a process performed by use of a mathematical calculation(s).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitations per use of mathematical calculations, then it falls within the “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The limitation of “evaluating the processing sequences that result in negative aggregated sums”, as drafted, is a process performed by use of a mathematical calculation(s).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitations per use of mathematical calculations, then it falls within the “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Claim 4:
The limitations of claim 4 merely further detail “… fraction T1 …”; fraction T2”; and “aggregating the plurality of state changes as a sum of log-odd transitions of the computed T1 fractions divided by the computed T2 fractions ….” of claim 3; and is herein addressed for the rationale as set forth above in claim 3.
Claim 5:
At step 2A, prong one the claim recites “selecting the MLM from a group consisting of a Naïve Bayes classifier, a Markov chain, a hidden Markov model, and a recurrent neural network”.
The limitation of “selecting the MLM from a group consisting of a Naïve Bayes classifier, a Markov chain, a hidden Markov model, and a recurrent neural network”, as drafted, is a process, under its broadest reasonable interpretation covers performing the limitation by use of steps in organizing a human activit(ies).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitations by managing personal behavior (i.e. “selecting the MLM …”) using an instruction or rule (i.e. “… from a group consisting of a Naïve Bayes classifier, a Markov chain, a hidden Markov model, and a recurrent neural network”), then it falls within the sub-grouping of “C. Managing Personal Behavior or Relationships or Interactions Between People” of the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. (MPEP 2106.04(a)(2)(C)(II): “Finally, the sub-groupings encompass both activity of a single person (for example, a person following a set of instructions or a person signing a contract online) and activity that involves multiple people (such as a commercial interaction), and thus, certain activity between a person and a computer (for example a method of anonymous loan shopping that a person conducts using a mobile phone) may fall within the "certain methods of organizing human activity" grouping. It is noted that the number of people involved in the activity is not dispositive as to whether a claim limitation falls within this grouping. Instead, the determination should be based on whether the activity itself falls within one of the sub-groupings.”) Accordingly, the claim recites an abstract idea.
Claim 6:
At step 1, the claim recites a method for comprising of a plurality of “actions”; and therefore is a process, which is a statutory category of invention.
At step 2A, prong one the claim recites “for each transition event, computing by the MLM based on the equipment history, a first probability that normal quality wafers transition from a first state i representing a first one of the plurality of processing equipment to a second state j representing a next one of the plurality of processing equipment, and computing a second probability that off-quality wafers transition from the first state i to the second state j”; and “aggregating, by the MLM, the first and second probabilities for each of the plurality of transition events over a production run of the semiconductor process for the recipe”; “when production results of the production run indicate that a first path A1 of the plurality of parallel processing paths generated acceptable quality wafers, but that a second path A2 of the plurality of parallel processing paths generated off-quality wafers, and the aggregation of first and second probabilities produces MLM results that match the production results, then evaluating, by the MLM, the computed second probabilities for each transition from state i to state j along path A2”; “identifying, by the MLM based on the computed second probabilities along the path A2, at least one anomalous transition between the processing steps along the path A2”; and “determining, by the MLM based on the equipment history, a root cause of the anomalous transition”.
The limitations of “for each transition event, computing by the MLM based on the equipment history, a first probability that normal quality wafers transition from a first state i representing a first one of the plurality of processing equipment to a second state j representing a next one of the plurality of processing equipment, and computing a second probability that off-quality wafers transition from the first state i to the second state j”, as drafted, are processes performed by use of a mathematical calculation(s).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitations per use of mathematical calculations, then it falls within the “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The limitation of “aggregating, by the MLM, the first and second probabilities for each of the plurality of transition events over a production run of the semiconductor process for the recipe”, as drafted, is a process performed by use of a mathematical calculation(s).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitations per use of mathematical calculations, then it falls within the “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The limitation of “when production results of the production run indicate that a first path A1 of the plurality of parallel processing paths generated acceptable quality wafers, but that a second path A2 of the plurality of parallel processing paths generated off-quality wafers, and the aggregation of first and second probabilities produces MLM results that match the production results, then evaluating, by the MLM, the computed second probabilities for each transition from state i to state j along path A2”, as drafted, is a process performed by use of a mathematical calculation(s).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitations per use of mathematical calculations, then it falls within the “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
At step 2A, prong two, the judicial is not integrated into a practical application. In particular, the claim recites “… a machine learning model (MLM) …”; “…wherein a recipe for the semiconductor process includes at least hundreds of processing steps using a plurality of processing equipment, each processing step using one of the plurality of processing equipment, each one of the plurality of processing equipment having an equipment history, selected ones of the at least hundreds of processing steps having a plurality of parallel processing paths through selected ones of the processing equipment …”; and “training the machine learning model (MLM) to detect anomalous transitions between processing steps in the semiconductor process for the recipe by modeling the equipment history for the plurality of processing equipment used in the processing steps of the recipe as a sequence of a plurality of transition events from one state i to the next state j”.
The limitation of “…wherein a recipe for the semiconductor process includes at least hundreds of processing steps using a plurality of processing equipment, each processing step using one of the plurality of processing equipment, each one of the plurality of processing equipment having an equipment history, selected ones of the at least hundreds of processing steps having a plurality of parallel processing paths through selected ones of the processing equipment …” is generally recited at a high level of generality and merely limits the abstract idea to a field of use. The courts have found “a claim directed to a judicial exception cannot be made eligible ‘simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use.’ Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.” (MPEP 2106.05(h)).
The limitation of “… a machine learning model (MLM) …” is recited at a high level of generality and recited so generically that it represents no more than mere instructions to apply the judicial exception on a computer component (see MPEP 2106.05(f)).
The limitation of “training the machine learning model (MLM) to detect anomalous transitions between processing steps in the semiconductor process for the recipe by modeling the equipment history for the plurality of processing equipment used in the processing steps of the recipe as a sequence of a plurality of transition events from one state i to the next state j” represents mere data gathering. The limitation of “training” is recited at a high level of generally and recited so generically it represents no more than an insignificant extra-solution activity of gathering data (see MPEP 2106.05(g)).
Accordingly, these additional elements neither individually nor in combination integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus, the claim is directed to an abstract idea.
At step 2B, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As previously discussed with respect to the integration of the abstract idea into a practical application, the addition of the element of “… a machine learning model (MLM) …”, as discussed above, amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. See MPEP 2106.05(d)(II), “Courts have held computer‐implemented processes not to be significantly more than an abstract idea (and thus ineligible) where the claim as a whole amounts to nothing more than generic computer functions merely used to implement an abstract idea, such as an idea that could be done by a human analog (i.e., by hand or by merely thinking).”
The limitation of “…wherein a recipe for the semiconductor process includes at least hundreds of processing steps using a plurality of processing equipment, each processing step using one of the plurality of processing equipment, each one of the plurality of processing equipment having an equipment history, selected ones of the at least hundreds of processing steps having a plurality of parallel processing paths through selected ones of the processing equipment …” merely limits the abstract idea to a field of use. Wherein, limiting the invention to a field of use cannot provide an inventive concept. Thus, the claim is not patent eligible. (MPEP 2106.05(h)).
The limitation of “training the machine learning model (MLM) to detect anomalous transitions between processing steps in the semiconductor process for the recipe by modeling the equipment history for the plurality of processing equipment used in the processing steps of the recipe as a sequence of a plurality of transition events from one state i to the next state j”, as discussed above, amounts to no more than mere data gathering. In addition, the limitation is well-understood, routine and conventional; wherein the courts have found limitations directed to obtaining data, recited at high level of generality, to be well-understood, routine and conventional. See MPEP 2106.05(d)(II), “storing and retrieving information in memory”.
Considering the additional elements individually and in combination and the claim as a whole, the additional elements do not provide significantly more than the abstract idea. The claim is not patent eligible
Claim 7:
At step 2A, prong one the claim recites “… selecting the MLM from a group consisting of a Naïve Bayes classifier, a Markov chain, a hidden Markov model”.
The limitation of “… selecting the MLM from a group consisting of a Naïve Bayes classifier, a Markov chain, a hidden Markov model, and a recurrent neural network”, as drafted, is a process, under its broadest reasonable interpretation covers performing the limitation by use of steps in organizing a human activit(ies).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitations by managing personal behavior (i.e. “… selecting the MLM …”) using an instruction or rule (i.e. “… from a group consisting of a Naïve Bayes classifier, a Markov chain, a hidden Markov model, and a recurrent neural network”), then it falls within the sub-grouping of “C. Managing Personal Behavior or Relationships or Interactions Between People” of the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. (MPEP 2106.04(a)(2)(C)(II): “Finally, the sub-groupings encompass both activity of a single person (for example, a person following a set of instructions or a person signing a contract online) and activity that involves multiple people (such as a commercial interaction), and thus, certain activity between a person and a computer (for example a method of anonymous loan shopping that a person conducts using a mobile phone) may fall within the "certain methods of organizing human activity" grouping. It is noted that the number of people involved in the activity is not dispositive as to whether a claim limitation falls within this grouping. Instead, the determination should be based on whether the activity itself falls within one of the sub-groupings.”) Accordingly, the claim recites an abstract idea.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
The following references are cited to further show the state of the art with respect to manufacturing methods/systems and anomaly analysis methods/devices.
U.S. Patent Publication No. 2016/0148850 A1 discloses techniques for measuring and/or compensating for process variations in a semiconductor manufacturing processes.
U.S. Patent Publication No. 2021/0407866 A1 discloses a system for determining a cause of an abnormality in a semiconductor manufacturing process includes an abnormality mode determination module, a selection module, and a root cause analysis module.
U.S. Patent Publication No. 2024/0201673 A1 discloses a method, apparatus, and system with abnormality determination.
U.S. Patent Publication No. 2026/0126782 A1 discloses a method includes receiving, by a processing device, first sensor data generated by a plurality of sensors of a process chamber of a manufacturing system during execution of a fabrication process.
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