DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statements (IDSs) were submitted on 6/17/2024. The submissions are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “a provision unit”, “an acquisition unit”, “a comparison unit”, “a determination unit” and “an output unit” in claim 27, which are interpreted as described in Fig. 3 and its related descriptions (pages 2).
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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.
The current 35 USC 101 analysis is based on the current guidance (Federal Register vol. 79, No. 241. pp. 74618-74633). The analysis follows several steps. Step 1 determines whether the claim belongs to a valid statutory class. Step 2A prong 1 identifies whether an abstract idea is claimed. Step 2A prong 2 determines whether any abstract idea is integrated into a practical application. If the abstract idea is integrated into a practical application the claim is patent eligible under 35 USC 101. Last, step 2B determines whether the claims contain something significantly more than the abstract idea. In most cases the existence of a practical application predicates the existence of an additional element that is significantly more.
The 35 USC 101 analysis between each element of claims and its combination is presented in the table below
Claim number and elements
Judicial exception (Step 2A Prong one)
Practical application (Step 2A Prong two)/ Significantly more (Step 2B)
Claim 1
Step2A Prong one: Yes
Step 2A Prong two: No / Step 2B: No
A computer-implemented method for monitoring a plant, the plant being capable of:
- receiving one or more educts; and
- executing multiple processes in which the educts are processed, wherein each of the multiple executed processes is characterized by an associated set (Si) of process parameters (ai - di), wherein at least one of the process parameters (ai - di) evolves in time during execution of the executed process;
Step 1: Yes, statutory class
“receiving ~” and “executing ~” are insignificant extra-solution activity to collect routine and perform a generic function of a generic computer to execute processes.
the multiple processes are indicative of data processing and/or mathematical calculations performed by a mathematical algorithm.
an associated set (Si) of process parameters are mathematical concept/values.
wherein the method comprises:
- providing (Si) sets (Si) of process parameters (ai - di) associated with the multiple executed processes;
- acquiring (S2) a set (Sj) of process parameters of interest (aj - dj) associated with a process of interest from the multiple executed processes;
abstract idea
mental process or mathematical concept
“providing ~ acquiring~ “ is math/mental process.
- comparing (S3) the set (Sj) of process parameters of interest (aj - dj) and the remaining sets (Si) of process parameters (ai - di) associated with the remaining multiple executed processes to determine a similarity degree between the set (Sj) of process parameters of interest (aj - dj) and the remaining sets (Si) of process parameters (ai - di);
- determining (S4) at least one similar process from the remaining multiple executed processes, the similar process having a similarity degree that is equal to or greater than a similarity threshold; and
abstract idea
mental process or mathematical concept
“comparing ~ to determine a similarity degree … determining ~” is a math/mental processes to calculate the similarity degree based on the collected routine data. (Para 0142-0159 and 0165-0168)
the similarity degree is a math concept/value/degree resulted from mathematical calculations.
- outputting (S5) the set (Sj) of process parameters of interest (aj - dj) together with the set (Si) of process parameters (ai - di) associated with the determined at least one similar process.
abstract idea
mental process or mathematical concept
“outputting ~” is insignificant post solution activity to output the mathematical result, which may be performed by a generic computer function of a computer component.
1. Claims 1-27 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1-27 are directed to an abstract idea. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception as addressed below and presented in the above table.
Step 2A: Prong One
Regarding Claim 1, the limitations recited in Claim 1, as drafted, are processes that, under its broadest reasonable interpretation, cover performance of the limitation in the mathematical calculations and/or the mind, as presented in the above table. Nothing in the claim elements precludes the step from practically being performed in the mind and/or the mathematical calculations. For example, “providing (Si) sets (Si) of process parameters (ai - di) associated with the multiple executed processes; - acquiring (S2) a set (Sj) of process parameters of interest (aj - dj) associated with a process of interest from the multiple executed processes” in the context of this claim may encompass manually calculating or inferring the set (Sj) of process parameters of interest (aj - dj) based on routine data (i.e., the multiple executed processes) executed from the received routine data (i.e., one or more educts). Similarly, the limitations of “- comparing (S3) the set (Sj) of process parameters of interest (aj - dj) and the remaining sets (Si) of process parameters (ai - di) associated with the remaining multiple executed processes to determine a similarity degree between the set (Sj) of process parameters of interest (aj - dj) and the remaining sets (Si) of process parameters (ai - di); - determining (S4) at least one similar process from the remaining multiple executed processes, the similar process having a similarity degree that is equal to or greater than a similarity threshold” in the context of this claim may encompass manually calculating or inferring the similarity degree based on the calculated/inferred results (i.e., process parameters) from mathematical process (i.e., the comparing step) and further determining the similar mathematical process to calculated the similarity degree based on the similarity threshold, where the similarity degree is a mathematical concept/value/degree resulted from mathematical calculations. (See at least paragraphs 0142-0159 and 0165-0168 in US PG publication of the instant application).
Step 2A: Prong Two
This judicial exception is abstract ideal itself and not integrated into a practical application. In particular, the specification details use of a processor to perform the mathematical calculations using a mathematical algorithm and/or an arithmetic computer program to perform “providing (Si) sets (Si) of process parameters (ai - di) associated with the multiple executed processes; - acquiring (S2) a set (Sj) of process parameters of interest (aj - dj) associated with a process of interest from the multiple executed processes” and “- comparing (S3) the set (Sj) of process parameters of interest (aj - dj) and the remaining sets (Si) of process parameters (ai - di) associated with the remaining multiple executed processes to determine a similarity degree between the set (Sj) of process parameters of interest (aj - dj) and the remaining sets (Si) of process parameters (ai - di); - determining (S4) at least one similar process from the remaining multiple executed processes, the similar process having a similarity degree that is equal to or greater than a similarity threshold”.
The plant is an additional element recited at a high-level of generality to perform an insignificant pre-solution activity for merely gathering routine data (i.e., a signal and samples obtained or derived from it) and performing generic computer functions of a generic computer component. The limitations of “-receiving one or more educts; and - executing multiple processes in which the educts are processed, wherein each of the multiple executed processes is characterized by an associated set (Si) of process parameters (ai - di), wherein at least one of the process parameters (ai - di) evolves in time during execution of the executed process” are insignificant extra-solution activities to collect routine data (i.e., educts, parameters characterized for each executed process ) and perform a generic function of a generic computer to execute processes. The limitation of “- outputting (S5) the set (Sj) of process parameters of interest (aj - dj) together with the set (Si) of process parameters (ai - di) associated with the determined at least one similar process” is an insignificant extra-solution activity to output/display the mathematical result on a displayer, which may be performed by a generic computer function of a computer component. (See paragraph 0159 in US PG publication US 20250067630 A1 of the instant application). Claim 1 does not present tangible or physical elements/components and/or integration of improvements to be indicative of specific features/structure/acts, for example, how and or with what to determine the similarity degree, and/or the set of process parameters. (See MPEP 2106.04(d)). There is no showing of integration into a practical application such as an improvement to the functioning of a computer, or to any other technology or technical field, or use of a particular machine.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The limitations of “-receiving one or more educts; and - executing multiple processes in which the educts are processed, wherein each of the multiple executed processes is characterized by an associated set (Si) of process parameters (ai - di), wherein at least one of the process parameters (ai - di) evolves in time during execution of the executed process” are insignificant extra-solution activities to collect routine data (i.e., educts, parameters characterized for each executed process ) and perform a generic function of a generic computer to execute processes. The limitation of “- outputting (S5) the set (Sj) of process parameters of interest (aj - dj) together with the set (Si) of process parameters (ai - di) associated with the determined at least one similar process” is an insignificant extra-solution activity to output/display the mathematical result on a displayer, which may be performed by a generic computer function of a computer component. (See paragraph 0159 in US PG publication US 20250067630 A1 of the instant application). As discussed above, with respect to integration of the abstract idea into a practical application, using the processor to perform “providing (Si) sets (Si) of process parameters (ai - di) associated with the multiple executed processes; - acquiring (S2) a set (Sj) of process parameters of interest (aj - dj) associated with a process of interest from the multiple executed processes” and “- comparing (S3) the set (Sj) of process parameters of interest (aj - dj) and the remaining sets (Si) of process parameters (ai - di) associated with the remaining multiple executed processes to determine a similarity degree between the set (Sj) of process parameters of interest (aj - dj) and the remaining sets (Si) of process parameters (ai - di); - determining (S4) at least one similar process from the remaining multiple executed processes, the similar process having a similarity degree that is equal to or greater than a similarity threshold” amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept cannot provide statutory eligibility. Claim 1 is not patent eligible.
Regarding Claims 2-26, the limitations are further directed to an abstract idea, as described in claim 1. The limitations of “a time series-based similarity search by means of calculating Euclidean Distances and Correlations on time series data or by Dynamic Time Warping (DTW) algorithms, in order to identify processes, or process steps, based on at least one example process data set for process parameter time series” in claim 2, “an identification of time phases of high or low interests by rules or similarity on one or more process parameters and/or a similarity search based on the difference between the process parameter of interest and the corresponding process parameter of the similar process and/or a decomposition based on an additive time series analysis” in claim 3, “determining (S6), for each process parameter of interest, a deviation value indicating a difference between the process parameter of interest and the corresponding process parameter of the similar process … wherein the deviation value is determined based on additional time-corresponding derivations for each process parameter of interest and wherein these derivations comprise slope over time comparisons and/or time frame comparisons for action indications and/or length of time frame comparisons and/or time phase comparisons with corresponding reference deviation values for such time derivations” in claims 5 and 6, “- determine whether each process parameter of interest (aj - dj) is within the range included in the optimal process parameter information; and - if one process parameter of interest (aj - dj) is outside the range included in the optimal process parameter information, determine an abnormality with said process parameter (aj - dj)” in claim 11 may encompass mathematical processes related to calculating the similarity degree and inferring the determination of the similar process and abnormality (MPEP 2106.04(a)(2)). The limitations recited in claims 8 to 10 and 12-13 may encompass manually calculating or inferring the abnormality based on the calculated/inferred results (i.e., the determined deviation value and the predetermined abnormality threshold). The limitations recited in claim 14 may encompass mathematical calculation related to the comparing step for manually calculating or inferring the similarity degree. (See at least paragraphs 0142-0159 and 0165 and 0168 in US PG publication of the instant application). The limitations recited in claims 23-24 may encompass mathematical calculation related to subdividing the process of interest into process of interest parts and comparing the process parameters (See at least paragraphs 0142-0159 and 0165 and 0168 in US PG publication of the instant application). The limitations related to “extracting the sets (Si) of process parameters (ai - di) … comparing the process parameters (ai - di) from the received process parameter information …” in claim 25 may encompass mathematical calculation the comparing step for manually calculating or inferring the similarity degree.
The limitations recited in claims 15-19 may encompass manually mathematical calculations or inferring related to classifying the normal process, where the artificial intelligence algorithm is indicative of mathematical software algorithm to perform arithmetic functions of the generic computer.
The limitations of “visually outputting an evolution in time of the at least one process parameter of interest evolving in time superimposed with and/or besides an evolution in time of a corresponding at least one process parameter evolving in time of the similar process” in claim 4, “visually indicating (S7), for each process parameter of the similar process, the determined deviation value” in claim 7 are an insignificant extra-solution activity to output/display the mathematical result on a displayer, which may be performed by a generic computer function of a computer component. (See paragraph 0159 in US PG publication US 20250067630 A1 of the instant application). The limitations of “- storing an optimal process parameter information indicating a range in which the process parameters of interest (aj - dj) are expected” in claim 11, “- receiving, from the plant [[(1)]], the process parameters information indicating a time evolution of the process parameters (ai - di) used during execution of the multiple processes; - storing, in the database, a process start information characterizing a start of a process, a process end information characterizing an end of the process and optionally a process step information characterizing a specific step of the process” in claim 25 are an insignificant extra-solution activity to perform a generic computer function of a computer component related to storing data. For the reasons described above with respect to Claim 1, the judicial exceptions are not meaningfully integrated into a practical application, or amount to significantly more than the abstract idea.
Regarding Claim 27, it is a device type claim, reciting all the limitations as of claim 1 above. Therefore, it is rejected under the same rationale as of claim 1 above. The additional elements of “a provision unit”, “an acquisition unit”, “a comparison unit”, “a determination unit” and “an output unit” are high level of generalities to perform generic computer functions of a generic computer component.
2. Claim 26 is rejected under 35 U.S.C. 101 because the claimed invention of “a computer program product” recited in claim 26 is directed to nonstatutory subject matter. The claim does not fall within at least one of the four categories of patent eligible subject matter because the claim invention is directed to a software per se which is not directed to any of the statutory categories. (MPEP 2106.03. I).
Non-limiting examples of claims that are not directed to any of the statutory categories include:
• Products that do not have a physical or tangible form, such as information (often referred to as "data per se") or a computer program per se (often referred to as "software per se") when claimed as a product without any structural recitations; (MPEP 2106.03. I)
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 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.
Claims 1, 26-27 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Grimm et al. (US 20190219992 A1, hereinafter referred to as “Grimm”, cited in IDS dated 06/17/2024).
Regarding Claim 1, Grimm teaches a computer-implemented method for monitoring a plant (Fig. 5), the plant being capable of:
- receiving one or more educts (at least paragraphs 0001-0004 and claim 1 teaches receiving a set of characterizing process parameters that characterize the process); and
- executing multiple processes in which the educts are processed, wherein each of the multiple executed processes is characterized by an associated set (Si) of process parameters (ai - di), wherein at least one of the process parameters (ai - di) evolves in time during execution of the executed process (at least paragraphs 0001-0004 and claim 1 teaches each of the stored sets of process parameters is associated with a successful trajectory of a respective one of the processes performed according to the respective set process parameters);
wherein the method comprises:
- providing (Si) sets (Si) of process parameters (ai - di) associated with the multiple executed processes (at least paragraphs 0018-0021, in particular, claim 1 teaches “providing a database, the database storing sets of process parameters to control and monitor respective ones of a plurality of processes performed in order to produce products”);
- acquiring (S2) a set (Sj) of process parameters of interest (aj - dj) (paragraph 0022, “characterizing parameters”) associated with a process of interest from the multiple executed processes (at least paragraph 0022, in particular, claim 1 teaches “providing a database, the database storing sets of process parameters to control and monitor respective ones of a plurality of processes performed in order to produce products wherein each of the stored sets of process parameters is associated with a successful trajectory of a respective one of the processes performed according to the respective set process parameters, wherein each successful trajectory is a time-based profile of measurements recorded during performance of the respective process ”);
- comparing (S3) the set (Sj) of process parameters of interest (aj - dj) and the remaining sets (Si) of process parameters (ai - di) associated with the remaining multiple executed processes to determine a similarity degree between the set (Sj) of process parameters of interest (aj - dj) and the remaining sets (Si) of process parameters (ai - di) (at least paragraphs 0023, 0030-0031 and 0266, in particular, claims 1-2 teaches specifying the similarity degree between the sets of process parameters, “the specified degree of similarity may be specified via a variable or an external function. The degree of similarity between the stored sets of process parameters and the characterizing process parameters may be determined by comparing a numerical description of the process being controlled and monitored with the numerical descriptions of the respective processes performed according to the stored sets of process parameters.” and “identifying a first set process parameters from the stored sets of process parameters, the first set of process parameters having a specified degree of similarity to the set of characterizing process parameters, wherein the first set of process parameters is associated with a first successful trajectory, controlling and monitoring the process using the first successful trajectory …. comparing the estimated trajectory with the first successful trajectory; when a difference between the estimated trajectory and the first successful trajectory fails a confidence criterion, comparing the recorded measurements and the set of characterizing process parameters to a plurality of the stored sets of process parameters”);
- determining (S4) at least one similar process from the remaining multiple executed processes, the similar process having a similarity degree that is equal to or greater than a similarity threshold (at least paragraphs 0023, 0030-0031 and 0266, in particular, claim 2 teaches “determining, based on the comparison, whether a second set of process parameters from the plurality of stored sets of process parameters has a greater degree of similarity to the set of characterizing process parameters and the recorded measurements than the first set of process parameters;”); and
- outputting (S5) the set (Sj) of process parameters of interest (aj - dj) together with the set (Si) of process parameters (ai - di) associated with the determined at least one similar process (at least paragraphs 0021, 0024 and 0266, teaches curve or graph to describe an associated process, “Each trajectory may be implemented as a curve or graph that describes an associated process”, “provide an overview of associated process data”, “the controlling and monitoring of the process may be carried out using the first successful trajectory and the first set of process parameters/values”).
Regarding Claim 26, it is a computer program product claim, dependent on claim 1 and having similar limitations as of claim 1 above. Therefore, it is rejected under the same rationale as of claim 1 above.
Regarding Claim 27, it is a device type claim having similar limitations as of claim 1 above. Therefore, it is rejected under the same rationale as of claim 1 above.
Citation of Pertinent Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
FANIDAKIS et al. (WO 2021156157 A1) teaches a method comprising a plurality of sensors, and one or more functionally connected processing units, the method comprising: providing, at any of the one or more processing units, time-series residual data of a sensor object; the sensor object being a group of at least some of the sensors from the plurality of sensors, and wherein the residual data comprises, for each of the sensors of the sensor object, a residue signal which is a difference between the sensor's measured output and the sensor's expected output, monitoring, via any of the one or more processing units, a level signal; wherein the level signal is indicative of a collective time-based variation of the time-series residual data, monitoring, via any of the one or more processing units, an association signal; wherein the association signal is indicative of the variation and/or association structure of the time-series residual data, generating, via any of the one or more processing units, an anomaly event signal when at a given time a value of the level signal and/or a value of the association signal changes from an expected value of the respective signal at or around that time. The present teachings also relate to a monitoring and/or control system for a plant comprising a plurality of sensors, wherein the system comprises one or more processing units configured to perform the method steps of any of the steps herein disclosed, and a computer software product.
Conclusion
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/BYUNG RO LEE/Examiner, Art Unit 2858
/LEE E RODAK/Supervisory Patent Examiner, Art Unit 2858
