DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1 – 3, 7 – 10, and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Martin et al. US 2022/0092112 (hereinafter Martin) in view of MOCHTY et al. US 2025/0021935 (hereinafter MOCHTY).
Regarding claim 1, Martin teaches: a method, comprising:
receiving, via graphical user interface (GUI) of a processing system, a selection of a dataset associated with one or more operations of one or more industrial automation components of an industrial system ([0014] - - interactive graphical user interfaces; [0002] - - data samples from sensors in a plant or factory);
receiving, via the GUI of the processing system, a set of input variables associated with the dataset ([0004] - - user selecting one or more features as input);
receiving, via the GUI of the processing system, a target variable associated with the dataset ([0004] - - user selecting a feature as a target);
receiving, via the GUI of the processing system, a model type for analyzing the dataset ([0004] - - user selecting a type of model);
determining, via the processing system, a contribution of each of the set of input variables to the target variable based on the model type ([0098] - - identify correlation in the data is determining contribution);
But Martin does not explicitly teach:
generating, via the processing system, a visualization representative of one or more statistical relationships between each of the set of input variables and the target variable based on the contribution of each of the set of input variables to the target variable.
However, MOCHTY teaches:
generating, via the processing system, a visualization representative of one or more statistical relationships between each of the set of input variables and the target variable based on the contribution of each of the set of input variables to the target variable (Fig. 2B, [0161] - - a solar correlation representation shows statistical relationships between response variable and other variables; the response variable is a target variable).
Martin and MOCHTY are analogous art because they are from the same field of endeavor. They all relate to user interface for data processing.
Therefore before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by Martin, and incorporating visualization representative of statistical relationships, as taught by MOCHTY.
One of ordinary skill in the art would have been motivated to do this modification in order to improve interactive user interface for a time series planning, evaluation and prediction system, as suggested by MOCHTY ([0016]).
Claim 8 is substantially similar to claim 1 and is rejected for the same reasons and rationale as above.
Regarding claim 2, the combination of Martin and MOCHTY teaches all the limitations of the base claims as outlined above.
Martin further teaches: receiving, via the GUI of the processing system, one or more inputs to adjust one or more values of one or more input variables of the set of input variables ([0119] - - changes of the selected plots from the model input charts);
generating, via the processing system, a predicted value for the target variable based on the one or more inputs ([0119] - - generate and display output of the model based on the inputs; output of the model is predicted value for the targe variable); and
displaying, via GUI of the processing system, the predicted value ([0119] - - the first and second plot of the model output chart temporally aligned and updated in real-time in response to changes of the selected plots from the model input charts).
Claim 9 is substantially similar to claim 2 and is rejected for the same reasons and rationale as above.
Regarding claim 3, the combination of Martin and MOCHTY teaches all the limitations of the base claims as outlined above.
MOCHTY further teaches: the one or more inputs correspond to one or more slide visualizations associated with the one or more input variables ([0066] - - a slider).
Martin and MOCHTY are combinable for the same rationale as set forth.
Claim 10 is substantially similar to claim 3 and is rejected for the same reasons and rationale as above.
Regarding claim 7, the combination of Martin and MOCHTY teaches all the limitations of the base claims as outlined above.
Martin further teaches: the model type comprises a classification model type or a regression model type ([0030] - - regression models, classification models).
Claim 14 is substantially similar to claim 7 and is rejected for the same reasons and rationale as above.
Claims 4, 5, 11, 12, 15 – 18 are rejected under 35 U.S.C. 103 as being unpatentable over Martin et al. US 2022/0092112 (hereinafter Martin) in view of MOCHTY et al. US 2025/0021935 (hereinafter MOCHTY) and further in view of SUN et al. US 2025/0044749 (hereinafter SUN).
Regarding claim 4, the combination of Martin and MOCHTY teaches all the limitations of the base claims as outlined above.
But the combination of Martin and MOCHTY does not explicitly teach:
determining, via the processing system, one or more commands to adjust one or more operations of the one or more industrial automation components based on the one or more statistical relationships; and
sending, via the processing system, the one or more commands to the one or more industrial automation components.
However, SUN teaches:
determining, via the processing system, one or more commands to adjust one or more operations of the one or more industrial automation components based on the one or more statistical relationships; and
sending, via the processing system, the one or more commands to the one or more industrial automation components ([0013] - - performing an action based on the generated predictions or insights; [0015] - - the action causing an operating parameter of the industrial process to be adjusted).
Martin, MOCHTY and SUN are analogous art because they are from the same field of endeavor. They all relate to data processing.
Therefore before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by the combination of Martin and MOCHTY, and incorporating taking actions based on prediction, as taught by SUN.
One of ordinary skill in the art would have been motivated to do this modification in order to improve system performance, as suggested by SUN ([0099]).
Claim 11 is substantially similar to claim 4 and is rejected for the same reasons and rationale as above.
Regarding claim 5, the combination of Martin and MOCHTY teaches all the limitations of the base claims as outlined above.
But the combination of Martin and MOCHTY does not explicitly teach:
receiving, via the GUI of the processing system, one or more causal analysis inputs for generating a causal analysis graph, wherein the one or more causal analysis inputs are selected from the set of input variables.
receiving, via the GUI of the processing system, a treatment for generating the causal analysis graph; and
generating, via the GUI of the processing system, a causal graph representative of one or more strengths of one or more input variables that correspond to the one or more causal analysis inputs with respect to the target variable.
However, SUN teaches:
receiving, via the GUI of the processing system, one or more causal analysis inputs for generating a causal analysis graph, wherein the one or more causal analysis inputs are selected from the set of input variables (Fig. 1, [0080] - - process graph are inputs).
receiving, via the GUI of the processing system, a treatment for generating the causal analysis graph (Fig. 1, [0080] - - each processing stage corresponding to a physical activity which is a treatment); and
generating, via the GUI of the processing system, a causal graph representative of one or more strengths of one or more input variables that correspond to the one or more causal analysis inputs with respect to the target variable (Fig. 2, [0089] - - causal network data overlaid on the process graph; [0209]-[0211] - - path strength, the strength of dependency between variables).
Martin, MOCHTY and SUN are analogous art because they are from the same field of endeavor. They all relate to data processing.
Therefore before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by the combination of Martin and MOCHTY, and incorporating causal graph, as taught by SUN.
One of ordinary skill in the art would have been motivated to do this modification in order to provide meaningful and actionable insights for the processes, as suggested by SUN ([0010]).
Claim 12 is substantially similar to claim 5 and is rejected for the same reasons and rationale as above.
Regarding claim 15, Martin teaches: non-transitory computer-readable medium comprising computer-executable instructions that, when executed, are configured to cause a processing system to perform operations comprising:
receiving, via graphical user interface (GUI) of the processing system, a selection of a dataset associated with one or more operations of one or more industrial automation components of an industrial system, wherein the dataset is associated with one batch of a plurality of batches associated with the industrial system ([0014] - - interactive graphical user interfaces; [0002] - - data samples from sensors in a plant or factory);
receiving, via the GUI, a set of input variables associated with the dataset ([0004] - - user selecting one or more features as input);
receiving, via the GUI, a target variable associated with the dataset ([0004] - - user selecting a feature as a target);
receiving, via the GUI, a model type for analyzing the dataset ([0004] - - user selecting a type of model);
determining, via the processing system, a contribution of each of the set of input variables to the target variable based on the model type ([0098] - - identify correlation in the data is determining contribution);
But Martin does not explicitly teach:
generating, via the processing system, a visualization representative of one or more statistical relationships between each of the set of input variables and the target variable based on the contribution of each of the set of input variables to the target variable;
However, MOCHTY teaches:
generating, via the processing system, a visualization representative of one or more statistical relationships between each of the set of input variables and the target variable based on the contribution of each of the set of input variables to the target variable (Fig. 2B, [0161] - - a solar correlation representation shows statistical relationships between response variable and other variables; the response variable is a target variable).
Martin and MOCHTY are analogous art because they are from the same field of endeavor. They all relate to user interface for data processing.
Therefore before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify the above medium, as taught by Martin, and incorporating visualization representative of statistical relationships, as taught by MOCHTY.
One of ordinary skill in the art would have been motivated to do this modification in order to improve interactive user interface for a time series planning, evaluation and prediction system, as suggested by MOCHTY ([0016]).
But the combination of Martin and MOCHTY does not explicitly teach:
determining, via the processing system, one or more commands for adjusting one or more operations of the one or more industrial automation components based on the one or more statistical relationships; and
sending, via the processing system, the one or more commands to the one or more industrial automation components.
However, SUN teaches:
determining, via the processing system, one or more commands to adjust one or more operations of the one or more industrial automation components based on the one or more statistical relationships; and
sending, via the processing system, the one or more commands to the one or more industrial automation components ([0013] - - performing an action based on the generated predictions or insights; [0015] - - the action causing an operating parameter of the industrial process to be adjusted).
Martin, MOCHTY and SUN are analogous art because they are from the same field of endeavor. They all relate to data processing.
Therefore before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify the above medium, as taught by the combination of Martin and MOCHTY, and incorporating taking actions based on prediction, as taught by SUN.
One of ordinary skill in the art would have been motivated to do this modification in order to improve system performance, as suggested by SUN ([0099]).
Regarding claim 16, the combination of Martin, MOCHTY and SUN teaches all the limitations of the base claims as outlined above.
Martin further teaches: receiving, via the GUI of the processing system, one or more inputs to adjust one or more values of one or more input variables of the set of input variables ([0119] - - changes of the selected plots from the model input charts); wherein the one or more inputs comprise a sugar rate, a pH, a temperature, a pressure, a mixing speed, or any combination thereof ([0048] - - temperature, pressure PH, movement & etc.);
generating, via the processing system, a predicted value for the target variable based on the one or more inputs ([0119] - - generate and display output of the model based on the inputs; output of the model is predicted value for the targe variable); and
displaying, via GUI of the processing system, the predicted value ([0119] - - the first and second plot of the model output chart temporally aligned and updated in real-time in response to changes of the selected plots from the model input charts).
Regarding claim 17, the combination of Martin, MOCHTY and SUN teaches all the limitations of the base claims as outlined above.
MOCHTY further teaches: the one or more inputs correspond to one or more slide visualizations associated with the one or more input variables ([0066] - - a slider).
Martin, MOCHTY and SUN are combinable for the same rationale as set forth.
Regarding claim 18, the combination of Martin, MOCHTY and SUN teaches all the limitations of the base claims as outlined above.
Martin further teaches: the operations comprise storing the one or more statistical relationships in a central repository ([0083]-[0088] - - database system is a central repository).
Claims 6, 13, 19 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Martin et al. US 2022/0092112 (hereinafter Martin) in view of MOCHTY et al. US 2025/0021935 (hereinafter MOCHTY) and SUN et al. US 2025/0044749 (hereinafter SUN) and further in view of WATT et al. US 2023/0076243 (hereinafter WATT).
Regarding claim 6, the combination of Martin, MOCHTY and SUN teaches all the limitations of the base claims as outlined above.
SUN further teaches:
display, via the GUI of the processing system, the one or more causal scores ([0138] - - relevance scores of each path is obtained and displayed in table 1).
But the combination of Martin, MOCHTY and SUN does not explicitly teach:
receiving, via the GUI of the processing system, a refute method; and
determine, via the processing system, one or more causal scores associated with the one or more strengths based on the dataset and the refute method;
However, WATT teaches:
receiving, via the GUI of the processing system, a refute method ([0048] - - refutation tests) ; and
determine, via the processing system, one or more causal scores associated with the one or more strengths based on the dataset and the refute method ([0048] - - refutation tests are used to estimate the stability of the causal effect).
Martin, MOCHTY, SUN and WATT are analogous art because they are from the same field of endeavor. They all relate to data processing.
Therefore before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by the combination of Martin, MOCHTY and SUN, and incorporating refute method, as taught by WATT.
One of ordinary skill in the art would have been motivated to do this modification in order to improve risk assessments and management, as suggested by WATT ([0004]).
Claim 13 is substantially similar to claim 6 and is rejected for the same reasons and rationale as above.
Regarding claim 19, the combination of Martin, MOCHTY and SUN teaches all the limitations of the base claims as outlined above.
SUN further teaches:
receiving, via the GUI of the processing system, one or more causal analysis inputs for generating a causal analysis graph, wherein the one or more causal analysis inputs are selected from the set of input variables (Fig. 1, [0080] - - process graph are inputs).
receiving, via the GUI of the processing system, a treatment for generating the causal analysis graph (Fig. 1, [0080] - - each processing stage corresponding to a physical activity which is a treatment); and
generating, via the GUI of the processing system, a causal graph representative of one or more strengths of one or more input variables that correspond to the one or more causal analysis inputs with respect to the target variable (Fig. 2, [0089] - - causal network data overlaid on the process graph; [0209]-[0211] - - path strength, the strength of dependency between variables).
But the combination of Martin, MOCHTY and SUN does not explicitly teach: the treatment comprises a front-door way (FW), back-door adjustment, inverse probability weighting (IPW), instrumental variables (IV), etc.), a target variable designation, a causal strength target, or any combination thereof;
However, WATT teaches: a treatment comprises a front-door way (FW), back-door adjustment ([0056] - - backdoor identification), inverse probability weighting (IPW) ([0061] - - Inverse probability weighting), instrumental variables (IV) ([0054] - - instrumental variables), etc.), a target variable designation, a causal strength target, or any combination thereof;
Martin, MOCHTY, SUN and WATT are analogous art because they are from the same field of endeavor. They all relate to data processing.
Therefore before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify the above medium, as taught by the combination of Martin, MOCHTY and SUN, and incorporating treatments, as taught by WATT.
One of ordinary skill in the art would have been motivated to do this modification in order to improve risk assessments and management, as suggested by WATT ([0004]).
Regarding claim 20, the combination of Martin, MOCHTY, SUN and WATT teaches all the limitations of the base claims as outlined above.
SUN further teaches:
display, via the GUI of the processing system, the one or more causal scores ([0138] - - relevance scores of each path is obtained and displayed in table 1).
WATT further teaches: receiving, via the GUI of the processing system, a refute method ([0048] - - refutation tests) ; and
determine, via the processing system, one or more causal scores associated with the one or more strengths based on the dataset and the refute method ([0048] - - refutation tests are used to estimate the stability of the causal effect), wherein the refute method comprises add random common cause, placebo treatment, dummy outcome, simulated outcome, add unobserved common causes, data subset validation, bootstrap validation, or any combination thereof ([0056] - - common causes; [0046] - - bootstrap);
Martin, MOCHTY, SUN and WATT are combinable for the same rationale as set forth.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to YUHUI R PAN whose telephone number is (571)272-9872. The examiner can normally be reached Monday-Friday 8AM-5PM EST.
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/YUHUI R PAN/Primary Examiner, Art Unit 2116