SYSTEMS AND METHODS FOR BATCH SYNCHRONIZATION IN INDUSTRIAL BATCH ANALYTICS

    公开(公告)号:US20240370001A1

    公开(公告)日:2024-11-07

    申请号:US18457466

    申请日:2023-08-29

    Abstract: An illustrative method includes a batch analytic system receiving 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, determining 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, generating 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 performing an operation using the batch representation of the batch.

    ROOT CAUSE ANALYSIS FRAMEWORK IN INDUSTRIAL PROCESS ANALYTICS

    公开(公告)号:US20250147488A1

    公开(公告)日:2025-05-08

    申请号:US18503898

    申请日:2023-11-07

    Abstract: A method may include 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. The method may also include receiving, via the GUI of the processing system, a set of input variables associated with the dataset, receiving a target variable associated with the dataset, and receiving a model type for analyzing the dataset. The method may also involve determining, via the processing system, a contribution of each of the set of input variables to the target variable based on the model type; and 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.

    BATCH PERFORMANCE MONITORING AND CONTROL PLATFORM WITH EXTENSIBLE DATA MODEL

    公开(公告)号:US20250103043A1

    公开(公告)日:2025-03-27

    申请号:US18373714

    申请日:2023-09-27

    Abstract: A system and method for monitoring and controlling production of batches of products in an industrial process, the method comprising: receiving, by a processing circuit, data describing a batch of products generated in an industrial process from one or more data sources; contextualizing, by the processing circuit, the data describing the batch of products generated in the industrial process; generating, by the processing circuit, a batch data model based on the contextualized data; executing, by the processing circuit, the batch data model to determine key performance indicators for the batch of products; comparing, by the processing circuit, the key performance indicators to pre-determined key performance indicators; and performing an automated action based on a result of the comparison.

    SYSTEMS AND METHODS FOR OPTIMIZING AN INDUSTRIAL PROCESS

    公开(公告)号:US20240385611A1

    公开(公告)日:2024-11-21

    申请号:US18596193

    申请日:2024-03-05

    Abstract: A method comprises determining that a batch generated in an industrial process (IP) is anomalous at a sample point k during the batch, the batch is ongoing; determining a process variable (PV) of the IP based on a variable contribution of the PV towards the batch being anomalous at the sample point k; determining a recommended value of the PV based on an anomaly metric corresponding to the sample point k of an assessment batch, the assessment batch is created based on sample(s) of the batch at the sample point k and the recommended value of the PV, the anomaly metric corresponding to the sample point k of the assessment batch is determined based on a T2-statistic metric corresponding to the sample point k and a Q-statistic metric corresponding to the sample point k of the assessment batch; and adjusting the IP based on the recommended value of the PV.

    EMPLOYING A BATCH MODEL IN ROOT CAUSE ANALYSIS OF INDUSTRIAL BATCH PERFORMANCE ANALYTICS

    公开(公告)号:US20250147501A1

    公开(公告)日:2025-05-08

    申请号:US18503866

    申请日:2023-11-07

    Abstract: A method may include receiving, via a processing system, a selection of a first dataset associated with one or more operations of one or more industrial automation components of an industrial system that may perform a batch operation. The method may involve generating an optimized dataset based on the dataset, receiving a second dataset associated with one or more additional operations of one or more additional industrial automation components of an additional industrial system that may perform an additional batch operation, and determining one or more deviations between the optimized dataset and the second dataset. The method may also involve determining a contribution of each of a set of parameters to the one or more deviations and generating a visualization representative of the contribution of each of a set of parameters to the deviation.

    Industrial Batch Dataset Generation for Operations Modeling

    公开(公告)号:US20240402697A1

    公开(公告)日:2024-12-05

    申请号:US18679061

    申请日:2024-05-30

    Abstract: A non-transitory tangible, computer-readable medium storing instructions that, when executed by processing circuitry, cause the processing circuitry to perform operations including receiving data associated with industrial equipment, pre-processing the data using pre-processing files associated with a modeling technique to generate pre-processed data, generating training dataset files based on the pre-processed data, and generating a model representative of expected operations of the industrial equipment based on the training dataset files. The instructions cause the processing circuitry to perform operations including storing an association between the training dataset files with the modeling technique, the industrial equipment, or both in a database, receiving a request to generate an additional model representative of additional expected operations of additional industrial equipment, receiving additional data associated with the additional industrial equipment, retrieving the training dataset files based on the additional data, and generating the additional model based on the training dataset files and the additional data.

    Industrial Batch Processing Operation Control for Use with Artificial Intelligence (AI) Models

    公开(公告)号:US20240402691A1

    公开(公告)日:2024-12-05

    申请号:US18679130

    申请日:2024-05-30

    Abstract: A non-transitory tangible, computer-readable medium storing instructions that, when executed by processing circuitry, cause the processing circuitry to perform operations including receiving a set of data associated with industrial devices of an industrial system, and retrieving pre-processing files and training datasets files associated with the industrial devices from a database, wherein the pre-processing files are configured to transform the data for generating a model representative of the industrial devices, and wherein the training dataset files are representative of operational characteristics of the industrial devices over time. The instructions cause the processing circuitry to perform operations including generating a set of prediction data representative of expected operations of the industrial devices based on the set of data and the model, determining commands for adjusting operational settings of the industrial devices based on the set of prediction data, and sending the commands to the industrial devices.

    Industrial Batch Processing Dynamic User Interface

    公开(公告)号:US20240402690A1

    公开(公告)日:2024-12-05

    申请号:US18679113

    申请日:2024-05-30

    Abstract: A non-transitory tangible, computer-readable medium storing instructions that, when executed by processing circuitry, cause the processing circuitry to perform operations including receiving data associated with one or more industrial devices of an industrial system, and retrieving one or more pre-processing files and one or more training datasets files associated with a model from a database, wherein the one or more pre-processing files are configured to transform the data, and wherein the one or more training dataset files are representative of one or more operational characteristics of the one or more industrial devices over time. The instructions cause the processing circuitry to perform operations including receiving one or more inputs to modify one or more parameters of the model via a user interface presented via an electronic display, and generating the model based on the training dataset files and the one or more inputs.

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