Patents by Inventor Andrew J Ellis
Andrew J Ellis has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11841699Abstract: An industrial data broker system receives contextualized industrial data from one or more industrial devices that support data modeling at the device level. The received industrial data is augmented with contextualization metadata that defines correlations between the data relevant to an analytical objective, and labels specifying analytic topics to which each data item is relevant. The broker system allows external systems, such as analytic systems, to subscribe to topics of interest, and streams a subset of contextualized device data relevant to the topic of interest to the external system for analysis.Type: GrantFiled: September 30, 2019Date of Patent: December 12, 2023Assignee: Rockwell Automation Technologies, Inc.Inventors: Bijan Sayyarrodsari, Michael Pantaleano, Ka H Lin, Juergen K Weinhofer, Andrew J Ellis, Kyle Crum, Sujeet Chand, David Vasko, Subbian Govindaraj
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Patent number: 11726459Abstract: An industrial control programming development platform simplifies generation of an industrial control program and associated tag definitions by generating at least a portion of the control program and tag definitions based on analysis of digital engineering drawings of an automation system to be monitored and controlled. This drawing-based program generation includes creation and configuration of smart data tags that model and contextualize controller data at the device level for processing by higher level analytic systems. This device-level contextualization can be based in part on inferences drawn from the digital engineering drawings.Type: GrantFiled: June 18, 2020Date of Patent: August 15, 2023Assignee: Rockwell Automation Technologies, Inc.Inventors: Bijan Sayyarrodsari, Subbian Govindaraj, David A. Vasko, Juergen Weinhofer, Andrew J Ellis, Ka-Hing Lin, Michael Pantaleano, Sujeet Chand, Kyle A. Crum
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Patent number: 11709481Abstract: An industrial device supports device-level data modeling that pre-models data stored in the device with known relationships, correlations, key variable identifiers, and other such metadata to assist higher-level analytic systems to more quickly and accurately converge to actionable insights relative to a defined business or analytic objective. Data at the device level can be modeled according to modeling templates stored on the device that define relationships between items of device data for respective analytic goals (e.g., improvement of product quality, maximizing product throughput, optimizing energy consumption, etc.). This device-level modeling data can be provided to higher level systems together with their corresponding data tag values to high level analytic systems, which discovers insights into an industrial process or machine based on analysis of the data and its modeling data.Type: GrantFiled: August 25, 2022Date of Patent: July 25, 2023Assignee: Rockwell Automation Technologies, Inc.Inventors: Bijan Sayyarrodsari, Michael Pantaleano, Ka H Lin, Juergen K Weinhofer, Andrew J Ellis, Kyle Crum, Sujeet Chand, David Vasko, Subbian Govindaraj
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Publication number: 20220404803Abstract: An industrial device supports device-level data modeling that pre-models data stored in the device with known relationships, correlations, key variable identifiers, and other such metadata to assist higher-level analytic systems to more quickly and accurately converge to actionable insights relative to a defined business or analytic objective. Data at the device level can be modeled according to modeling templates stored on the device that define relationships between items of device data for respective analytic goals (e.g., improvement of product quality, maximizing product throughput, optimizing energy consumption, etc.). This device-level modeling data can be provided to higher level systems together with their corresponding data tag values to high level analytic systems, which discovers insights into an industrial process or machine based on analysis of the data and its modeling data.Type: ApplicationFiled: August 25, 2022Publication date: December 22, 2022Inventors: Bijan Sayyarrodsari, Michael Pantaleano, Ka H Lin, Juergen K Weinhofer, Andrew J Ellis, Kyle Crum, Sujeet Chand, David Vasko, Subbian Govindaraj
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Patent number: 11435726Abstract: An industrial device supports device-level data modeling that pre-models data stored in the device with known relationships, correlations, key variable identifiers, and other such metadata to assist higher-level analytic systems to more quickly and accurately converge to actionable insights relative to a defined business or analytic objective. Data at the device level can be modeled according to modeling templates stored on the device that define relationships between items of device data for respective analytic goals (e.g., improvement of product quality, maximizing product throughput, optimizing energy consumption, etc.). This device-level modeling data can be provided to higher level systems together with their corresponding data tag values to high level analytic systems, which discovers insights into an industrial process or machine based on analysis of the data and its modeling data.Type: GrantFiled: September 30, 2019Date of Patent: September 6, 2022Assignee: Rockwell Automation Technologies, Inc.Inventors: Bijan Sayyarrodsari, Michael Pantaleano, Ka H Lin, Juergen K Weinhofer, Andrew J Ellis, Kyle Crum, Sujeet Chand, David Vasko, Subbian Govindaraj
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Publication number: 20210397166Abstract: An industrial control programming development platform simplifies generation of an industrial control program and associated tag definitions by generating at least a portion of the control program and tag definitions based on analysis of digital engineering drawings of an automation system to be monitored and controlled. This drawing-based program generation includes creation and configuration of smart data tags that model and contextualize controller data at the device level for processing by higher level analytic systems. This device-level contextualization can be based in part on inferences drawn from the digital engineering drawings.Type: ApplicationFiled: June 18, 2020Publication date: December 23, 2021Inventors: Bijan Sayyarrodsari, Subbian Govindaraj, David A. Vasko, Juergen Weinhofer, Andrew J Ellis, Ka-Hing Lin, Michael Pantaleano, Sujeet Chand, Kyle A. Crum
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Publication number: 20210097456Abstract: A smart gateway platform leverages pre-defined industrial expertise to identify limited subsets of available industrial data deemed relevant to a desired business objective, and to collect and model this relevant data to apply useful constraints on subsequent artificial intelligence or machine learning analytics applied to the data. This approach can reduce the data space to which AI analytics are applied and assist data analytic systems to more quickly derive valuable insights and business outcomes. In some embodiments, the smart gateway platform can operate within the context of a multi-level industrial analytic system, feeding pre-modeled data to one or more AI or machine learning systems executing on one or more different levels of an industrial enterprise. The multi-level industrial analytic system can also further refine modeled industrial data as the data moves upward through the system (e.g., from the device level to higher levels).Type: ApplicationFiled: September 30, 2019Publication date: April 1, 2021Inventors: Bijan Sayyarrodsari, Michael Pantaleano, Ka H Lin, Juergen K Weinhofer, Andrew J Ellis, Kyle Crum, Sujeet Chand, David Vasko, Subbian Govindaraj
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Publication number: 20210096551Abstract: An industrial data broker system receives contextualized industrial data from one or more industrial devices that support data modeling at the device level. The received industrial data is augmented with contextualization metadata that defines correlations between the data relevant to an analytical objective, and labels specifying analytic topics to which each data item is relevant. The broker system allows external systems, such as analytic systems, to subscribe to topics of interest, and streams a subset of contextualized device data relevant to the topic of interest to the external system for analysis.Type: ApplicationFiled: September 30, 2019Publication date: April 1, 2021Inventors: Bijan Sayyarrodsari, Michael Pantaleano, Ka H. Lin, Juergen K. Weinhofer, Andrew J. Ellis, Kyle Crum, Sujeet Chand, David Vasko, Subbian Govindaraj
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Publication number: 20210096541Abstract: An industrial device supports device-level data modeling that pre-models data stored in the device with known relationships, correlations, key variable identifiers, and other such metadata to assist higher-level analytic systems to more quickly and accurately converge to actionable insights relative to a defined business or analytic objective. Data at the device level can be modeled according to modeling templates stored on the device that define relationships between items of device data for respective analytic goals (e.g., improvement of product quality, maximizing product throughput, optimizing energy consumption, etc.). This device-level modeling data can be provided to higher level systems together with their corresponding data tag values to high level analytic systems, which discovers insights into an industrial process or machine based on analysis of the data and its modeling data.Type: ApplicationFiled: September 30, 2019Publication date: April 1, 2021Inventors: Bijan Sayyarrodsari, Michael Pantaleano, Ka H Lin, Juergen K Weinhofer, Andrew J Ellis, Kyle Crum, Sujeet Chand, David Vasko, Subbian Govindaraj