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公开(公告)号：US20210003996A1
公开(公告)日：2021-01-07
申请号：US16503166
申请日：2019-07-03
发明人： Mithun Mohan Nagabhairava , Andrew J. Schaeffler , David C. Mazur , Rob Alan Entzminger , Peter A. Morell
IPC分类号： G05B19/418 , H04L29/08 , G06F16/903
摘要： Techniques to facilitate automatic discovery of industrial assets and associated data in an industrial automation environment are disclosed herein. In at least one implementation, a computing system iteratively scans a communication network to automatically detect at least one industrial device on the communication network. The computing system determines a unique identifier of a device type associated with the at least one industrial device detected on the communication network. The computing system determines an identity object for the industrial device and maps the identity object to the unique identifier of the device type associated with the industrial device. Based on the identity object for the industrial device, the computing system establishes communication with the industrial device on the communication network and receives operational data from the industrial device. The computing system processes the operational data received from the industrial device to generate a device profile for the industrial device.
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公开(公告)号：US11126168B2
公开(公告)日：2021-09-21
申请号：US16503166
申请日：2019-07-03
发明人： Mithun Mohan Nagabhairava , Andrew J. Schaeffler , David C. Mazur , Rob Alan Entzminger , Peter A. Morell
IPC分类号： G05B19/418 , G06F16/903 , H04L29/08
摘要： Techniques to facilitate automatic discovery of industrial assets and associated data in an industrial automation environment are disclosed herein. In at least one implementation, a computing system iteratively scans a communication network to automatically detect at least one industrial device on the communication network. The computing system determines a unique identifier of a device type associated with the at least one industrial device detected on the communication network. The computing system determines an identity object for the industrial device and maps the identity object to the unique identifier of the device type associated with the industrial device. Based on the identity object for the industrial device, the computing system establishes communication with the industrial device on the communication network and receives operational data from the industrial device. The computing system processes the operational data received from the industrial device to generate a device profile for the industrial device.
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公开(公告)号：US20210080941A1
公开(公告)日：2021-03-18
申请号：US16573609
申请日：2019-09-17
IPC分类号： G05B23/02 , G05B19/418 , G05B13/02 , G06N20/00
摘要： Techniques to facilitate predictive maintenance for industrial assets in an industrial automation environment are disclosed herein. In at least one implementation, a computing system receives a plurality of industrial automation process variables associated with at least one industrial asset employed in an industrial automation process. The industrial automation process variables are fed into a machine learning model associated with the at least one industrial asset to generate a future maintenance event prediction for the at least one industrial asset. The future maintenance event prediction for the at least one industrial asset is provided to an industrial controller that controls the at least one industrial asset.
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公开(公告)号：US20220244711A1
公开(公告)日：2022-08-04
申请号：US17659742
申请日：2022-04-19
发明人： Nicole R. Bulanda , Fabio M. Mielli , Andrew J. Schaeffler , Peter A. Morell , David C. Mazur , Barry N. Elliott , Scotty Bromfield
IPC分类号： G05B19/418 , H04J3/06 , G06N20/00
摘要： Techniques to facilitate synchronization of industrial assets in an industrial automation environment are disclosed herein. In at least one implementation, a computing system receives time-series industrial process data associated with a plurality of process subsystems of an industrial automation process. The time-series industrial process data is fed into a machine learning model associated with the industrial automation process to dynamically generate a process duration prediction for a first one of the process subsystems and responsively determine an updated set point for a second one of the process subsystems based on the process duration prediction for the first one of the process subsystems. The updated set point for the second one of the process subsystems is provided to an industrial controller associated with the second one of the process subsystems.
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公开(公告)号：US11340594B2
公开(公告)日：2022-05-24
申请号：US16543112
申请日：2019-08-16
发明人： Nicole R. Bulanda , Fabio M. Mielli , Andrew J. Schaeffler , Peter A. Morell , David C. Mazur , Barry N. Elliott , Scotty Bromfield
IPC分类号： G05B19/418 , H04J3/06 , G06N20/00
摘要： Techniques to facilitate synchronization of industrial assets in an industrial automation environment are disclosed herein. In at least one implementation, a computing system receives time-series industrial process data associated with a plurality of process subsystems of an industrial automation process. The time-series industrial process data is fed into a machine learning model associated with the industrial automation process to dynamically generate a process duration prediction for a first one of the process subsystems and responsively determine an updated set point for a second one of the process subsystems based on the process duration prediction for the first one of the process subsystems. The updated set point for the second one of the process subsystems is provided to an industrial controller associated with the second one of the process subsystems.
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公开(公告)号：US11906947B2
公开(公告)日：2024-02-20
申请号：US17659742
申请日：2022-04-19
发明人： Nicole R. Bulanda , Fabio M. Mielli , Andrew J. Schaeffler , Peter A. Morell , David C. Mazur , Barry N. Elliott , Scotty Bromfield
IPC分类号： G05B19/418 , H04J3/06 , G06N20/00
CPC分类号： G05B19/41865 , G05B19/4183 , G05B19/4185 , G06N20/00 , H04J3/0661
摘要： Techniques to facilitate synchronization of industrial assets in an industrial automation environment are disclosed herein. In at least one implementation, a computing system receives time-series industrial process data associated with a plurality of process subsystems of an industrial automation process. The time-series industrial process data is fed into a machine learning model associated with the industrial automation process to dynamically generate a process duration prediction for a first one of the process subsystems and responsively determine an updated set point for a second one of the process subsystems based on the process duration prediction for the first one of the process subsystems. The updated set point for the second one of the process subsystems is provided to an industrial controller associated with the second one of the process subsystems.
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公开(公告)号：US20210048798A1
公开(公告)日：2021-02-18
申请号：US16543112
申请日：2019-08-16
发明人： Nicole R. Bulanda , Fabio M. Mielli , Andrew J. Schaeffler , Peter A. Morell , David C. Mazur , Barry N. Elliott , Scotty Bromfield
IPC分类号： G05B19/418 , H04J3/06 , G06N20/00
摘要： Techniques to facilitate synchronization of industrial assets in an industrial automation environment are disclosed herein. In at least one implementation, a computing system receives time-series industrial process data associated with a plurality of process subsystems of an industrial automation process. The time-series industrial process data is fed into a machine learning model associated with the industrial automation process to dynamically generate a process duration prediction for a first one of the process subsystems and responsively determine an updated set point for a second one of the process subsystems based on the process duration prediction for the first one of the process subsystems. The updated set point for the second one of the process subsystems is provided to an industrial controller associated with the second one of the process subsystems.
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