Abstract: Methods generally including interpreting at least a subset of the plurality of detection values to determine a state value comprising at least one of a process state or a component state; analyzing a subset of the plurality of detection values and the state value, using at least one of a neural net or an expert system, and providing an adjustment recommendation for the industrial production process, the adjustment recommendation, at least in part, in response to a sensitivity of at least one of the plurality of input channels relative to the state value; adjusting the industrial production process in response to the adjustment recommendation; determining a relevance of the adjustment recommendation to at least one role type stored within a role taxonomy; and reporting the adjustment to the industrial production process to at least one entity associated with the role type stored within the role taxonomy.

Abstract: Systems for data collection in an industrial environment having a self-sufficient data acquisition box for capturing and analyzing data in an industrial process generally including a data circuit for analyzing a plurality of sensor inputs; and a network control circuit for sending and receiving information related to the plurality of sensor inputs to an external system. The information sent and received by the network control system is based at least in part on a role-based reporting rule and encoded with role-based information that is used by the external system to report the information sent and received to a specified role taxonomy, the system provides sensor data to one or more other systems for data collection, and the data circuit dynamically reconfigures a route by which the system sends the sensor data based on how many devices are requesting the information.

Abstract: Methods generally including determining a structure in the data; by the controller, determining a relevance of the determined structure in the data to at least one role type stored within a role taxonomy; by the controller, determining a reduced dimensionality view of the data in response to the determined structure in the data. The reduced dimensionality view comprises fewer dimensions than the data from the plurality of input sensors. The reduced dimensionality view further comprises a graphical element representing at least one of: mechanical portions of a machine of the industrial environment, or a sensor from the plurality of input sensors that provided data; and providing the reduced dimensionality view to a user interface that is associated with at least one entity associated with the at least one role type stored within the role taxonomy.

Abstract: Computer-implemented methods for fault diagnosis in an industrial environment generally includes processing the plurality of sensor data values to determine a recognized pattern therefrom; retrieving at least one industrial-environment digital twin corresponding to the industrial environment, the at least one industrial-environment digital twin comprising a plurality of component digital twins, with each of the plurality of component digital twins corresponding to one of the plurality of components in the industrial environment, and wherein the at least one industrial-environment digital twin and the plurality of component digital twins are visual digital twins that are configured to be rendered in a visual manner; and rendering the at least one industrial-environment digital twin and the at least one respective component digital twin corresponding to the particular component in the client application in response to the received request and based on the operational condition of the particular component.

Abstract: Data storage structured to store a plurality of detection values relating to aspects of an industrial production process and data relating to at least one role type stored within a role taxonomy; a data analysis circuit structured to interpret at least a subset of the plurality of detection values to determine a state value comprising at least one of a process state or a component state; an optimization circuit structured to analyze a subset of the plurality of detection values and the state value using at least one of a neural net or an expert system to determine a signal effectiveness of at least one of the plurality of input channels relative to the state value, and to provide an adjustment recommendation based, at least in part, on the signal effectiveness; and an analysis response circuit structured to adjust the industrial production process in response to the adjustment recommendation.

Abstract: Method for data collection in an industrial environment generally including receiving, at a switch, data from one or more variable groups of sensor inputs; monitoring the data from the one or more variable groups of sensor inputs; adaptively scheduling data collection at the switch; determining one or more noise values including one of an ambient noise, a local noise, or a vibration noise; using machine learning to forecast a future state of the industrial environment based at least in part on the determined one or more noise values; and reporting the forecasted future state of the industrial environment to an entity associated with a role type stored within a role taxonomy.

Abstract: Computer-implemented methods for fault diagnosis in an industrial environment generally includes processing the plurality of sensor data values to determine a recognized pattern therefrom; retrieving at least one industrial-environment digital twin corresponding to the industrial environment, the at least one industrial-environment digital twin comprising a plurality of component digital twins, with each of the plurality of component digital twins corresponding to one of the plurality of components in the industrial environment, and wherein the at least one industrial-environment digital twin and the plurality of component digital twins are visual digital twins that are configured to be rendered in a visual manner; and rendering the at least one industrial-environment digital twin and the at least one respective component digital twin corresponding to the particular component in the client application in response to the received request and based on the operational condition of the particular component.

Abstract: Computer-implemented methods for fault diagnosis in an industrial environment generally includes processing the plurality of sensor data values to determine a recognized pattern therefrom; retrieving at least one industrial-environment digital twin corresponding to the industrial environment, the at least one industrial-environment digital twin comprising a plurality of component digital twins, with each of the plurality of component digital twins corresponding to one of the plurality of components in the industrial environment, and wherein the at least one industrial-environment digital twin and the plurality of component digital twins are visual digital twins that are configured to be rendered in a visual manner; and rendering the at least one industrial-environment digital twin and the at least one respective component digital twin corresponding to the particular component in the client application in response to the received request and based on the operational condition of the particular component.

Abstract: An apparatus, methods and systems for data collection in an industrial environment are disclosed. A monitoring system can include a data collector coupled to a plurality of sensors to collect data, a data storage structured to store a plurality of data collection management plans, a data acquisition circuit structured to interpret a plurality of detection values from the collected data, and a data analysis circuit structured to analyze the collected data and select one of the plurality of data collection management plans, wherein the selected one of the plurality of data collection management plans is selected is at least in part based on a data analysis of received data from the plurality of sensors.

Abstract: An apparatus, methods and systems for data collection related to an oil and gas process and disclosed. A system may include a multi-sensor acquisition component including a plurality of inputs and a plurality of outputs, a sensor data storage profile circuit structured to determine a data storage profile including a data storage plan for the plurality of inputs, a sensor communication circuit structured to interpret a plurality of inputs, a sensor data storage implementation circuit structured to store at least a portion of the inputs in response to the data storage profile, a data analysis circuit structured to analyze the plurality of inputs and determine a data quality parameter, and a data response circuit structured to adjust at least one of the data storage profile and the data collection routine in response to the data quality parameter.

Abstract: Systems and methods for data collection in an industrial production system including a plurality of components are disclosed. An example system may include a sensor communication circuit structured to interpret a plurality of data values from a sensed parameter group, the sensed parameter group including a plurality of sensors including a vibration sensor and a temperature sensor, and the plurality of sensors operatively coupled to at least one of the plurality of components; a data analysis circuit structured to detect an operating condition of the industrial production system based on detecting that the data values from the vibration sensor indicate a vibration pattern that matches a stored vibration fingerprint together with detecting that the data values from the temperature sensor indicate a change in a temperature; and a response circuit structured to modify a production-related operating parameter of the industrial production system in response to the detected operating condition.

Abstract: Systems for self-organizing collection and storage in a distribution environment are disclosed. A system may include a data collector for handling a plurality of sensor inputs from sensors in the distribution environment, wherein the sensor inputs sense at least one of an operational mode, a fault mode, a maintenance mode, or a health status of at least one target system selected from a group consisting of a power system, a conveyor system, a robotic transport system, a robotic handling system, a packing system, a cold storage system, a hot storage system, a refrigeration system, a vacuum system, a hauling system, a lifting system, an inspection system, and a suspension system. A system may further include a self-organizing system for: a storage operation of the data, a data collection operation, or a selection operation.

Abstract: Systems for self-organizing data collection and storage in a manufacturing environment are disclosed. A system may include a data collector for handling a plurality of sensor inputs from sensors in the manufacturing system, wherein the plurality of sensor inputs is configured to sense at least one of: an operational mode, a fault mode, a maintenance mode, or a health status of at least one target system. The system may also include a self-organizing system for self-organizing a storage operation of the data, a data collection operation of the sensors, or a selection operation of the plurality of sensor inputs. The self-organizing system may organize a swarm of mobile data collectors to collect data from a plurality of target systems.

Abstract: Systems for self-organizing data collection and storage in a power generation environment are disclosed. A system may include a data collector for handling a plurality of sensor inputs from sensors in the power generation system, wherein the plurality of sensor inputs is configured to sense at least one of: an operational mode, a fault mode, a maintenance mode, or a health status of at least one target system. The system may also include a self-organizing system for self-organizing a storage operation of the data, a data collection operation of the sensors, or a selection operation of the plurality of sensor inputs. The self-organizing system may organize a swarm of mobile data collectors to collect data from a plurality of target systems.

Abstract: Systems for self-organizing data collection in an industrial environment are disclosed. An example system may include a self-propelled mobile data collector for handling a plurality of sensor inputs from sensors in the industrial environment, wherein the plurality of sensor inputs is configured to sense at least one of: an operational mode, a fault mode, a maintenance mode, or a health status of at least one target system. The system may include a self-organizing system for self-organizing at least one of a storage operation of the data, a data collection operation of the sensors, or a selection operation of the plurality of sensor inputs. The self-organizing system organizes a swarm of self-propelled mobile data collectors to collect data from a plurality of target systems in the industrial environment.

Abstract: System and methods for learning data patterns predictive of an outcome are described. An example system may include a plurality of input sensors communicatively coupled to a controller; a data collection circuit structured to collect output data from the plurality of input sensors; and a machine learning data analysis circuit structured to receive the output data, learn received output data patterns indicative of an outcome, and learn a preferred input data collection band among a plurality of available input data collection bands. The machine learning data analysis circuit may be structured to learn received output data patterns by being seeded with a model based on industry-specific feedback. The outcome may be at least one of: a reaction rate, a production volume, or a required maintenance.

Abstract: Systems for self-organizing data collection and storage in a refining environment are disclosed. An example system may include a swarm of mobile data collectors structured to interpret a plurality of sensor inputs from sensors in the refining environment, wherein the plurality of sensor inputs is configured to sense at least one of: an operational mode, a fault mode, a maintenance mode, or a health status of a plurality of refining system components disposed in the refining environment, and wherein the plurality of refining system components is structured to contribute, in part, to refining of a product. The self-organizing system organizes a swarm of mobile data collectors to collect data from the system components, and at least one of a storage operation of the data, a data collection operation of the sensors, or a selection operation of the plurality of sensor inputs.

Abstract: A platform for updating one or more properties of one or more digital twins including receiving a request for one or more digital twins; retrieving the one or more digital twins required to fulfill the request from a digital twin datastore; retrieving one or more dynamic models corresponding to one or more properties that are depicted in the one or more digital twins indicated by the request; selecting data sources from a set of available data sources based on the one or more inputs of the one or more dynamic models; obtaining data from selected data sources; determining one or more outputs using the retrieved data as one or more inputs to the one or more dynamic models; and updating the one or more properties of the one or more digital twins based on the one or more outputs of the one or more dynamic models.

Abstract: A lifting sling apparatus for lifting, holding, and transporting materials. More particularly, the invention relates to a lifting sling comprising a reinforced heavy-duty fabric body, such as, for example, a geotextile fabric, i.e., a synthetic fabric made from polypropylene, polyester, or other like synthetic materials, having heavy-duty sling webbing loops and reinforcement webbing on the body.

Abstract: A platform for updating one or more properties of one or more digital twins including receiving a request for one or more digital twins; retrieving the one or more digital twins required to fulfill the request from a digital twin datastore; retrieving one or more dynamic models corresponding to one or more properties that are depicted in the one or more digital twins indicated by the request; selecting data sources from a set of available data sources based on the one or more inputs of the one or more dynamic models; obtaining data from selected data sources; determining one or more outputs using the retrieved data as one or more inputs to the one or more dynamic models; and updating the one or more properties of the one or more digital twins based on the one or more outputs of the one or more dynamic models.