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.

Systems and methods for process monitoring through data collection in a production environment can include a data collector communicatively coupled to a plurality of input channels, each input channel connected to a monitoring point from which data is collected, the collected data providing a plurality of process parameter values for the production environment; a data storage structured to store collected data from the plurality of input channels; a data acquisition circuit structured to interpret the plurality of process parameter values from the collected data; a data analysis circuit structured to analyze the plurality of process parameter values to detect a process condition associated with the production environment; and a response circuit structured to adjust an operational process for the production environment in response to the detected process condition.

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.

A system including biogas purification and provides biogas as feedstock to a solid oxide fuel cell. The biogas purification treatment process provides a polished biogas that is substantially free of carbonyl sulfides and hydrogen sulfide. The system uses a biogas treatment apparatus, that includes apparatus such as a packed columns, comprising copper oxide or potassium permanganate packing material, and an activated carbon component configured to treat the biogas by polishing it to remove carbonyl sulfides and deleterious trace residues, such as hydrogen sulfide, that were not removed by any prior bulk H2S removal steps. In addition, an oil removal device is used to remove any entrained fine oil droplets in the biogas. A polished biogas having in the range of 60% methane is charged to the fuel cell. Electricity generated may be fed into a grid or used directly as energy to charge electrical-powered vehicles, for example. Energy credits are tracked in real time and are appropriately assigned.

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.

Systems and methods for interactions with power station noise patterns are disclosed. A system can include a data collector communicatively coupled to a plurality of input channels, wherein at least one of the plurality of input channels is operatively coupled to a vibration detection facility structured to detect a noise pattern of a power station, a library structured to store the detected noise pattern, an interface circuit structured to make the noise pattern available to a noise pattern marketplace, the noise pattern marketplace including a plurality of noise patterns from a plurality of power stations; and a user interface for accessing at least one of the plurality noise patterns of the noise pattern marketplace.

The present application generally pertains to scaling of a production process to produce a chemical, pharmaceutical and/or biotechnological product and/or of a production state of a respective production equipment. Particularly, there is provided a computer-implemented method of scaling a production process to produce a chemical, pharmaceutical and/or biotechnological product, the scaling being from a source scale to a target scale, wherein the production process is defined by a plurality of steps specified by one or more process parameters controlling an execution of the production process, the method comprising: (a) retrieving: parameter evolution information that describes the time evolution of the process parameter(s); a plurality of recipe templates, wherein a recipe comprises the plurality of steps defining the production process, and wherein a recipe template is a recipe in which at least one of the process parameters specifying the plurality of steps is a parameter being variable and having no predetermined value at the outset; (b) receiving: a source setup specification of a source setup to be used for executing the production process at the source scale, the source setup specification comprising the source scale value; a target setup specification of a target setup to be used for executing the production process at the target scale, the target setup specification comprising the target scale value; a source recipe defining the production process at the source scale; at least one acceptability function defining conditions for the values of the process parameter(s) at the source scale and/or at the target scale; (c) simulating the execution of the production process at the source scale using the source setup specification, the source recipe and the parameter evolution information; (d) determining, from the simulation, one or more source trajectories for the process parameter(s), wherein a trajectory corresponds to a time-based profile of values recordable during the simulated execution of the production process; (e) performing a target determination step comprising: selecting a recipe template pertinent to the production process out of the plurality of recipe templates; providing an input value for the at least one variable parameter in the selected recipe template; simulating the execution of the production process at the target scale using the target setup specification, the selected recipe template, the input value for the at least one variable parameter and the parameter evolution information; determining, from the simulation, one or more target trajectories for the process parameters; comparing the source trajectory(ies) and the target trajecto

A system for monitoring an oil and gas process includes a data acquisition circuit structured to interpret a plurality of detection values corresponding to input received from a detection package which includes at least one of a plurality of input sensors each operatively coupled to at least one of a plurality of components of an industrial production process; a data analysis circuit structured to analyze a subset of the plurality of detection values to determine a status parameter; and an analysis response circuit structured to adjust the detection package in response to the status parameter, wherein the plurality of available sensors have at least one distinct sensing parameter selected from the sensing parameters consisting of: input ranges, sensitivity values, locations, reliability values, duty cycle values, sensor types, and maintenance requirements.

The present disclosure describes monitoring systems and methods for data collection in an industrial environment. A system can include a data collector and a data acquisition circuit to interpret a plurality of detection values corresponding to input channels, wherein the data acquisition circuit acquires sensor data from a first route of input channels. A data storage stores sensor specifications for sensors and a data analysis circuit evaluates the sensor data with respect to the stored anticipated state information including an alarm threshold level. The data analysis circuit sets an alarm state when the alarm threshold level is exceeded for a first input channel and transmits the alarm state to a routing control facility. A response circuit changes the routing of the input channels to an alternate routing upon reception of a routing change indication from the routing control facility.

Systems, methods and apparatus for modifying a data collection trajectory for conveyors are described. An example system may include a data acquisition circuit to interpret a plurality of detection values, each corresponding to at least one of a plurality of input sensors communicatively coupled to the data acquisition circuit. The system may further include a data storage circuit to store specifications and anticipated state information for a plurality of conveyor types and an analysis circuit to analyze the plurality of detection values relative to specifications and anticipated state information to determine a conveyor performance parameter. A response circuit may initiate an action in response to the conveyor performance parameter.