A blast furnace fault determination apparatus includes a processor configured to: calculate a fault index indicative of a degree of fault in a blast furnace; calculate a ventilation index of the blast furnace; and determine a fault condition in the blast furnace using the fault index and the ventilation index.

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.

According to an embodiment, a monitoring apparatus configured to generate time-series predicted data based on time-series measured data and a prediction model that generates predicted data including one or more predicted values predicted to be output from one or more sensors; and generate, for a first sensor among the one or more sensors, a displayed image including a measured value graph representing a temporal change in a measured value included in the time-series measured data in a second period after a first period, a predicted value graph representing a temporal change in a predicted value included in time-series predicted data in the second period, past distribution information representing a distribution of a measured value in the first period, and measurement distribution information representing a distribution of the measured value included in the time-series measured data in the second period.

A system, apparatus, computer program product, and a method for manufacturing an unconsolidated composite material. Sensor data is received from a sensor system for a composite material manufacturing system. The sensor data is received during manufacturing an unconsolidated composite material by the composite material manufacturing system. A set of predicted properties is determined for a number of portions of the unconsolidated composite material using the sensor data. The set of predicted properties is for the number of portions of the unconsolidated composite material as a completed product. A corrective action is performed based on a quality level for the number of portions of the unconsolidated composite material.

An information translation device, information translation method, and an information translation system based on Modbus are provided. The client module of the information translation device receives an information model file including identity information, receives a sensor signal corresponding to first identity information and Modbus data including memory addresses of Modbus protocol, determines a first memory address corresponding to the sensor signal according to sensed values of the sensor signal and values corresponding to each of the memory addresses and builds a memory address mapping table including the first memory address and the first identity information, and receives a first value of the first memory address and searches the first identity information corresponding to the first memory address according to the memory address mapping table. The server module of the information translation device receives the first value and the first identity information and transmits to an OPC UA device.

A system and method include receiving time series values of one or more sensed parameters of a product manufacturing processes. The received time series values are compared to desired time series values to detect one or more anomalies in the received time series values. An action to apply to the product manufacturing process product is determined based on the one or more detected anomalies is orchestrated by an intelligent workflow engine, that derives inferences from analytics, heuristics rules, skills, and a knowledge library.

Methods and systems for a monitoring system for data collection in an industrial environment including a data collector communicatively coupled to a plurality of input channels connected to data collection points related to machine components, wherein at least one of the plurality of input channels is connected to a data collection point on a rotating machine component; a data acquisition circuit structured to interpret a plurality of detection values from the collected data, each of the plurality of detection values corresponding to at least one of the plurality of input channels; and an expert system analysis circuit structured to analyze the collected data, wherein the expert system analysis circuit determines a failure state for the rotating machine component based on analysis of the plurality of detection values, wherein upon determining the failure state the expert system analysis circuit provides the failure state to a data storage.

The present invention relates to a method and a system for detecting anomalies in a robotic system in an industrial plant. The robotic system is associated with a computing system configured to detect an anomaly in the robotic system. The computer system monitors configuration parameters of the robotic system and process parameters associated with the robotic system. Further, the computing system detects an association between at least one configuration parameter and at least one process parameter for obtaining optimal configuration parameters and optimal process parameters. The optimal configuration parameters and optimal process parameters are analyzed for detecting an anomaly. At least one parameter among the configuration parameters and the process parameters is identified causing the anomaly. Thereafter, the detected anomaly is validated, valid setpoint is estimated and the estimated valid setpoint is updated in the analytics model. The updated analytics model is subsequently used to detect anomaly accurately.

Methods and systems for monitoring a plurality of components of a pump in an industrial environment include a data acquisition circuit structured to interpret a plurality of detection values, each of the plurality of detection values corresponding to at least one of a plurality of input sensors operationally coupled to the pump and communicatively coupled to the data acquisition circuit; a data processing circuit structured to utilize at least one of the plurality of detection values to perform at least one noise processing operation on at least a portion of the plurality of detection values; a signal evaluation circuit structured to determine a pump performance parameter in response to the noise processed plurality portion of the plurality of detection values; and a response circuit structured to perform at least one operation in response to the pump performance parameter.

A method and system for eliminating a fault condition in a technical installation is provided. In one aspect, the method includes predicting an occurrence of the fault condition in at least a portion of the technical installation. The method also includes determining a root cause of the predicted fault condition. Additionally, the method includes identifying one or more mitigation actions to resolve the fault condition. Furthermore, the method includes determining an outcome associated with at least one of the one or more mitigation actions on the technical installation. The method also includes outputting on a device associated with a user at least one mitigation action to be implemented in the technical installation based on the determined impact.