A method, an apparatus, and a system for managing alarms is provided. In one aspect, the method includes detecting a fault in one of a plurality of alarm systems, wherein each of the alarm systems is configured to generate at least one alarm associated with an event in the technical installation. The method further includes invoking a proxy of the faulty alarm system upon detecting the fault condition, wherein the proxy, when invoked, is configured to perform the functions of the faulty alarm system. Additionally, the method includes processing, by the proxy, event data associated with the event in the technical installation. Furthermore, the method includes generating at least one alarm by the proxy based on the processing of the event in the technical installation and outputting an alarm condition on a device associated with a user of the technical installation.

Systems and methods for data collection and processing are described, including a plurality of variable groups of industrial sensor inputs operationally coupled to an industrial environment and a multiplexer communicatively coupled to the industrial sensor inputs; and a controller configured to receive and monitor the data and adaptively schedule the data collector.

A control circuit system for influencing at least one process variable includes a plurality of sensors which each detect at least one measurement variable, a plurality of actuators which each manipulate at least one control variable, wherein the sensors and actuators are each assigned electronic circuits for control, and at least one control mechanism which controls and/or coordinates each of the plurality of sensors and actuators by means of at least one control unit. The control circuit system is sub-divided into a plurality of sub-units which are each provided with at least one sensor, at least one actuator and at least one control unit, and for a plurality of the sub-units, in particular all of the sub-units, each to be set up to operate a control circuit system.

A system comprising a processor is programmed to receive, from a plurality of vehicles, sets of diagnostic test data relating to a performed diagnostic test. Each set of diagnostic test data includes a test output value and one or more corresponding test condition values. The processor is further programmed to select some of the test output values based on selecting a function to relate the test output value to test output values from different sets of diagnostic data. The processor is further programmed to provide the test output value and the corresponding test conditions values as input to the selected function to obtain a plurality of scaled test output values; and generate an adjustment to the diagnostic test based at least in part on the scaled test output values.

An abnormality degree calculation system includes a concept classification assignment unit that assigns a predetermined concept classification based on an identification number of a target device, a feature value vector extraction unit that extracts a feature value vector based on sensor data of a sensor corresponding to the target device, a likelihood calculation unit that calculates a likelihood of the feature value vector by using a machine learning model obtained from a learning database, a loss calculation unit that calculates a loss using a loss function as a function of the likelihood, a model update unit that updates the model by using the loss and a model, a re-learning necessity determination unit that determines whether re-learning is necessary from the calculated likelihood when an abnormality of the target device is detected, and an abnormality degree calculation unit that calculates an abnormality degree when the re-learning is unnecessary.

An operation management method for machine tools is provided for collectively managing a plurality of events generated by a series of events. The operation management method for the machine tools includes a collecting step of monitoring an operation state of the machine tools, and collecting events that are generated by operations thereof, and a grouping step of dividing into a plurality of groups a collected plurality of the events and storing the same in a storage medium. In the grouping step, at each time that a mode which is set in the machine tools is switched, one event or two or more events that are generated during the set mode are grouped together and stored.

Pulverizers are very critical equipment in overall functioning of a plant. They need to be controlled and monitored properly for the optimized operation of the pulverizers. A system and method for performance and health monitoring to optimize operation of a pulverizer is provided. The system comprises a digital twin that can mimic the performance of the pulverizer in real-time and assist the operators in decision making related to operation, maintenance and scheduling. The digital twin is configured to receives real-time sensor data from a plurality of data sources and provides real-time soft sensing of key health and performance parameters of the pulverizer. One more key aspect of the solution is the advisory system that alerts and recommends corrective actions in terms of parameters controlled through other equipment or changes in operation or design or changes in cleaning schedule.

The present disclosure describes systems and methods for data collection in an industrial environment having self-organization functionality. A method can include analyzing a plurality of sensor inputs, sampling data received from the sensor inputs, and self-organizing at least one of (i) a storage operation of the data, (ii) a collection operation of sensors that provide the plurality of sensor inputs, and (iii) a selection operation of the plurality of sensor inputs. The method may further include receiving instructions directing a mobile data collector unit to operate sensors at a target, transmitting a communication to one or more other mobile data collector units regarding the instructions, and self-organizing a distribution of the mobile data collector unit.

Systems and methods for data collection and detection of noise patterns. A system may 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 an industrial machine, a library 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 industrial machines, and a user interface for accessing the plurality of noise patterns of the noise pattern marketplace.

Monitoring systems and methods for data collection in an industrial environment are described. A system can include a first and second data collector coupled to input channels and a data acquisition circuit to interpret detection values corresponding to the input channels, wherein the sensor data is acquired from a first route of input channels. A data storage may store sensor specifications for sensors corresponding to the input channels and a data analysis circuit may evaluate the sensor data with respect to stored anticipated state information including an alarm threshold level. When the threshold is exceeded, a communication circuit communicates with a second data collector which transmits a state message related to a first input channel. A response circuit changes a routing of the input channels from a first routing to an alternate routing based on the state message from the second data collector.