Abstract: A method for recommending an operational command includes receiving an alarm from a sensor and/or an operator; obtaining the current state of the plant that includes a current process value and/or operational command; comparing the current state to a list of historic states, each comprising a plurality of historic process values and/or historic operational commands; when the current state matches a subset of at least one of the historic states, starting a simulation and running a plurality of simulations, each based on a variation of at least one of the historic operational commands; determining, for each simulation of the plurality of simulations, a quality value, based on at least one quality criterion; and recommending the variation of the operational command that resulted in the simulation with the highest quality value.

Abstract: There is provided an explainer system for explaining an alarm raised by a machine learned model of an industrial automation system. The explainer system is configured to: receive model output from the machine learned model trained to predict anomalous behaviour in the industrial automation system and to raise the alarm; process the model output using at least one prediction explanation technique to identify at least one influential feature which contributed to the model output; use the identified at least one influential feature to extract contextual information from at least one machine-readable information source pertaining to the industrial automation system; and prepare the extracted contextual information for display to an operator of the industrial automation system, to enable the operator to select an appropriate action to take in response to the alarm for ensuring proper functioning of the industrial automation system.

Abstract: A method for determining an appropriate sequence of actions to take during operation of an industrial plant includes obtaining values of a plurality of state variables that characterize an operational state of the plant (or a part thereof); encoding by at least one trained state encoder network the plurality of state variables into a representation of the operating state of the plant; mapping by a trained state-to-action network the representation of the operating state to a representation of a sequence of actions to take in response to the operating state; and decoding by a trained action decoder network the representation of the sequence of actions to the sought sequence of actions to take.

Abstract: A method for system monitoring in a hierarchical network of distributed edge devices includes a master edge, first and second client edges connected via a first communication interface to the master edge, the method including receiving sensor data from a sensor device via a second communication interface, determining a first local model parameter representing a machine learning (ML) model of the at least first client edge based on the sensor data; storing the first local model parameter in a data storage of the at least first client edge; collecting the first local model parameter from the at least first client edge; and generating a global ML model based on the at least first local model parameter, wherein the global ML model is used for monitoring a system performance or a condition of the system.

Abstract: A system and method for enabling an efficient data processing in a distributed network of devices includes collecting first data from at least one client device sent by at least one plant device via a first communication interface; storing the first data in a data storage; profiling the first data to obtain characteristic information of the collected first data; determining a data processing strategy upon a result of the characteristic information of the first data; processing the first data according to the data processing strategy and deciding which data of the first data need to be sent to the master device via a second communication interface.

Abstract: A method for determining the state of health of an industrial process executed by at least one industrial plant comprising an arrangement of entities, and the state of each such entity, includes obtaining values of the entity state variables; providing the values to a model to obtain a prediction of the state of health; determining propagation paths for anomalies between said entities; determining importances of the states of health of the individual entities for the overall state of health of the process; and aggregating the individual states of health of the entities to obtain the overall state of health of the process.

Abstract: A method for training a prediction model includes obtaining training samples representing states of the process that do not cause the undesired event; obtaining based on a process model and a set of predetermined rules that stipulate states having an increased likelihood of the undesired event occurring; training samples representing states with an increased likelihood to cause the undesired event; providing samples to the to-be-trained prediction model to obtain a prediction of the likelihood for occurrence of the undesired event in a state of the process represented by the respective sample; rating a difference between the prediction and the label of the respective sample using a predetermined loss function; and optimizing parameters such that, when predictions are made, the rating by the loss function improves.

Abstract: A computer-implemented method for orchestrating execution of workloads on nodes includes determining a set of requirements for resources needed for execution of the workload; determining for each compute node an availability of the resources required; establishing multiple candidate configurations having an assignment of each compute workload to at least one pair of a compute node and a working class, wherein different working classes differ at least in the degree of retention of the compute workload in memory and/or in at least one cache of the compute node after execution; computing for each candidate configuration at least one figure of merit with respect to at least one given optimization goal; and determining a candidate configuration with the best figure of merit as the optimal configuration.

Abstract: A method for providing an efficient communication in a hierarchical network of distributed devices includes collecting first data from a first client device sent by a sensor via a second communication interface; storing the first data in a data storage; determining metadata of the first data; receiving a requirement information of the first data; generating classification information of the first data according to the metadata and the requirement information; providing the classification information to a master device and/or to a second client device according to a rule; and updating the classification information when the first data is changed.

Abstract: An assistance system comprises a plant topology repository comprising a representation of the components of the plant and relations between the components; a monitoring subsystem configured for monitoring signals from the components and for monitoring a related event, as a key for the monitored signals; an aggregation subsystem configured for storing a plurality of the monitored signals and the related events, wherein at least one of the events is the abnormal situation; an identification subsystem configured for comparing currently monitored signals to stored monitored signals and the related event; and an evaluation subsystem configured for outputting a predefined action, if the currently monitored signals match to the event that is the abnormal situation.

Abstract: A method for generating and/or augmenting an execution protocol for an SOP in an industrial plant includes providing at least one SOP of the plant, which includes a plurality of steps; providing measurement data; for each step of the SOP, determining from the measurement data a subset of the measurement data that is indicative of actions performed for the purpose of executing this particular step of the SOP; and aggregating the subset of the measurement data determined for each step of the SOP into at least one instruction for executing this particular step of the SOP, wherein this instruction is part of the sought protocol.

Abstract: A method for providing a solution strategy for a current event in industrial process automation includes monitoring a process for events and recording manual user action data, upon occurrence of an event, acquiring the recorded data regarding manual user actions before, during, and after the occurrence of the event, learning a procedure for handling the event based on the acquired data, and applying the learnt procedure to a currently occurring event.

Abstract: A method includes acquiring state variables that characterize an operational state of an industrial plant; acquiring interaction events of a plant operator interacting with the distributed control system via a human-machine interface; determining based on the interaction events, and with state variables as input data, whether one or more interaction events are indicative of the plant operator executing a task that is not sufficiently covered by engineering of the distributed control system. When this determination is positive, mapping the input data to an amendment and/or augmentation for the engineering tool that has generated the application code.

Abstract: A system and method for providing a configuration for data extraction from an automation system includes a signal selection agent configured to: receive a user selection of at least one module of the automation system; generate, for display to the user, a user interface identifying one or more selectable signals associated with the selected module and displaying one or more guidance elements comprising data mined from data sources pertaining to the automation system for guiding the user in the selection of relevant signals; receive a user selection of one or more of the selectable signals; and automatically generate the configuration for data extraction on the basis of the selected signals.

Abstract: An industrial plant operator intervention system for use in an industrial plant includes a processing unit configured to monitor and analyze industrial plant operation data to detect an anomaly in the industrial plant operation data that warrants initiating an operator intervention, and in response to detecting the anomaly, automatically determine a user interface configuration of a user interface to be presented to a designated operator who is to perform the operator intervention. The user interface configuration is determined on the basis of technical context data, including industrial plant operation data associated with the anomaly, and on the basis of operator data pertaining to the designated operator, in such a manner that an anomaly-related and operator-specific user interface configuration is obtained.

Abstract: A system for building data exchange includes an information modelling unit, which includes a digital twin model, a building information modelling, wherein the information modelling unit provides modelling data, an extractor configured to determine extraction data from an instance, an extractor configured to determine extraction data from an instance of the model using the modelling data, at least one converter engine, a compositor to populate the converted data into a converted instance, and a compositor to populate the converted data into a converted instance.

Abstract: A decision support system and method for an industrial plant is configured and operates to: obtain a causal graph modeling causal assumptions relating to conditional dependence between variables in the industrial plant; obtain observational data relating to operation of the industrial plant; and perform causal inference using the causal graph and the observational data to estimate at least one causal effect relevant for making decisions when operating the industrial plant.