Abstract: A method and an apparatus for optimizing diagnostics of rotating equipment is provided. The apparatus includes a device for providing status information about status of the rotating equipment over a series of time windows whereby status can be derived from sensor features of at least one available sensor taking measurements during a predefinable time period, a device for using deep learning which combines provided historic sensor information with sequence of events data indicating warnings and/or alerts of the rotating equipment, whereby status information is supplemented with via deep learning predicted probabilities whether a warning and/or an alert has occurred within a time window, device for providing an amount of textual diagnostic knowledge cases, device for extracting semantic information on text features from the textual diagnostic knowledge cases, and device for combining status information and semantic information into a unified representation enabling optimization of the diagnostics.

Abstract: A method and system for securing asset data in a computing environment includes receiving a request for modifying asset data. Further, the method includes validating the request for modifying the asset data based on pre-stored one or more parameters associated with the one or more assets deployed in the technical installation and the pre-stored one or more parameters associated with the requestor profile using blockchain validation method. The method further includes modifying the pre stored asset data to generate a modified asset data based on the validated request. Furthermore, the method includes generating a digital representation model of the modified asset data using a knowledge graph. Additionally, the method includes outputting the generated digital representation model of the modified asset data on a user interface.

Abstract: The disclosed relates to a system for generating a refined query, whereby the system comprises or is coupled with a search engine for searching through a tree of query modification operations, whereby the root node of said tree is an empty node which represents a given initial query, and comprises at least one processor which is configured to perform the following steps: a) defining a set of query modification operators which can be inserted into said tree; b) receiving a second set of reference query results; c) receiving a first set of current query results from a currently given query comprising one or more triple patterns; d) contrasting the first set of query results with the second set of query results by assessing the differences between the two query results; e) running the search engine which is configured to perform the following steps: f) selecting a node of said tree by a computed score derived from the assessed result; g) selecting any query modification operator of the defined set of query modif

Abstract: A computer-implemented method and system for assigning at least one query triplet to at least one respective class. The at least one respective class is true or false. The method includes the steps of providing the at least one query triplet and a knowledge graph with a plurality of triples and extracting at least one affirmative argument using reinforcement learning on the basis of the at least one query triplet and the knowledge graph. The at least one affirmative argument indicates that the at least one query triplet is true. The method further includes extracting at least one opposing argument using reinforcement learning on the basis of the at least one query triplet and the knowledge graph. The at least one opposing argument indicates that the at least one query triplet is false. The method further includes assigning the at least one query triplet to the at least one respective class using supervised machine learning depending on the at least two arguments.

Abstract: The disclosed relates to a system for generating a refined query, whereby the system comprises or is coupled with a search engine for searching through a tree of query modification operations, whereby the root node of said tree is an empty node which represents a given initial query, and comprises at least one processor which is configured to perform the following steps: a) defining a set of query modification operators which can be inserted into said tree; b) receiving a second set of reference query results; c) receiving a first set of current query results from a currently given query comprising one or more triple patterns; d) contrasting the first set of query results with the second set of query results by assessing the differences between the two query results; e) running the search engine which is configured to perform the following steps: f) selecting a node of said tree by a computed score derived from the assessed result; g) selecting any query modification operator of the defined set of query

Abstract: A method and system for generating digital representation of asset information in a cloud computing environment. The method includes extracting asset information associated with one or more assets from plurality of structured and unstructured data sources. The one or more assets are deployed in an industrial environment. Further, the method includes processing the extracted asset information based on a first predefined set of rules. The method further includes generating a digital representation of the processed asset information based on plurality of user devices. Furthermore, the method includes storing the generated representation of the processed asset information in a predefined file format in a database. The predefined file format is compatible with a format used by the plurality of user devices.

Abstract: Provided is a bot for a communication platform, wherein the bot is set up to read in an input data record, wherein the input data record includes a plurality of tickets or a plurality of numerical representations of tickets, listen in on at least one communication process between at least two persons on the communication platform, wherein the at least one communication process has at least one service case or at least one numerical representation of a service case, and generate an output data record, wherein the output data record has the input data record and the at least one communication process. A corresponding communication platform, a computer-implemented method, and a computer program product are also provided.

Abstract: An embedded control system for a field device of an automation system includes: a diagnostic application interface to a backend server for signal analytics information, complex event pattern information, and diagnostic information; a physical process interface to a signal source for transferring signal data; a signal evaluation component for comparing received signal analytics information with received signal data to identify a first and a second event; an event processing component for applying received event pattern information to the first and second identified events to identify a first classified event; and a diagnostic reasoning component for deriving causal dependencies between the first classified event and a further classified event with regard to diagnostic information to identify a root cause for the first classified event or predict an impact of the first classified event.

Abstract: The monitoring of a technical system using sensor data. In the event of the failure of a sensor, in this case, for the failed sensor, virtual sensor data are created on the basis of the remaining functional sensors. In this case, the sensors for the calculation of the virtual sensor data are selected in two stages. In a first step, firstly, possible candidates of sensors are ascertained on the basis of a knowledge-based approach and the topology of the system. A second step involves calculating a mathematical relationship between the sensor data of a faulty sensor and the possible candidates of sensors for the calculation of the virtual sensor data. Those sensors which form a suitable basis for the calculation of the virtual sensor data can be identified in this way.

Abstract: A computer-implemented method for efficient processing of pooled data shared by users of a cloud platform, the method includes the steps of uploading at least one dataset by a client device of a user to said cloud platform; calculating similarity scores indicating a degree of similarity between the current uploaded dataset and datasets previously uploaded by client devices of other users; and performing a procedure selected by a user on the cloud platform based on pooled data including the current dataset of the respective user and the datasets previously uploaded from client devices of other users stored in a database of the cloud platform having calculated similarity scores in relation to the current uploaded dataset of the respective user exceeding a configurable similarity score threshold, is provided.

Abstract: A computer-implemented method for configuring a computing device for predictive maintenance, a computer-implemented method for predictive maintenance as well as a predictive maintenance apparatus are disclosed. Training log files including event sequences are examined iteratively for sequences of increasing length in order to determine a set of configuration data containing event sequences that have high predictive power for a system failure. Forward and backward gap values are defined such that not only sequences in the exact same temporal order as in the training log files are examined but also sequences with slightly different temporal ordering. In this way, possibly imprecise and/or incorrect time stamps in log files are compensated.

Abstract: A method predicts a derivable event in a logistic network. The method includes generating a Bayesian network describing a structure of at least a part of a logistic network. A query is received for the derivable event that depends on a combination of base events in the logistic network. The Bayesian network is instantiated for a plurality of points in time. A prediction of the derivable event is deduced from the instantiated Bayesian network by use of complex event processing.

Abstract: Provided is a computer-implemented technology which generates rules for completion of a knowledge graph by producing, with a generic machine learning model or one that is trained on the knowledge graph, inferred triples, optionally refines and filters the produced rules along predefined user settings and provides the resulting rules, along with the inferred facts covered by the rules, as candidates for completion of the knowledge graph.

Abstract: An Internet of Things, IoT, structure including application layers with a 3D Adaption Matrix, a server for an IoT structure, a device for an IoT application and a method for manipulating dependencies between the application layers is provided. The 3D Adaption Matrix includes adaption rules, which adaption rules are specified once and which adaption rules enable specifying dependencies between the application layers. A module of the IoT structure is configured to employ the adaption rules for an IoT application.

Abstract: Provided is a method for providing measured values of a technical installation in which measured values in at least one measurement series are captured, wherein a respective measured value is provided by a measurement sensor for a respective physical measurement variable in the technical installation for a respective measurement time. The measured values are categorized as normal measured values or anomalous measured values with the aid of a threshold value comparison and at least one further method stage. The further method stage comprises calculating one or more statistical position parameters for selected measured values from the same measurement series and/or different measurement series. The method makes it possible to increase the reliability of the measured values provided. A technical system comprising the technical installation, at least one measurement sensor and a program-controlled device, and a method for operating the technical system are also proposed.

Abstract: A computer-implemented method for configuring a computing device for predictive maintenance, a computer-implemented method for predictive maintenance as well as a predictive maintenance apparatus are disclosed. Training log files including event sequences are examined iteratively for sequences of increasing length in order to determine a set of configuration data containing event sequences that have high predictive power for a system failure. Forward and backward gap values are defined such that not only sequences in the exact same temporal order as in the training log files are examined but also sequences with slightly different temporal ordering. In this way, possibly imprecise and/or incorrect time stamps in log files are compensated.

Abstract: Provided is a method for providing measured values of a technical installation in which measured values in at least one measurement series are captured, wherein a respective measured value is provided by a measurement sensor for a respective physical measurement variable in the technical installation for a respective measurement time. The measured values are categorized as normal measured values or anomalous measured values with the aid of a threshold value comparison and at least one further method stage. The further method stage comprises calculating one or more statistical position parameters for selected measured values from the same measurement series and/or different measurement series. The method makes it possible to increase the reliability of the measured values provided. A technical system comprising the technical installation, at least one measurement sensor and a program-controlled device, and a method for operating the technical system are also proposed.

Abstract: A method for generating at least one recommendation includes receiving a case embedding, generating the at least one recommendation based on the case embedding using deep learning, and outputting the at least one recommendation.

Abstract: The monitoring of a technical system using sensor data. In the event of the failure of a sensor, in this case, for the failed sensor, virtual sensor data are created on the basis of the remaining functional sensors. In this case, the sensors for the calculation of the virtual sensor data are selected in two stages. In a first step, firstly, possible candidates of sensors are ascertained on the basis of a knowledge-based approach and the topology of the system. A second step involves calculating a mathematical relationship between the sensor data of a faulty sensor and the possible candidates of sensors for the calculation of the virtual sensor data. Those sensors which form a suitable basis for the calculation of the virtual sensor data can be identified in this way.

Abstract: A control apparatus of an automation system, the control apparatus includes a database adapted to store time series data in a historian data source and adapted to store events derived from the time series data based on event detection rules in an event data source, wherein a semantic data or event query received by the control apparatus is mapped to a corresponding data source of the database to retrieve the queried data or event which are contextualized using an ontological context model of the automation system stored in the database and output by control apparatus in a semantic format is provided.