Abstract: A system includes an Industrial facility having a first memory storing first machine-executable components and a first processor coupled to the first memory and designed to execute the first machine-executable components. The first machine-executable components include a cloud connectivity component, a second memory residing at a cloud platform and coupled to a second processor storing second machine-executable components and is designed to execute the second machine-executable components which include a management component. The management component belongs to an entity that produces Industrial devices residing at the industrial facility. During an Interaction with the cloud connectivity component, the management component defines an allowed installation context and authorizes installation of a computer program on the Industrial devices only within the scope of the allowed installation context, wherein the interaction excludes sending the computer program to the management component.

Abstract: Provided is a deployment platform for deployment of an industrial application on an edge computing device, ECD, connected to the controller of a machine tool, MT, the deployment platform including a model management component, MMC, adapted to instantiate a generic machine tool model, GMTM, stored in a memory to provide a machine instance model, MIM, of the respective machine tool, MT, on the basis of a machine tool data report, MTDR, received by the model management component, MMC, from the edge computing device, ECD, of the respective machine tool, MT, and further adapted to convert generic data requirements, gR, of a generic industrial application into machine tool specific requirements, mtsR, using the machine instance model, MIM, of the respective machine tool, MT, wherein an instantiated industrial application for the machine tool, MT, is provided by instantiating the generic industrial application by extending its configuration data with machine tool specific requirements.

Abstract: A system device and a method for managing access to data in an automation environment are disclosed. The data is associated with assets in an automation environment, where the data includes one of restricted data and unrestricted data. The automation environment is accessible via one or more computing platforms including a plurality of computing resources that are classifiable into a trusted computing platform and a non-trusted computing platform. The method includes classifying analytics operations performable on the data into a first operation set that is executable on the trusted computing platform. The analytics operations are associated with one or more applications executable on at least one of the computing platforms. The method includes enabling access to at least one of the unrestricted data and a first unrestricted output of the first operation set outside the trusted computing platform by a communication operation.

Abstract: A method for controlling access to at least one computer program which is accessible and executable on an embedded system is disclosed. The embedded system is provided and comprises two different runtime modes, a first runtime mode and a second runtime mode. In the first runtime mode, a predefined set of IT-security constraints is associated with the at least one computer program. In the second runtime mode at least a part of the predefined set of the IT-security constraints associated with the at least one computer program is void and the at least one computer program is accessible and executable with elevated rights for performing software development operations on the at least one computer program. The embedded system is set into the second runtime mode for a predefined time period. After the predefined time period is expired, the embedded system is set into the first runtime mode.

Abstract: A method for transmitting software artifacts from a source network to a target network is disclosed. Each target and source network is assigned to a proxy system comprising a plug-in. The transmission is monitored on the target network side. A target network-Internal information structure is provided containing entries, each of which characterizes a software artifact that can be downloaded when authorization is granted by an operator of the target network by the plug-in. The entries are read from the target network-internal information structure. Requests from the target network relating to the availability of new software artifacts are received on behalf of the source network. For each request, at least one entry which matches the request is searched in the target network-internal information structure. Based on the at least one matching entry being present in the target network-internal information structure, either the software artifact is retrieved or the request is blocked.

Abstract: System device and method for managing access to data in an automation environment is disclosed. The data is associated with assets (112, 312, 314) in an automation environment (110, 310), wherein the data comprises one of restricted data and unrestricted data, and wherein the automation environment (110, 310) is accessible via one or more computing platforms comprising a plurality of computing resources that are classifiable into a trusted computing platform (150, 250, 350) and a non-trusted computing platform (170, 260, 360).

Abstract: Data are sent from an internal data processing system of an industrial plant to an external data processing system of the industrial plant by generating with an industrial edge device data packets from data related to an industrial machine, and generating therefrom signed data packets signed with a first digital signature. While the signed data packet are read, a user-defined data filter is applied, which lets either pass or rejects the signed data packets. The data packets that passed the user-defined data filter are then sent to the external data processing system.

Abstract: A system for providing a generic query interface for industrial systems of different customers includes an interface configured to input customer queries of customer industrial systems. The system also includes a query processing unit that is configured to automatically perform a query decomposition of the input customer query into query parts based on a query reformulation model stored in a database of the system. For each decomposed query part, it is determined whether the decomposed query part is available in an application semantic model stored in the database of the system. Query parts not available in the application semantic model are automatically reformulated based on the query reformulation model, and a query recomposition of the query parts available in the application semantic model and the reformulated semantic query parts is automatically performed to generate a generic query applied to an application logic of the system to provide a query result.

Abstract: Provided is a process optimizer apparatus for optimizing dynamically an industrial production process of a production plant including physical production modules, the process optimizer including a watchdog component adapted to monitor the production modules of the production plant to detect configuration changes within the production plant; a model comparator component adapted to evaluate a production plant data model of the production plant including digital twin data models related to physical production modules of the production plant to identify automatically deviating model elements of digital twin data models related to physical production modules of the production plant affected by the configuration changes detected by the watchdog component; and a process resequencer component adapted to perform a dynamic process optimization of the at least one production process of the production plant depending on the deviating model elements identified by the model comparator component.

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: A system for providing a generic query interface for industrial systems of different customers includes an interface configured to input customer queries of customer industrial systems. The system also includes a query processing unit that is configured to automatically perform a query decomposition of the input customer query into query parts based on a query reformulation model stored in a database of the system. For each decomposed query part, it is determined whether the decomposed query part is available in an application semantic model stored in the database of the system. Query parts not available in the application semantic model are automatically reformulated based on the query reformulation model, and a query recomposition of the query parts available in the application semantic model and the reformulated semantic query parts is automatically performed to generate a generic query applied to an application logic of the system to provide a query result.

Abstract: Provided is a deployment platform for deployment of an industrial application on an edge computing device, ECD, connected to the controller of a machine tool, MT, the deployment platform including a model management component, MMC, adapted to instantiate a generic machine tool model, GMTM, stored in a memory to provide a machine instance model, MIM, of the respective machine tool, MT, on the basis of a machine tool data report, MTDR, received by the model management component, MMC, from the edge computing device, ECD, of the respective machine tool, MT, and further adapted to convert generic data requirements, gR, of a generic industrial application into machine tool specific requirements, mtsR, using the machine instance model, MIM, of the respective machine tool, MT, wherein an instantiated industrial application for the machine tool, MT, is provided by instantiating the generic industrial application by extending its configuration data with machine tool specific requirements.

Abstract: Provided is a method for machine learning of analytical models, AMs, including core model components, CMCs, shared between tasks, t, of different customers and including specialized model components, SMCs, specific to customer tasks, t, of individual customers, wherein the machine learning of the analytical models, AMs, is performed collaboratively based on local data, LD, provided by machines of the customer premises of different customers without the local data, LD, leaving the respective customer premises.

Abstract: Provided is a a process optimizer apparatus for optimizing dynamically an industrial production process of a production plant including physical production modules, the process optimizer including a watchdog component adapted to monitor the production modules of the production plant to detect configuration changes within the production plant; a model comparator component adapted to evaluate a production plant data model of the production plant including digital twin data models related to physical production modules of the production plant to identify automatically deviating model elements of digital twin data models related to physical production modules of the production plant affected by the configuration changes detected by the watchdog component; and a process resequencer component adapted to perform a dynamic process optimization of the at least one production process of the production plant depending on the deviating model elements identified by the model comparator component.

Abstract: A method for manufacturing a product according to a production plan includes a plurality of production steps. The method includes providing a plurality of production modules, for each production step of the plurality of production steps, independently executing a negotiation process for selecting a production module, and disposing the selected production modules, each selected for performing one of the production steps, for performing the plurality of production steps. The negotiation process includes designating production modules that are capable of performing the production step, assigning module parameters to the designated production modules, calculating a cost for each of the designated production modules based on the module parameters of the respective production module, and selecting one of the designated production modules as a function of the calculated cost.

Abstract: A device for coupling a machine, in particular a machine tool, having a number N of data sources for providing data of the machine in data source-specific file formats having a plurality of applications is provided. The device includes a transformation unit, which is designed to transform data of one of the N data sources present in one of the data source-specific data formats to data of a generic semantic data model for at least one of the applications and data of one of the applications present in the generic semantic data model to data of one of the data source-specific data formats for one of the N data sources. The transformation unit thus advantageously establishes data interoperability between the respective application and the respective data source of the machine. Also provided is a method and to a computer program product for coupling a machine to a plurality of applications.

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: A method for storing data units from a data source in a selectable storage device from a storage system, wherein a data unit attribute is allocated to each data unit and a storage attribute is allocated to each storage device, comprising the following steps: checking and adapting the data unit attributes at specified times during an operation of the storage devices; evaluating the data unit attributes and the storage attributes for generating storage system state data; and, for each data unit, selecting a storage device depending on the allocated data unit attributes, at least a selection of the storage attributes and the storage system state data, and storing the respective data unit) in the selected storage device; wherein the data unit attributes and/or storage attributes comprise information relating to a selection and storage of data units at previous times.

Abstract: A method for manufacturing a product according to a production plan includes a plurality of production steps. The method includes providing a plurality of production modules, for each production step of the plurality of production steps, independently executing a negotiation process for selecting a production module, and disposing the selected production modules, each selected for performing one of the production steps, for performing the plurality of production steps. The negotiation process includes designating production modules that are capable of performing the production step, assigning module parameters to the designated production modules, calculating a cost for each of the designated production modules based on the module parameters of the respective production module, and selecting one of the designated production modules as a function of the calculated cost.

Abstract: A novel power allocation method, as early as in the procurement of electricity, takes account of network congestion and simultaneously enables logical and physical separation of network control and power allocation. An allocation component and a network monitoring component separately from one another detect tasks relating to the allocation of power and via predetermined interfaces exchange information or intermediate states relating to the allocation before the allocation is actually implemented for power control. This enables adaptive power control of power sources and consumer units and the flexible implementation of a plurality of requirements of a modern power distribution network.