Abstract: A method, device for identifying causes of faults in automated systems and an automated system which forms the device for identifying causes of faults in automated systems, wherein within a digital twin of the automated system, at least one element of the digital twin is assumed to be faulty and then simulated using the digital twin until a fault time, and where at least one faulty element of the automated system is identified as the cause of a fault based on the at least one element assumed to be faulty.

Abstract: A method, device for identifying causes of faults in automated systems and an automated system which forms the device for identifying causes of faults in automated systems, wherein within a digital twin of the automated system, at least one element of the digital twin is assumed to be faulty and then simulated using the digital twin until a fault time, and where at least one faulty element of the automated system is identified as the cause of a fault based on the at least one element assumed to be faulty.

Abstract: A method and apparatus for determining differences between an automated installation and a digital twin of the automated installation and to an automated installation that includes the apparatus, wherein a sensor unit is fastened to a process material and passes through an automated installation together with the process material where, during this process, the sensor unit continuously records at least one measurement variable, a temporal profile of the recorded measurement variable is compared with a temporal profile of a corresponding simulated measurement variable and if there is a difference between the temporal profiles, then the location in the automated installation at which the difference is present is identified.

Abstract: A computer-aided method, based on at least one specification parameter, construction parameters are generated by a complex device by a trained neural network is provided. The neural network is trained based on reference data and operating data, wherein a non-insignificant part of the data is used for training from the iteration steps of the specialist. The reference data characterizes a plurality of complex devices which have been constructed or produced in the past and their respective at least one specification parameter and construction parameters thereof. The operating data characterizes the plurality of complex devices and their respective operating parameters which correspond to the respective construction parameters.

Abstract: A computer-supported creation of an interdisciplinary simulation model of a physical-technical device is provided. Based on a predefined database, which is indicative of the physical-technical behaviour of the device, discipline-specific simulation components of the device and at least one interface for each of the simulation components are created, such that statuses of the simulation components can be synchronised with one another by means of the interfaces. In addition, each discipline-specific simulation component models a corresponding discipline-specific aspect of the physical-technical behaviour of the device. The created simulation components represent the simulation model together with the interfaces.

Abstract: A method and apparatus for determining differences between an automated installation and a digital twin of the automated installation and to an automated installation that includes the apparatus, wherein a sensor unit is fastened to a process material and passes through an automated installation together with the process material where, during this process, the sensor unit continuously records at least one measurement variable, a temporal profile of the recorded measurement variable is compared with a temporal profile of a corresponding simulated measurement variable and if there is a difference between the temporal profiles, then the location in the automated installation at which the difference is present is identified.

Abstract: A method and assembly for identifying animals, wherein according to the invention, for the identification of an animal, first a sensor checks whether a body part of the animal to be identified is in a predefined position is provided. With a positive test result, an imaging sensor is prompted to capture an image of the nose of the animal. According to the invention, by means of a pattern recognition method, a texture of the nose is then detected on the captured image and extracted and the animal is assigned a unique identifier based on the extracted nose texture.

Abstract: A method and an apparatus for automatically generating a target simulation model for a defined simulation object, provides artifacts of the simulation object in a data base; extracts the information needed for generating the target simulation model from the artifacts; maps the object elements based on the defined objective into the elements of the target simulation model; and assembles the extracted information and the mapped elements to generate the target simulation model. The artifacts describe the structure, the behavior, and the physics of the object elements with mechatronics simulation tags representing implicit indirect engineering information not extracted automatically by a tool.

Abstract: A method and an apparatus for automatically generating a target simulation model for a defined simulation object, provides artefacts of the simulation object in a data base, wherein the artefacts describing the structure, the behavior and the physics of the object elements, and the artefacts have mechatronics simulation tags (MST) representing implicit indirect available engineering information; extracts out of the artefacts the information needed for generating the target simulation model; maps the object elements based on the defined objective into the elements of the target simulation model; and assembles the extracted information and the mapped elements to generate the target simulation model. The elements of the master model are defined and transformed into the target model. A lot of time is spent for setting up simulation models. The modeling effort can be reduced drastically wherein the reduction is direct saving of real manpower, time and with this saving money.