Abstract: Assistance apparatus for automatically identifying failure types of a technical system is provided including at least one processor configured to determine for each sensor data a set of specific temporal courses of first time series of the sensor data of the sensor and assign a symbolic representation to each of the different specific temporal courses, provide at least one failure pattern, obtain more than one monitored time series of sensor data of the technical system, each of them divided into a sequence of time segments, and automatically assign to each time segment a symbolic representations according to the temporal course of the sensor data in the time segment, calculate a similarity measure for the set of symbolic representations of a selected time interval, determine a ranking of the failure pattern depending on decreasing values of the calculated similarity measure, and output the ranking.

Abstract: A computer implemented method for automatically generating a behavior tree program for controlling a machine includes the steps of: transmitting a sequence of machine commands input by a user from a user interface to a controller, receiving supervision data in the user interface from the controller while the machine commands are executed in the controller controlling the machine, observing and copying the machine commands and supervision data transmitted between the controller and the user interface, storing the machine commands and the supervision data in a logging unit, generating a behavior tree program derived from the stored machine commands and the supervision data by statistical inference, and sending the generated behavior tree program to the controller unit to control the machine.

Abstract: A method for checking samples for defects is provided, in which image data of the samples are recorded and classified into predeterminable defect categories by a defect detection algorithm, and the samples classified into a defect category are represented in a multi-dimensional confusion matrix as a classification result of the defect detection algorithm, characterized in that—miniature images which reproduce the image data are assigned according to the classified defect categories of the image data to segments of the confusion matrix which represent the defect categories, and these miniature images are displayed visually, —the miniature image is assigned by an interaction with a user or a software robot to a different segment from the assigned segment of the confusion matrix, and is either provided as training image data for the defect detection algorithm or is output as training image data for the defect detection algorithm.

Abstract: An evaluation framework for a generated dataset of a data generation algorithm such as a generative adversarial network is provided. The generated dataset includes a plurality of iterations of multiple instances of generated time series of data points. The evaluation framework provides multiple views. A first view includes at least one distance measure. The at least one distance measure is between the multiple instances of the generated time series and multiple instances of a reference time series, as a function of the plurality of iterations.

Abstract: A computer implemented method for automatically generating a behavior tree program for controlling a machine includes the steps of: transmitting a sequence of machine commands input by a user from a user interface to a controller, receiving supervision data in the user interface from the controller while the machine commands are executed in the controller controlling the machine, observing and copying the machine commands and supervision data transmitted between the controller and the user interface, storing the machine commands and the supervision data in a logging unit, generating a behavior tree program derived from the stored machine commands and the supervision data by statistical inference, and sending the generated behavior tree program to the controller unit to control the machine.

Abstract: A method for the computer-aided processing of operating data relating to a technical system, wherein the operating data have been captured during operation of the technical system in a predefined operating interval and are stored as digital data in a memory is provided. A pair of first state variables and one or more second state variables with corresponding state values of the technical system at the particular operating time are extracted from the operating data by the method. A two-dimensional representation is generated on a display of a user interface by these state variables. Bar charts for different state ranges of the pairs of first state variables are generated in this representation on the basis of the evaluation of a threshold value criterion, wherein the bar charts represent, inter alia, how many states of the technical system within the particular state range can be classified as critical.

Abstract: A method for parameterizing an anomaly detection method, which takes a multiplicity of sensor data points as a basis for performing a density-based cluster method, including a) mapping each sensor data point in a data space into a pixel data point in a pixel space, b) reproducing at least one operation of the density-based cluster method in the data space by means of at least one pixel operation in the pixel space, c) receiving at least one parameter value for each parameter of the density-based cluster method, d) applying the at least one pixel operation in accordance with the parameter values to the pixel data points e) outputting a cluster result in visual form in the pixel space, and f) providing the received parameter values for the anomaly detection method, and an assistance apparatus for parameterizing an anomaly detection apparatus that performs the anomaly detection method.

Abstract: A method for the computer-aided processing of operating data relating to a technical system, wherein the operating data have been captured during operation of the technical system in a predefined operating interval and are stored as digital data in a memoryis provided. A pair of first state variables and one or more second state variables with corresponding state values of the technical system at the particular operating time are extracted from the operating data by the method. A two-dimensional representation is generated on a display of a user interface by these state variables. Bar charts for different state ranges of the pairs of first state variables are generated in this representation on the basis of the evaluation of a threshold value criterion, wherein the bar charts represent, inter alia, how many states of the technical system within the particular state range can be classified as critical.