Patents by Inventor Anja von Beuningen

Anja von Beuningen has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20240092004
    Abstract: Control method, control system, computer-implemented method for determining a predicted weight value of a product produced by an injection molding device and a computer-implemented method for training a machine learning (ML) via an ML method, wherein the trained ML model is configured to determine the predicted weight value of the product produced via the injection molding device, where the method comprises recording and/or determining first production parameters of the injection molding device during production of a first product, recording and/or determining predecessor production parameters of the injection molding device during production of at least one predecessor product and each predecessor weight value of the at least one predecessor product, recording and/or determining a first weight value for the first product, and training the ML model, via a supervised learning method, with the first product parameters, further product parameters, at least one predecessor weight value, and the first weight value
    Type: Application
    Filed: September 15, 2023
    Publication date: March 21, 2024
    Inventors: Anja VON BEUNINGEN, Martin BISCHOFF, Michel TOKIC, Hans-Dimitri PAPDO TCHASSE, Ingo GEIER, Georgios VASIADIS
  • Publication number: 20240002160
    Abstract: A process for controlling a conveyor line for general cargo is provided, the conveyor line including a plurality of consecutive conveyor line portions, each of which is driven by a drive. The drives are controlled by a computing unit using a machine learning model. The machine learning model accomplishes this by getting first input data on the basis of current operating information from at least one further conveyor line that it does not control. The machine learning model has previously been trained using second input data on the basis of operating information of the at least one further conveyor line. The operating information of the at least one further conveyor line in this instance relates to measured values from sensors for detecting general cargo and speeds of conveyor line portions.
    Type: Application
    Filed: June 28, 2023
    Publication date: January 4, 2024
    Inventors: Michel Tokic, Anja von Beuningen, Martin Bischoff, David Grossenbacher
  • Publication number: 20240005149
    Abstract: Using the example of a logistics system including a plurality of parallel conveyor lines for piece goods, which each lead to a combining unit in the conveying direction, it is provided how the temporally and spatially extremely complex control of such an industrial installation can be simulated with the aid of neural networks such that the temporal and spatial dependences are also reliably identified by the neural network. This is effected by digital stopwatches which are applied to the neural network in addition to sensor data from the logistics system and are reset to an initial value whenever motion detectors indicate the passage of a package.
    Type: Application
    Filed: June 26, 2023
    Publication date: January 4, 2024
    Inventors: Michel Tokic, Anja von Beuningen, Niklas Körwer, Martin Bischoff, David Grossenbacher, Michael Leipold
  • Publication number: 20240002159
    Abstract: A process for controlling a conveyor line for general cargo, the conveyor line including a plurality of consecutive conveyor line portions , each of which is driven by a drive. One or more sensors for detecting general cargo are located on at least some of the conveyor line portions. The drives are controlled by means of a computing unit using a machine learning model. The machine learning model accomplishes this by repeatedly receiving input data including a vector of a fixed length, each vector element being associated with a section of the conveyor line and indicating a current proportional occupancy of the respective section by an item of general cargo. Each conveyor line portion is split into a plurality of the sections of identical size. An apparatus or a system for data processing, a computer program, a computer-readable data carrier and a data carrier signal is also provided.
    Type: Application
    Filed: June 23, 2023
    Publication date: January 4, 2024
    Inventors: Michel Tokic, Anja von Beuningen, Martin Bischoff, Niklas Körwer, David Grossenbacher, Kai Heesche
  • Publication number: 20230244792
    Abstract: To protect against the theft of a machine learning module predicting sensor signals, the machine learning module is trained, on the basis of a timeseries of a sensor signal, to predict a later signal value of the sensor signal as first output signal and to output a scatter width of the predicted later signal value as second output signal. The machine learning module is expanded, and the expanded machine learning module is transferred to a user. When an input signal is supplied, a first and a second output signal are derived from the input signal. The checking module then checks whether a later signal value of the input signal lies outside a scatter width indicated by the second output signal by a signal value indicated by the first output signal. An alarm signal is output depending on the check result, if later signal values lie outside the scatter width.
    Type: Application
    Filed: January 19, 2023
    Publication date: August 3, 2023
    Inventors: Anja von Beuningen, Michel Tokic, Boris Scharinger
  • Publication number: 20220406180
    Abstract: A method predicts a switch state and/or a switch time point of a signaling system. The method includes collecting first and second state data, the first and second state data influencing the switch state and/or switch time point. The collection of the first state data includes reading of state data from a signaling system control device of the signaling system by a signaling system interface. The collection of the second state data includes reading in of the state data. A prediction model is provided and configured to make a prediction of the switch time point and/or the switch state of the signaling system based on first and second state data. The switch state and/or the switch time point of the signaling system is predicted via the prediction model using the first and second state data. The predicted switch state and/or switch time point of the signaling system is outputted.
    Type: Application
    Filed: August 4, 2020
    Publication date: December 22, 2022
    Inventors: Harald Frank, Felix Rudolph, Michel Tokic, Anja von Beuningen