Siemens Aktiengesellschaft

Siemens Industry Software Gmbh

Dirk Hartmann

Steffen Fries

Suraj Ravi Musuvathy

Birgit Obst

Florian Ulli Wolfgang Schnös

Utz Wever

Christoph Kiener

Sven Tauchmann

Meinhard Paffrath

Stefan Gavranovic

Hans-Georg Köpken

Lucia Mirabella

David Madeley

David Bitterolf

Roland Gersch

Uwe Blöcher

Mohamed Khalil

Christoph Heinrich

Peter Philip Lonsdale Nanson

Daniel Regulin

Philipp Emanuel Stelzig

Richard Charles Collins

Michael Jaentsch

Christoph Ernst Ludwig

Tobias Kamps

Erik Olof Johannes Wannerberg

Hiren Dedhia

Rishith Ellath Meethal

Florian Ulli Wolfgang SCHNÖS

A computing system may include a design access engine and a design processing engine. The design access engine may be configured to access an object design to be constructed through additive manufacturing. The design processing engine may be configured to represent the object design as a combination of coarse geometric elements and high-resolution lattice elements and process the object design based on both the coarse geometric elements and the high-resolution lattice elements. Processing of the object design may include generation of lattice infills, lattice simulations, or a combination of both.

Object design processing using coarse geometric elements and high-resolution lattice elements

To separate excess material, the component moved by a movement device that is controlled by movement data, and a fill level of the component with material is measured. A process for emptying material from the component simulated for each different initial fill level with material, wherein movement data, which specify a simulated movement of the component, and a simulated fill level progression resulting from the simulated movement are assigned to the associated initial fill level. In addition, a corresponding initial fill level is selected in accordance with the measured fill level, and the movement device is controlled by movement data which are assigned to the selected initial fill level. The fill level is measured and compared to a simulated fill level progression assigned to the selected initial fill level. The steps of selecting a corresponding initial fill level (SAFG) and controlling the movement device (BV) are carried out.

Method and assembly for separating excess material from an additively manufactured component

For detecting a cyber-attack on a machine controller, a concurrent simulation of the machine is run in a secured access domain. From the machine controller actual control data are transmitted to the machine and resulting monitoring data are transmitted to a monitoring device. Furthermore, sensor data of the machine are transmitted to the concurrent simulation on a first secured transmission path. Based on the sensor data, the concurrent simulation simulates an operational behavior of the machine, thus inferring simulated monitoring data. The simulated monitoring data are then compared with the resulting monitoring, and an alarm signal is triggered depending on the comparison.

Method and system for detecting a cyber-attack on a machine controller

A method for operating a numerical controlled machine comprising receiving a sequence of control commands which, when executed by a numerical controlled machine, cause the numerical controlled machine to machine a workpiece to obtain a predetermined workpiece geometry, wherein the sequence of control commands includes while machining the workpiece based on the received sequence of control commands measuring a value of a first interaction parameter for a first position of the tool, comparing a measured value of the first interaction parameter for the first position of the tool with the simulated value of the first interaction parameter for the first position of the tool, and determining an adapted value of the second interaction parameter for a following position of the tool based on a result of the comparison.

Online multi-force-adaption during machining

In order to separate excess material from an additively manufactured component, spatially resolved structural data on the component are received. On the basis of the structural data, a process for emptying material from the component is simulated, wherein a sequence of emptying poses of the component is determined. For an associated emptying pose: the component is moved into the associated emptying pose in accordance with the simulated emptying process, movement of material is detected by sensors, as a result of a detection of a decrease in the movement of material, a trigger signal is generated, and a movement of the component into a subsequent emptying pose is initiated by the trigger signal, the trigger signal being considered higher priority than the simulated emptying process.

In order to be able to take into account machining configurations more flexibly, a method for optimizing numerically controlled machining of a workpiece includes ascertaining geometric interaction data. A relationship between a force to be expected and a configuration parameter of the machining is determined on the basis of the interaction data. The force is calculated during the machining on the basis of the relationship and a current value of the at least one configuration parameter. The machining is adapted depending on the calculated force.

Computer-aided optimization of numerically controlled machining of a workpiece

Provided is a method for determining a physical shape having a predefined physical target property that includes calculating a sensitivity landscape on the basis of a shape data record for the physical shape with the aid of a calculation device. The calculation device is a machine-taught artificial intelligence device. The shape data record identifies locations at or on the physical shape. For a plurality of these locations, the sensitivity landscape respectively indicates how the target property of the physical shape changes if the physical shape changes in the region of the location. Furthermore, the shape data record for the physical shape to be determined is changed on the basis of the sensitivity landscape in such a manner that the predefined physical target property is improved.

Method and apparatus for determining a physical shape, method for manufacturing a calculation device, calculation device, and use of the calculation device

Provided is a method for the computerized control of an end element of a machine tool. The method includes a method step of sensing a plurality of optical markers in a work environment of the machine tool by means of an optical measuring system. The method includes a method step of determining a first relative pose between the end element and a workpiece on the basis of the plurality of sensed optical markers. The method includes a method step of determining a first correction value on the basis of a comparison of the first relative pose with a reference pose. The method includes a method step of controlling the end element for machining the workpiece taking the first correction value into consideration.

Method for controlling an end element of a machine tool, and a machine tool

A method using machine learned, scenario based control heuristics including: providing a simulation model for predicting a system state vector of the dynamical system in time based on a current scenario parameter vector and a control vector; using a Model Predictive Control, MPC, algorithm to provide the control vector during a simulation of the dynamical system using the simulation model for different scenario parameter vectors and initial system state vectors; calculating a scenario parameter vector and initial system state vector a resulting optimal control value by the MPC algorithm; generating machine learned control heuristics approximating the relationship between the corresponding scenario parameter vector and the initial system state vector for the resulting optimal control value using a machine learning algorithm; and using the generated machine learned control heuristics to control the complex dynamical system modelled by the simulation model.

Method and system for providing an optimized control of a complex dynamical system

A method () for optimizing a production process for a component () that is to be manufactured by additive manufacturing by means of simulation () of the production process () includes: a) ascertaining a position of the component () in a production space that has been optimized according to a process optimization criterion (); b) calculating displacements and/or stresses in the component () that can be caused by the production process (); c) ascertaining supporting structures () that counteract the displacements and/or stresses that have been optimized according to the process optimization criterion (); and d) ascertaining at least a portion of the design of the component () that has been optimized according to a component optimization criterion ().

Optimization of a production process

A system for controlling motions of a plurality of particles in a spatial area with at least one target and at least one obstacle, has a first detection device for detecting positions of the particles at a starting time; predicting a future path search of the particles occurs by way of a computer device, wherein the region has been superimposed by a cell grid and each cell takes on various occupation and total potential states, and each cell is associated with a target potential determining how particles are attracted to a target, and is associated with an obstacle potential determining how particles are repelled by an obstacle, and wherein each particle is associated with a particle potential, wherein a total potential in a cell is made up of the values of the target potential and the obstacle potential in the cell and the particle potentials of particles in cells adjacent to the cell, and particles each change from a cell into an adjacent cell having a least total potential, and additionally, starting from a target to each cell, the target potential for each cell is calculated using a length of the shortest distance from the cell to each cell center point. A central controller controls the motions of the particles in case of forecast critical situations.

Device and method for generating a targeted realistic motion of particles along shortest paths with respect to arbitrary distance weightings for simulations of flows of people and objects

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Aßling, Germany

Dirk Hartmann