Systems, devices, and methods including selecting one or more sequences of machining types for a feature of one or more features, where the selection of the one or more sequences of machining types is based on the feature and a database of prior selections of machining types; selecting one or more tools for the selected one or more sequences of machining types, where the selection of the one or more tools is based on the feature, the selected one or more sequences of machining types, and a database of prior selections of one or more tools; and selecting one or more machining parameters for the selected one or more tools, where the selected machining parameters are based on the feature, the selected one or more sequences of machining types, the selected one or more tools, and a database of prior selections of one or more machining parameters.

To optimize an automatically optimized machining time for machining a workpiece in a machine tool, an original parts program is loaded into a machine tool controller. The machining of the workpiece using the original parts program is simulated, where a motion path generated by the original parts program in the machine tool is determined. The motion path is classified into at least one area of potential optimization in which there is no workpiece contact. The at least one area of potential optimization is assigned a tolerance space. An optimized motion path is determined within the tolerance space. The machining of the workpiece using the modified parts program is simulated. The optimized motion path is displayed and marked. Once a user has approved the modification in the parts program, machining of the workpiece takes place using the modified parts program.

The present disclosure relates to a method of calculating process parameters. which are optimized for processing a workpiece with specific material properties by means of a laser machine, comprising the method steps of: determining material properties for which the process parameters should be optimized; determining preconfigured initial process parameters; executing a re-optimization algorithm until a target objective function is minimized or maximized for calculating optimized material-specific process parameters by accessing a storage with a statistical model, wherein the statistical model is based on Bayesian optimization using Gaussian Processes as priors.

The invention relates to a system for generating sets of control data for networked robots, comprising a plurality of robots (R.sub.i), wherein i=1, 2, 3, . . . , n, and n2, an optimizer (OE) and a database (DB), which are networked via a data network, wherein each robot (R.sub.i) includes at least: a control unit (SE.sub.i) for controlling and/or regulating the robot (R.sub.i); a storage unit (SPE.sub.i) for controlling sets of control data SD.sub.i(A.sub.k), which in each case enable the control of the robot (R.sub.i) in accordance with a predetermined task (A.sub.k), wherein k=1, 2, 3, . . . , m; a unit (EE.sub.i) for specifying a new task A.sub.m+1 for the robot (R.sub.i), wherein A.sub.m+1A.sub.k; a unit (EH.sub.i) for determining a set of control data SD.sub.i(A.sub.m+1) for execution of the task (A.sub.m+1) by the robot (R.sub.i), an evaluation unit (BE.sub.i), which evaluates the set of control data SD.sub.i(A.sub.m+1) determined by the unit (EH.sub.i), with regard to at least one parameter (P1) with the characteristic number K.sub.P1(SD.sub.i(A.sub.m+1)), and a communication unit (KE.sub.i) for communication with the optimizer (OE) and/or the database (DB) and/or other robots (R.sub.ji), the optimizer (OE), which is designed and configured in order to determine, upon request by a robot (R.sub.i), at least one optimized set of control data SD.sub.i,P2(A.sub.m+1) with regard to at least one predetermined parameter (P2), wherein the request by the robot (R.sub.i) occurs when the characteristic number K.sub.P1(SD.sub.i(A.sub.m+1)) does not meet a predetermined condition, and the data base (DB) stores the set of control data SD.sub.i,P2(A.sub.m+1) optimized by the optimizer (OE) and provides it to the robot (R.sub.i) for execution of the task (A.sub.m+1).

A machining-process generation device includes: a process-instance storage section to store therein a process instance that is an instance of a machining process indicating machining details of each machining-operation unit; a process generation section to generate a machining process on a basis of the process instance and a generation condition for the machining process, and to generate background information indicating a background to generation of the machining process, the background information including information of the process instance used to generate the machining process; and a display section capable of displaying the background information on a display device.

A machining status display apparatus includes an achievement degree data storage storing achievement degree data relating to a degree of achievement of each of predetermined machining-related evaluation items within a range determined by attainable maximum and minimum values of the evaluation item and storing the degrees of achievement of the evaluation items obtained under each of predetermined sets of machining conditions in association with the set of machining conditions, a display part displaying the degrees of achievement of the evaluation items corresponding to a selected set of machining conditions by referring to the data in the achievement degree data storage, and an input part inputting a selection signal for selecting a set of machining conditions. The display part displays the degrees of achievement of the evaluation items obtained under the set of machining conditions corresponding to the selection signal by referring to the data in the achievement degree data storage.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that can optimize a manufacturing plant's operations and/or production based on simulations that utilize information about the current and forthcoming manufacturing conditions to determine the optimal operational characteristics for the different plant devices. Methods may include obtaining, using data from a set of sensors, a set of current operational characteristics for multiple plant devices in a plant. Multiple manufacturing scenarios can be simulated using different sets of operational characteristics for plant devices in which at least one operational characteristic from the set of current operational characteristics is varied. A first manufacturing scenario can be determined that satisfies overall operational parameter(s) for one or more plant devices or for the whole manufacturing plant. Setting(s) of one or more plant devices can be adjusted based on a set of operational characteristics corresponding to the first manufacturing scenario.

The present invention relates to method for modifying process parameters based on optimum operation performance criteria for a metal working process, said method comprising the steps of inputting standard process parameters for at least one product to be machined and generating operational data based on the standard process parameters. Operational data is compared with optimized operation performance criteria and is presented to a decision-making entity. This entity may be allowed to modify the process parameters so as to improve operation of the metal working process.

A machining condition search device according to the disclosure includes a machining condition generation unit, a practical machining command unit, a machining evaluation unit, a prediction unit, an optimum machining condition calculation unit. The machining condition generation unit generates a machining condition defined by one or more control parameters settable on a machining apparatus. The practical machining command unit causes the machining apparatus to perform machining based on a generated machining condition. The machining evaluation unit generates an evaluation value of performed machining, on the basis of information indicating a machining result of the performed machining. The prediction unit predicts an evaluation value corresponding to a machining condition under which machining is not performed, on the basis of the evaluation value and the machining condition corresponding to the evaluation value. The optimum machining condition calculation unit obtains an optimum machining condition on the basis of a prediction value predicted by the prediction unit and an evaluation value generated by the machining evaluation unit. The optimum machining condition is a machining condition under which an evaluation value is equal to or greater than a threshold and a tolerance is maximum.

A method includes: selecting a movement path for a moving component of a machine tool; either before or after the movement path, causing the moving component to make a first predefined movement; before the movement path, causing the moving component to make a second predefined movement; after the movement path, causing the moving component to make a third predefined movement; recording, using a computing device including one or more accelerometers, movement data resulting from the first, second and third predefined movements, and from the movement path; analyzing the movement data by finding waveforms to identify a start point, a finish point, and which one of the predefined movement paths in the set was selected; calculating timing information based on the identified start and end points, and the identified one of the predefined movement paths in the set; and determining performance limits of the machine tool based on the timing information.