The present invention relates to a computer-implemented method and a planer for calculating at least one supplementary processing plan for a workpiece to be processed by a processing machine. The method comprises the steps of: Measuring workpiece properties, including a thickness parameter of the workpiece; Providing at least one supplementary processing plan, which is specific for the measured workpiece properties. Due to the present invention, measurement of the workpiece properties is performed before starting to process the workpiece. Therefore, time and material can be saved, and scrap and waste are reduced.

Systems and methods are described for managing articles. The systems and methods described herein may comprise an example method for manufacturing an article. The systems and methods provides an end-to-end manufacturing value chain as a closed system and feedback loop.

Techniques for adjusting the shape of an ion beam are described. Characteristics of a desired beam shape may be defined. The ion beam generator may include beam shaping elements associated with tunable parameters that can be set in combination with each other. A search space for the possible combinations is defined. A set of exploratory points in the search space are measured and used to interpolate a large number of interpolated points based on a regression model. Interpolated points that are associated with low confidence values may be measured. Based on the measured and interpolated points, clusters of tunable parameter combinations may be identified for evaluation. The clusters are evaluated for stability and sensitivity, and one of the clusters is selected based on the evaluation. The ion beam generator may be configured based on the selected cluster.

An interpolation parameter calculation unit calculates an interpolation parameter of a predetermined interpolation calculation formula based on a first plurality of coordinate values input by means of a coordinate input unit and constituting a coordinate pattern for determining a locus pattern of one cycle when a laser beam is vibrated. A locus pattern calculation unit calculates a second plurality of coordinate values constituting the locus pattern based on an interpolation parameter, respective amplitudes of the locus pattern in an x-axis direction that is a moving direction of a processing head and a y-axis direction that is a direction orthogonal to the x-axis direction, a frequency of the locus pattern, and a control cycle of a beam vibration mechanism for vibrating the laser beam.

A three-dimensional laser machine includes a machine head, a controller for positioning the machine head and controlling an orientation of a nozzle, and a sensor for detecting a distance between a workpiece and the nozzle. The controller is capable of performing a profile control of correcting the position of the machine head based on the detected distance. When the machine head has reached a predetermined position part way through an approach process of moving the machine head from an approach start position to a machining start position while controlling the pose of the nozzle, the controller performs the profile control to move the machine head to the machining start position.

A machine learning apparatus able to obtaining an optimal shift amount of an assist gas. The machine learning apparatus comprises a state-observation section configured to observe machining condition data included in a machining program given to the laser machine, and measurement data of a dimension of dross generated at a cutting spot of the workpiece when the machining program is executed, as a state variable representing a current state of an environment in which the workpiece is cut; and a learning section configured to learn the shift amount in association with cutting quality of the workpiece, using the state variable.

A laser cutting device includes a control unit configured to control operations of a laser machining robot and a laser oscillator. Machining condition tables are stored in memory of the control unit. Each of the machining condition tables includes data of a laser power output and a duty, a usable range of a cutting speed of cutting a workpiece, the usable range being set based on a speed range in which a laser cutting robot can move with given tracking accuracy, and an effective range of the cutting speed and the laser power output that are set so that a cut surface of the workpiece meets given finishing conditions. The control unit is configured to select one of the machining condition tables so that the cutting speed and the laser power output meet given conditions, and control cutting of the workpiece based on the selected machining condition table.

A method for recognizing cutting parameters which are particularly important for specific features of a cut edge. A recording of the cut edge is analyzed by an algorithm having a neural network for determining the cutting parameters. Those recording pixels which play a significant part for ascertaining the cutting parameters are identified by backpropagation of this analysis. An output in the form of a representation of these significant recording pixels, in particular in the form of a heat map, demonstrates to a user of the method which cutting parameters need to be changed in order to improve the cut edge. A computer program product and a device for carrying out the method.

A method and a system for monitoring a laser machining process includes the steps of: inputting at least one process signal data set of the laser machining process into an autoencoder formed by a deep neural network; generating a reconstructed process signal data set by means of the autoencoder; determining a reconstruction error based on the at least one process signal data set and the at least one reconstructed process signal data set; and detecting an anomaly of the laser machining process based on the determined reconstruction error. A laser machining method includes the method and a laser machining system includes the system.

Provided is a control device for a laser machining apparatus which can maintain the inclination direction of a nozzle with respect to a machining program route even during modification of the tool diameter correction amount, and which can improve machining accuracy. This control device 1 for a laser machining apparatus comprises: a tool center route calculation unit 12which calculates a tool center route on the basis of an offset vector with respect to a machining program route; a first inclination direction calculation unit 131 which calculates an inclination direction of a nozzle 2 with respect to the machining program route; a tool orientation calculation unit 14 which calculates an orientation of the nozzle 2 on the basis of the inclination direction of the nozzle 2 calculated by the first inclination direction calculation unit 131 and an inclination angle of the nozzle 2 in the inclination direction from a direction that is perpendicular to a plane of a workpiece W in a plane orthogonal to the machining program route; a drive shaft movement amount calculation unit 15 which calculates a movement amount of a drive shaft on the basis of the tool center route and the orientation of the nozzle 2; and a drive shaft control unit 16 which controls the drive shaft on the basis of the movement amount of the drive shaft.