Method and system for machining a workpiece

Abstract

A method of machining a workpiece is provided, the method comprising: machining the workpiece by pre-machining; generating a virtual workpiece model as a representative of the workpiece after and / or during pre-machining; and planning or adapting post-machining of the workpiece using the virtual workpiece model. We further describe a system configured to perform the method, comprising a data source, a data transmitter, and a data processing system.

Description

[Technical Field]

[0001] The present invention generally relates to a method of machining a workpiece and a system configured to perform the method of machining a workpiece, such that the workpiece is machined in several stages with an adaptive machining process. [Background technology]

[0002] Machining of a workpiece generally requires adaptive measures to take into account differences or deviations of the actual semi-finished product outline relative to the planned semi-finished product outline, whereby the semi-finished product may also require an initial product outline. Particularly in multi-stage machining, which may be implemented, for example, in tool making or in mass production of cast / forged / printed components, such deviations of the actual semi-finished product outline from the planned semi-finished product outline frequently occur. Since any subsequent processing steps may generally be based on the actual outline of the semi-finished product, such deviations may have adverse effects.

[0003] For example, it may be possible to measure a semi-finished product stage using a suitable, precise measuring device such as a coordinate measuring machine (CMM), but the measurement may need to be performed outside the machine tool, the entire machined surface may not be covered, and / or additional measuring time may be required. This may be inefficient and slow down the entire machining process, as at least some disassembly may be required, or indeed may even be impossible for freeform surfaces. Finally, safe offsets may be selected and corrective cuts may be made, resulting in an inefficient process for manufacturing the workpiece.

[0004] In some cases, advanced a priori simulations, which may take into account many relevant aspects of the process and the machine, may be used to avoid reworking any steps. However, such a priori simulations may not be applicable if the initial workpiece geometry is not known. Therefore, additional, comprehensive measurements of at least some parts may again be necessary to be able to provide corrective measures when deviations of the actual semi-finished product geometry from the planned semi-finished product geometry are detected.

[0005] In Chinese Patent Application Publication No. 102865847(A), numerical control machining is applied by using a spline curve compensation method to measure contour deviation based on path units. In German (European Patent Translation) No. 60222026(T2), a standardized product model exchange-numerical controller (STEP-NC) is used to overcome the shortcomings of traditional NC with a closed structure.

[0006] Further prior art can be found, for example, in German Patent No. 112015004939 (B4) generally relating to a method for optimizing machining productivity of a CNC machine, and in International Publication No. WO 2016 / 065492 (A1) generally relating to a computer-implemented method for part analysis of a workpiece machined by at least one CNC machine.

[0007] In view of the above, improvements in the machining of workpieces are needed. Summary of the Invention

[0008] The invention is set out in the independent claims. Preferred embodiments of the invention are outlined in the dependent claims.

[0009] According to aspects of the present disclosure, a method of machining a workpiece is provided, the method including: machining the workpiece by pre-machining; generating a virtual workpiece model as a representative / representation of the (actual) workpiece; and planning post-machining of the workpiece using the virtual workpiece model. In some examples, the virtual workpiece is generated during machining, for example, with a latency of 5 ms or 10 ms after pre-machining is completed, and / or the virtual workpiece may be generated one second or more, and / or one minute or more, and / or one hour or more, and / or one day or more (or longer) after pre-machining is completed.

[0010] By using a virtual workpiece model, which may be generated from internal machine data (which may be, but is not limited to, control data and / or machining data that control the machine tool, e.g., force and / or vibration and / or temperature data, as further outlined below), with machining planning for one or more post-machining steps, the machining process may be shortened and the quality of the workpiece produced may be improved. The workpiece model may incorporate real-world imperfections, allowing for more fully discovered path planning, and / or the workpiece model may allow for more fully connected multiple (e.g., two) machining steps.

[0011] In some or any one of the examples outlined throughout this disclosure, in particular, the virtual workpiece model may be generated from internal machine data, so that the virtual workpiece model may be specific to the machining of a particular workpiece.

[0012] In some examples, the virtual workpiece model may relate to the geometry of the workpiece. Additionally or alternatively, the virtual workpiece model may reference one or more other parameters of the workpiece and / or the process producing the workpiece, whereby the one or more other parameters may be location-resolved and / or time-resolved. In some examples, the one or more parameters may be or relate to forces (e.g., forces generated on the machine tool during the machining process upon engagement of the cutting tool), accelerations (e.g., of the machine tool at the tool center point), temperatures (e.g., of the machine tool components and / or of the workpiece during the machining process), vibrations (e.g., of the machine tool components and / or of the workpiece during the machining process), and other parameters related to the machining process, such as bending of the machined workpiece and / or mathematical calculations for the machine tool drilling / cutting through the machined workpiece.

[0013] In view of the above, in some examples, a virtual workpiece may be defined as a contour that describes a virtual representation of the workpiece shape in a workpiece coordinate system (including, in some examples, one or more geometric errors for different orders of surface description and / or higher order surfaces) at any time during the manufacturing process. Alternatively, or in addition, in some examples, the definition of a virtual workpiece may include a broader definition that relates to comprising one or more of metadata, (optional) sensor data, one or more processing parameters, and measurement sensor data on the part surface at any time during the manufacturing process.

[0014] The virtual workpiece may be based on a trace used in the machining process, whereby the trace may be or comprise a list with several numerical control (NC) and / or programmable logic controller (PLC) and / or sensor data (topics) in the time domain with synchronized timestamps.

[0015] In any one or more (or all) of the examples outlined throughout this disclosure, post-processing may be defined as a second (e.g., intermediate and / or final) process that occurs after pre-processing, and thus pre-processing may be defined as a first (e.g., initial) process that occurs before post-processing. Thus, generally, pre-processing may be a first process, and post-processing may be a second process, with the first process occurring before the second process.

[0016] In some example methods, pre-machining and / or post-machining is performed using one or more numerical control (NC) code blocks.

[0017] In some examples of the method, at least one of pre-machining and post-machining is planned via computer-based path planning. Thus, in some examples, the computer-based path planning may relate to path planning for a machine tool. The path planning may be taken into account in machining planning for post-machining. Path planning may be performed for one or both of pre-machining and post-machining. In some examples, the path planning may be performed via a computer-aided manufacturing (CAM) algorithm.

[0018] In some example methods, at least one machine tool is used to perform pre-machining and post-machining, and the number of at least one machine tool is less than or equal to the number of machining steps used to machine the workpiece using pre-machining and post-machining.

[0019] In some example methods, (actual) data from the machine tool controller and / or (actual) data from embedded sensors in the machine tool are used to generate the virtual workpiece model. In some examples, the (actual) data may relate to internal machine data as outlined throughout this disclosure.

[0020] In some example methods, the virtual workpiece model is generated pseudo-parallel to pre-machining and / or after pre-machining. In some examples, pseudo-parallel means with a latency of less than 50 ms, preferably less than 10 ms. This may enable efficient production of the workpiece.

[0021] In some example methods, the virtual workpiece model is generated by considering one or more displacements of one or more physical components (of the workpiece) caused by the force loop. In some examples, the physical components may be cutting tools and / or clamping / fastening devices. Additionally or alternatively, in some examples, one or more machine and / or part stiffnesses and / or one or more correction tables may be taken into account when determining the one or more displacements. Additionally or alternatively, the workpiece itself may be deformed by the machining and / or clamping forces.

[0022] In some examples of the method, the virtual workpiece model is generated by taking into account a (virtual workpiece model) compensation algorithm executed in the machine or NC controller. In some examples, the compensation algorithm may relate to kinematic contour errors and / or thermal compensation that may be taken into account during generation of the virtual workpiece.

[0023] In some example methods, the virtual workpiece model is generated with a local geometric resolution that is smaller than the part's inherent local geometric dimension tolerance (GDT), which can result in a resolution that is smaller than features that can subsequently be measured on the virtual workpiece model.

[0024] In some example methods, after pre-machining, micron or sub-micron precision measurements, particularly performed by the use of coordinate measuring machines and / or machine-mounted tactile probing, and / or optical measurements, and the measurement point cloud are used to enhance and / or correct one or more (specific) areas of the virtual workpiece model. For calibration purposes, a complete model of the surfaces of the virtual workpiece model may be obtained.

[0025] In some example methods, calibration of the machining model as a function of one or more boundary conditions is performed in parallel to pre-machining. The machining model may comprise one or more of a force model, a tool material (model), and a workpiece model. The tool-material model may thereby relate to a cutting tool (e.g., geometry, material)-workpiece material model. The tool material model (cutting tool-workpiece material model) may be a model based on one or more parameters that solve a force equation (e.g., the Kienzle equation), which may depend on one or more parameters, for example, on one or more of the cutting tool geometry, tool wear, lubricant, tool material, and workpiece material (particularly related to local and / or global properties of the entire workpiece). Additionally or alternatively, the force equation may be influenced by one or both of thermal and melting conditions around each cutting edge and / or may be determined by a particular spindle speed, cutting tool-workpiece engagement, or feed rate. Additionally or alternatively, the one or more parameters may be or relate to the stiffness and / or deformability of the tool and / or workpiece, respectively.

[0026] In some examples, calibration of the processing model may include an initial generation of the processing model and / or a later adaptation of the processing model. In some examples, an initial model (e.g., a Kienzle model) may be later calibrated / adapted.

[0027] Throughout this disclosure, a tool-material model may be a cutting tool (e.g., geometry and / or material)-workpiece material model.

[0028] In some cases, the model may be an empirical model.

[0029] Based on the tool material model (cutting tool-workpiece material model), the cut can be calculated, whereby a physics simulation (cutting tool-workpiece engagement calculation driven by trace data) can be used to determine how much cutting force will be generated when machining the workpiece using a machine tool or spindle-mounted force sensor or table-based force measurement platform. Within the physics simulation, cutting conditions (e.g., ae (radial depth of cut), ap (axial depth of cut), volume) and / or force direction and / or force value are calculated. The engagement simulation can be based on, for example, Boolean, dexel, or voxel operations.

[0030] One or more tool material models (cutting tool-workpiece material models) may be stored in a database and may be available for one or more subsequent machining steps and / or subsequent parts to be manufactured.

[0031] In some cases, the calibrated machining model (tool material-workpiece material model) is used to plan post-machining.

[0032] In some example methods, calibration of the tool-material model (tool material-workpiece material model) is performed in parallel to post-machining, which may allow for later calibration of the model.

[0033] In some examples of the method, post-machining planning is performed using an initial workpiece outline based on the virtual workpiece model. In some examples, the virtual workpiece model can be used as the initial outline without using any additional workpiece outline information to define the initial workpiece outline. In some examples, data regarding the post-machining planning can be transmitted from (or acquired via) the machine tool performing the pre-machining. In some examples, post-machining planning is performed after pre-machining and generation of the virtual workpiece model.

[0034] In some example methods, one or more machining parameters (e.g., feed rates and rotational speeds, e.g., rather than just the path) are adjusted in a post-machining plan based on higher order shape deviations with respect to the virtual workpiece model, which may relate, for example, to one or more of higher order waviness, roughness, and other surface features.

[0035] In some example methods, one or more supplemental sensor signals, particularly acceleration data, are added to the virtual workpiece model in a location-related (geometric) manner. Additionally or alternatively, one or more signals from the machine tool controller and / or one or more external sensors (which may in some examples be uncritical to the machining process) may be added to the virtual workpiece model. The supplemental information may be used to adjust one or more machining parameters, such as, but not limited to, feedrates and / or rotational speeds (of the machine tool).

[0036] In some examples of the method, the post-machining planning is performed by simulating the ideal outline obtained in the pre-machining planning as the initial workpiece outline. Thus, in some examples, the planning can be a CAM plan in the first step based on the ideal final outline of the workpiece. In some examples, the method further includes a step of planning a path for the post-machining. The path planning for the post-machining can be performed before and / or during and / or after the pre-machining.

[0037] In some examples of the method, one or more initial calculated paths for post-machining are adjusted based on additional input generated from the virtual workpiece model. In some examples, the additional input may be deviation, and one or more other parameters (e.g., surface roughness and / or one or more higher-order parameters) may be used in addition to or instead of the deviation. Additionally or alternatively, in some examples, this adjustment may be based on an (internet) cloud service.

[0038] In some example methods, a posture-dependent offset table is generated using a virtual workpiece model, depending on one or more variables related to parameterized NC (numerical control) code and / or contour deviation and / or tool center point displacement. Additionally or alternatively, the offset table may be location-dependent. Offset tables throughout this disclosure may provide offset information related to one or more dimensions, particularly 3-axis or 5-axis machining. In a further example method, an initially generated NC code for post-machining is modified in a path adaptation engine using a virtual workpiece model. An interpretation of the initial NC code, called an NC parser, taking into account the specific machine tool dialect for post-machining before and after path modification may be included.

[0039] The one or more offset tables may be stored in a database (e.g., along with one or more tool material models (along with cutting tool-workpiece material models)) and may be available for subsequent parts to be manufactured.

[0040] The adaptation of the machine path need not be limited to the method of offset tables, and further methods of micron-based modification of the machining path are possible.

[0041] In some example methods, the path adjustment is performed by a machine tool controller (used to machine the workpiece) such that one or more final paths are generated at the NC device and / or machine tool. This adjustment may be performed (pseudo-)parallel to the machining process. The final paths may be generated at the NC or machine by either actual data adjustment or target data adjustment.

[0042] In some examples of the method, one or more target paths for post-processing are adjusted on-premise and / or in the (internet) cloud. In some examples, updates in the NC may not be provided.

[0043] In some example methods, the path adjustment is less than a predetermined threshold, the predetermined threshold being based on one or more machining parameters for machining the workpiece (during pre-machining and / or post-machining) and / or based on a tool geometry of a tool used to machine the workpiece (during pre-machining and / or post-machining). In some example methods, the path adjustment is a displacement of a single path that is less than the overlap of adjacent cutting contours. In some examples, additional (e.g., all) paths may be added.

[0044] In some example methods, the predetermined threshold is less than half the tool diameter of the tool, which allows for smaller divisions when adjusting one or more paths. Generally, the predetermined threshold may be determined based on the kinematic roughness expected to be present and / or measured when machining the workpiece.

[0045] In some example methods, one or more paths are adjusted by adding a single path segment.

[0046] In some examples of the method, post-machining planning includes determining a virtual tool (cutting tool)-workpiece engagement (e.g., in preparation for force determination) and calculating the tool center point displacement, whereby a measured virtual path can be used. In some examples, simulation can be performed using a conventionally (and initially) calculated path and / or an adapted path. In some examples, this simulation can be a virtual (e.g., iterative) machining optimization before the pre-machining step.

[0047] In some examples of the method, a tool-material model (tool material-workpiece material model) that is set and / or calibrated in pre-machining is used for planning.

[0048] In some example methods, a virtual NC controller, particularly including one or more offset tables, particularly NC internal corrections / compensations, is used to calculate a predicted actual path associated with an a priori simulation of a virtual workpiece model, which allows interpretation of the one or more offset tables, particularly including NC internal corrections / compensations, which may generally help to better predict results.

[0049] In some examples of the method, the target path (for the tool) is iteratively (in particular virtually) generated taking into account the displacement of the tool center point / tool ​​center point, which requires fewer actual steps in the method and thus further reduces costs when preparing the workpiece.

[0050] In any one of the examples outlined herein, the adaptation is not limited to open-loop control of the path. Closed-loop control of the path and machining parameters is also possible based on high-speed actual time data measurement, cutting tool-workpiece engagement calculation, force calculation, tool center point (TCP) deflection calculation, compensation definition, a priori TCP deflection simulation, and path adaptation in NC. In some examples of the method, the above steps occur in parallel to or after the machining sequence (part of machining or roughing / finishing), or always during each part of a single path.

[0051] In some example methods, post-machining is performed by an electrical discharge machine, whereby electrical discharge machining including a specific machining plan can be planned for post-machining. In some examples, knowledge of the actual electrode geometry for the electrical discharge machine as a virtual workpiece model can help optimize the accuracy of results obtained via the electrical discharge machine.

[0052] In some examples of the method, post-machining is performed by electrochemical machining. In some examples, knowledge of the actual cathode geometry for the electrochemical machine as a virtual workpiece model can help optimize the accuracy of the results obtained via the electrochemical machine.

[0053] In some examples, the method further includes a step of a micron / sub-micron precision part measurement process after pre-machining, and the corresponding measurement point cloud is used to correct the coordinate system of the virtual workpiece model relative to reference points, in particular relative to the zero point clamps of the electrode (EDM) and / or cathode (ECM).

[0054] According to another aspect of the present disclosure, there is provided a system configured to perform a method according to any one or more of the examples outlined throughout this disclosure, the system comprising a data source, a data transmitter, and a data processing system.

[0055] In some examples of systems, the data source is a machine tool with a data interface that transmits and / or reads machine internal data at a high sampling rate (above a threshold).

[0056] In some example systems, data is provided by the data interface at a frequency less than 2 kHz to provide PLC data, and / or at a frequency between 100 Hz and 20 kHz to provide servo data, and / or at a frequency between 2 kHz and 40 kHz to provide rotor shaft deformation.

[0057] In some examples of systems, the data includes one or more of the following: current supplied to a motor, signals from a rotary encoder and / or linear scale, spindle shaft displacement, one or more tool tables, one or more compensation tables, and one or more NC blocks. This data can be read from the machine.

[0058] In some example systems, the data is obtained from sensors measuring rotor shaft deformation in front of and / or between bearing pairs. Additionally or alternatively, the data may relate to one or more lathe and / or turning operations.

[0059] In some example systems, the data source is a machine internal job manager and / or a (eg, higher level) cell controller and / or a manufacturing execution system.

[0060] In some examples, the system is configured to provide job information and / or context information from one or more pre-processing steps and / or one or more corresponding images of the workpiece.

[0061] In some examples of the system, a data source, a data transmitter, and a data processing system for generating a virtual workpiece model, including a software unit for material removal simulation and a software unit for determining deformation, are provided with a software unit for computer-aided path planning (e.g., CAM), in particular a machine tool including an internally housed edge PC. Thus, the system can be provided within the machine tool or at (i.e., connected to) the machine tool. This can be particularly advantageous, as the incorporation of the system in the machine can enable real-time application of exemplary implementations of the methods outlined throughout this disclosure. The computation and implementation of the system in the machine further allows for the realization of an autonomous / self-sustaining system. [Brief explanation of the drawings]

[0062] These and other aspects of the present invention will now be further described, by way of example only, with reference to the accompanying drawings, in which like reference numerals refer to like parts and in which:

[0063] [Figure 1] FIG. 1 shows a schematic diagram of steps in a sequence according to some exemplary implementations of the present disclosure. [Figure 2] FIG. 2 shows a schematic diagram of steps in a sequence according to some example implementations of the present disclosure. [Figure 3] FIG. 3 shows a schematic diagram of steps in a sequence according to some exemplary implementations of the present disclosure. [Figure 4]FIG. 4 shows a schematic diagram of steps in a sequence according to some example implementations of the present disclosure. [Figure 5a] FIG. 5a shows a cross-sectional side view of a schematic representation of the cuts made when machining a workpiece. [Figure 5b] FIG. 5b shows a cross-sectional side view of a schematic representation of the cuts made when machining a workpiece. [Figure 5c] FIG. 5c shows a cross-sectional side view of a schematic representation of the cuts made when machining a workpiece. [Figure 6] FIG. 6 shows a schematic diagram of steps in a sequence according to some example implementations of the present disclosure. [Figure 7] FIG. 7 shows a schematic diagram of steps in a sequence according to some example implementations of the present disclosure. [Figure 8] FIG. 8 shows a schematic diagram of steps in a sequence according to some example implementations of the present disclosure. [Figure 9] FIG. 9 shows a schematic diagram of steps in a sequence according to some example implementations of the present disclosure. [Figure 10] FIG. 10 illustrates a schematic diagram of an improved virtual workpiece model coordinate system according to some example implementations of the present disclosure. [Figure 11] FIG. 11 illustrates a schematic diagram of a system setup according to some example implementations of the present disclosure. [Figure 12] FIG. 12 illustrates a flow diagram of a method according to some example implementations of the present disclosure. [Figure 13] FIG. 13 illustrates a schematic block diagram of a system according to some example implementations of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0064] According to exemplary implementations outlined throughout this disclosure, machining steps can be adapted to the planned geometry more quickly by using a virtual workpiece model generated from internal machine data of a previous machining step.

[0065] Thereby, the internal machine data may relate to, for example, positions traversed by a machine tool and / or forces that may act on one or more motors of the machine tool. Generally, internal machine data may refer to data that controls the machine tool. Thereby, in some examples, data obtained by subsequent measurements may not be taken into account for the internal machine data.

[0066] The internal machine data may relate to data resulting from the current machining process. In some examples, the internal machine data may relate to one or more of forces, accelerations, temperatures, vibrations, and other parameters related to the machining process, such as bending of the workpiece to be produced (e.g., at a resolution of less than 50 μm) and / or bending of the (cutting) machine tool, and / or mathematical calculations for the machine tool drilling / cutting through the workpiece to be produced. The data may be acquired during the (current) machining process. The data may originate from a controller that controls the machine tool and / or from sensors that may not be connected (at least directly) to the controller.

[0067] In some examples, the internal mechanical data may be mapped to a position resolution of 1 micrometer or less (e.g., 1 picometer). Additionally or alternatively, the internal mechanical data may be time-resolved.

[0068] For example, assuming that safety cuts or additional corrective cuts, including measurements using a CMM, can be eliminated according to the examples outlined throughout this disclosure, the cost of producing a workpiece can potentially be significantly reduced. Furthermore, improved quality of the produced workpiece can be achieved. In the case of variable and / or unknown blank geometries, knowledge of the actual geometry after initial machining steps, for example in the case of casting or additive manufacturing, can be obtained. Furthermore, better knowledge of the actual geometry at the semi-finished product stage can be obtained, thereby saving / removing safety cuts and achieving higher tolerances after post-machining (e.g., for DM).

[0069] FIG. 1 shows a schematic diagram of steps in a sequence 100 according to some example implementations of the present disclosure.

[0070] In some examples, the sequence 100 may be used for the continuous machining of cast, forged, or additively manufactured parts.

[0071] In sequence 100, one or more pose-related offset tables may be generated as input to a numerical control for any one or more or all of the steps for machining a workpiece.

[0072] In this example, the initial (ideal) contour is provided to the path generation kernel (computer-aided manufacturing (CAM)) and post-processor in step 101, whereby initial contour_2, ..., n corresponds to target contour_2-1, ..., n-1.

[0073] In this example, a path generation kernel (computer-aided manufacturing (CAM)) and post-processor are used in step 102 to output data / program NC_1 ("numerical control_1") that is used to control the machine tool used to manufacture the workpiece.

[0074] Thus, in some cases, a post-processor may process the path planning results after they are generated, which may include (1) adding one or more machining parameters and / or spindle stops / actuations, etc. to the path data (CAM may only calculate paths in a 3D environment), (2) describing the path as a vector list (e.g., move commands), and (3) generating NC code in the machine tool's specific dialect (e.g., M and G-codes vary for a particular machine tool / machine tool vendor / NC vendor).

[0075] In this example, data NC_1 is provided to a pre-machining 104, which may be a roughing operation in preparing the workpiece. In this example, in pre-machining, (computer) numerically controlled (NC) machining is used in the machining process where pre-programmed computer software may be used to control the movements of the machine tool.

[0076] In this example, in pre-machining 104, a raw part (with oversize and / or (potential) dimensional variations) is machined in the pre-machining.

[0077] In this example, the NC used in pre-machining outputs data NC trace_1 which may be or comprise a list with several numerical control (NC) and / or programmable logic controller (PLC) and / or sensor data (topics) in the time domain with synchronized timestamps.

[0078] Once the rough-machined part is prepared, adaptive machining correction (APC) based on a virtual workpiece model is performed in the edge NC system. In this example, in APC machining, a machine tool (cutting tool)-workpiece engagement simulation (CWES) with deformation calculation (and optional force calculation) is performed in step 106 based on measured machine trace data (in this example, based on NC trace_1). The virtual workpiece model (virtual workpiece model_1) generated from step 106 is provided to a calculation of local geometric deviations in step 108. Thus, in this example, data on the target outline (target outline_1) is provided to the calculation of local geometric deviations from the path generation kernel (computer-aided manufacturing (CAM)) and post-processor in step 108.

[0079] In this example, the local deviations calculated in step 108 are then provided to a pose-related offset table generator 110, which generates one or more offset tables that are used to provide to a numerical control (NC) for post-machining (in this example, semi-finishing) performed in step 112. In this example, numerical control data NC_2 is provided to the NC from a path generation kernel (computer-aided manufacturing (CAM)) and post-processor for post-machining (semi-finishing).

[0080] In this example, data NC trace_n-1 is output by the post-machining (semi-finishing) NC to a further adaptive machining correction (APC) 114 which may implement steps corresponding to those outlined in steps 106 to 112. In this example, data relating to the target outline of the workpiece for the nth machining step (target outline_n) provided by the path generation kernel (computer-aided manufacturing (CAM)) and post-processor is input at APC 114.

[0081] From APC 114, offset table_n-1 is provided to a numerical control (NC), where post-machining (in this example, the nth step, which is finish machining) is performed in step 116 to obtain a final machined workpiece from the semi-finished part. In this example, data NC_n is provided to the NC from a path generation kernel (computer-aided manufacturing (CAM)) and a post-processor for post-machining performed in step 116.

[0082] As can be seen, the generator of pose-related offset tables is used in the manufacturing sequence to generate adaptations based on the virtual contour and local deviations of the workpiece. The offset tables can be used as input in the execution of manufacturing of the workpiece based on a previous (ideal) plan.

[0083] In this example, all steps in the manufacturing process of the workpiece are planned from the beginning based on the ideal outer shape. In this example, n CAM steps are performed together in planning the manufacturing process of the workpiece.

[0084] The sequence shown in FIG. 1 may be particularly applicable to cast parts, which may relate to components / parts that can be produced relatively quickly / frequently (relatively cheap) compared to the other sequences outlined throughout this disclosure.

[0085] The one or more offset tables generated by the pose-related offset table generator are based on differences between the ideal workpiece and the virtual workpiece. Parameters of the ideal / virtual workpiece that may be taken into account in this comparison relate to one or more of the following: workpiece geometry, workpiece temperature, workpiece vibration, workpiece bending, and others. In some examples, the offsets provided in the offset tables may be location-resolved and / or time-resolved.

[0086] It should be noted that, throughout this disclosure, whenever reference is made to multiple offset tables, a single offset table may be used / generated in place of multiple offset tables in the described example implementations.

[0087] FIG. 2 shows a schematic diagram of steps in a sequence 200 according to some example implementations of the present disclosure.

[0088] Sequence 200 generally corresponds to sequence 100 as shown in FIG. 1 . However, in sequence 200, an apriori simulation in a virtual NC kernel is performed in step 211. For the apriori simulation, one or more model parameters (e.g., an empirical force model) are input from a machine tool (cutting tool)-workpiece engagement simulation. Furthermore, in this example, a generator of posture-related offset tables is configured to output offset table_1, which is used as input in the apriori simulation. Furthermore, in this example, data NC_2 is provided from the path generation kernel and the post-processor as input to the apriori simulation. Through the apriori simulation, offset table_1b is generated and provided as input to a numerical control in post-machining (semi-finishing) in step 112.

[0089] As can be appreciated, the a priori simulation is part of an adaptive machining modification based on a virtual workpiece model. The a priori simulation can reduce the difference between the nominal contour of the workpiece and the manufactured contour of the workpiece after machining the workpiece compared to machining implemented in the sequence of FIG.

[0090] 3 shows a schematic diagram of steps in a sequence 300 according to some example implementations of the present disclosure, in which one or more variables are generated for parametric NC code used in various steps of machining a workpiece.

[0091] Sequence 300 generally corresponds to sequence 100 as shown in FIG. 1 . However, in sequence 300, instead of a generator of a posture-related offset table, a variable generator is used to generate one or more variables_1, which are input to a numerical control for post-machining (semi-finishing), from local deviations obtained when calculating local geometric deviations (which are deviations between the virtual workpiece model and the ideal outline) in step 310. When generating the variables, parameter NC_2 data is input to the variable generator. Furthermore, data parameters NC_2 are also input to the numerical control for post-machining (semi-finishing). The data parameters NC_2 may include, for example, one or more variables that enable path correction for specific features of the workpiece. In this example, data is input to the variable generator 310, so that the variable generator 310 knows which parameter or parameters to optimize (i.e., based on which parameters to correct the path) to reach the target outline through post-machining. In some examples, one or more parameters may be found in a fitting algorithm.

[0092] The above is similarly applicable to the APC 114, where a variable _n-1 is generated from the APC 114 and input (together with the data parameter NC_n) to the numerical control for post-processing (the nth step for finishing the workpiece).

[0093] FIG. 4 shows a schematic diagram of steps in a sequence 400 according to some example implementations of the present disclosure.

[0094] Sequence 400 generally corresponds to sequences 100, 200, or 300. However, instead of the generator for pose-related offset tables / variables used in sequence 300, in sequence 400, a path adaptation kernel and post-processor are used in step 410 to generate NC code as input to the numerical control for post-machining (in this example, semi-finishing and the nth machining step that finishes the workpiece, respectively). It may be possible to input only Path_1 or NC_1. In some cases, for NC_1, an NC parser may need to be incorporated.

[0095] In any one or more of the exemplary implementations outlined throughout this disclosure, at the edge of the workpiece, no new movement may be calculated, and simply a correction / adaptation may be provided in the machining process.

[0096] Additionally, in pre-machining, it is possible to apply offset tables / variables already calculated for previous parts in the batch to minimize oversizing from the first run.

[0097] 5a to 5c show cross-sectional side views of a schematic diagram of cutting performed when machining a workpiece.

[0098] 5a-5c, a schematic diagram of a cutting tool 502 and a schematic diagram of a cutting tool 504 are shown that may be used to machine / cut a workpiece. Thereby, cutting tool 502 may be used for rough machining and / or cutting tool 504 may be used for semi-finishing and / or finishing. As will be appreciated, a single cutting tool may be used for different cutting operations in the examples of FIGS. 5a-5c.

[0099] In Fig. 5a, the study of the intermediate part outline (virtual workpiece model) after rough machining is not used when performing post-machining.

[0100] In this example, a workpiece raw part 505 is first cut via cutting tool 502. As can be seen, the manufactured contour 506 after rough machining deviates from the nominal contour 508 after rough machining, resulting in localized errors in pre-machining (indicated via the upward arrow in FIG. 5a).

[0101] After rough machining, the workpiece is cut via cutting tool 504. As can be seen, the finished manufacturing contour 510 deviates from the finished nominal contour 512 (which is the target part outline), resulting in localized errors in post-machining (indicated via downward arrows in FIG. 5a).

[0102] In Fig. 5b, the intermediate part outline (virtual workpiece model) after rough machining is taken into consideration when post-machining is performed.

[0103] In this example, a workpiece raw part 505 is first cut via cutting tool 502. As can be seen, the manufactured contour 506 after rough machining deviates from the nominal contour 508 after rough machining, resulting in localized errors in pre-machining (indicated via the upward arrow in FIG. 5b).

[0104] After rough machining, the workpiece is cut via cutting tool 504. As can be seen, the finished manufacturing contour 510 deviates from the finished nominal contour 512 (which is the target part outline), resulting in localized post-machining errors (indicated via downward arrows in FIG. 5b). However, the localized post-machining errors are smaller in the machining shown in FIG. 5b compared to the machining shown in FIG. 5a.

[0105] In Fig. 5c, the intermediate part outline (virtual workpiece model) after rough machining is considered when performing post-machining, whereby a priori simulation is used when planning post-machining.

[0106] In this example, a workpiece raw part 505 is first cut via cutting tool 502. As can be seen, the manufactured contour 506 after rough machining deviates from the nominal contour 508 after rough machining, resulting in localized errors in pre-machining (indicated via the upward arrow in FIG. 5c).

[0107] After rough machining, the workpiece is cut via cutting tool 504. As can be seen, the finished manufacturing contour 510 does not deviate (or deviates very little) from the finished nominal contour 512 (which is the target part outline), resulting in no (or minimal) local errors in post-machining. Therefore, the local errors in post-machining shown in Figure 5b (and Figure 5a) can be avoided in the machining shown in Figure 5c.

[0108] In some cases, a first cut machines a raw part of the workpiece. Based on an initially calculated path to achieve a nominal (ideal) outer shape, a specific contour ("is contour") is obtained. This specific contour varies due to physical effects not considered during the initial path planning. Initially, unknown oversizes exist in the machined workpiece, but the displacement of the tool center point is later determined based on machine-internal (actual) data, called a virtual workpiece model, with a predicted acquired contour. This allows for the determination of the deviation between the nominal contour and the predicted acquired contour, so that the oversize can be determined.

[0109] In other words, this deviation can be added to the machine tool (cutting tool)-workpiece engagement in post-machining. In the second cut, the oversize is known, allowing the tool center point displacement to be calculated to compensate so that the "is contour" matches the finished part. In some cases, a single iteration of applying the oversize information when planning / executing the second cut can be provided. However, any remaining oversize can still exist after the second cut.

[0110] 6 shows a schematic diagram of steps in a sequence 600 according to some example implementations of the present disclosure. Generally, machining data (particularly the virtual workpiece geometry) from a previous manufacturing step is used in the CAM planning for the actual manufacturing step.

[0111] In this example, initial (ideal) contour_1 and target contour_1 are input to a path generation kernel (CAM) and post-processor in step 601.

[0112] The virtual workpiece model obtained through the machine tool (cutting tool)-workpiece engagement simulation 106 is provided to a second path generation kernel (CAM) and post-processor 602. The cutting tool-workpiece engagement simulation, together with the path generation kernel (CAM) and post-processor 602, is used for machining data-based CAM planning (embedded CAM), which can be implemented n times up to (n-th) finish (post-) machining, including (n-th) finish (post-) machining.

[0113] FIG. 7 shows a schematic diagram of steps in a sequence 700 according to some example implementations of the present disclosure.

[0114] Sequence 700 generally corresponds to sequence 600 as shown in Fig. 6. However, in sequence 700, a priori simulation 702 in virtual NC is used in CAM planning based on machining data. Using a priori simulation, uncertainties in the characteristics of the machined workpiece, especially the contour, can be reduced (or even avoided). In some examples, a (new) parameterized physical machining simulation (capable of measuring, for example, machining forces and / or tool deflection) is used.

[0115] One or more model parameters (eg, empirical force models) may be provided to the a priori simulation in virtual NC 702 from a machine tool (cutting tool)-workpiece engagement simulation.

[0116] In this example, the a priori simulation exchanges data NC_2 with the path generation kernel (CAM) and post-processor 602. The downward arrow (arrow 701a) represents the NC_2 generated above (note that NC_2 changes (slightly) with each iteration of the a priori simulation / virtual optimization and may be called NC_2*). The upward arrow (arrow 701b) is the geometric offset information after virtual machining in post-machining that may be considered in the next path generation above. It may depend on the location / pose and may be relative or absolute. If the offset in virtual machining is within a predefined tolerance, it may send a command to use the upward NC_2*.

[0117] The data NC_2b is then output by the path generation kernel (CAM) and post-processor 602 as input for the numerical control 112 used in post-machining. The embedded CAM can be used n times until a finished workpiece is obtained.

[0118] 8 shows a schematic diagram of steps of a sequence 800 according to some example implementations of the present disclosure. In this example, the sequence 800 is applied to the machining of an electrical discharge machining (EDM) electrode.

[0119] In this example, initial (ideal) contour_1 and target contour_1 are input to a path generation kernel (CAM) and post processor 802. The path generation kernel (CAM) and post processor 802 outputs data / program NC_1 to a numerical control 804 that is used in pre-machining, which in this example is an electrode machining process. The raw part is machined in the pre-machining.

[0120] The data NC Trace_1 is output by the Numerical Control 804 and provided to a Machining Tool (Cutting Tool)-Workpiece Engagement Simulation (CWES) 806 with (optional force and) deformation calculations based on the measured machine trace data. NC Trace_1 can be or comprise a list with several Numerical Control (NC) and / or Programmable Logic Controller (PLC) and / or sensor data (topics) in the time domain with synchronized timestamps.

[0121] From the machining tool (cutting tool)-workpiece engagement simulation (CWES), a virtual workpiece model of the electrode is obtained and input (together with target outline_2) in the machining plan 810 for EDM.

[0122] The data NC_2 is output from the machining plan 810 EDM and input to the numerical control 812 when performing post-machining, which in this example is EDM machining on the electrode.

[0123] 9 shows a schematic diagram of steps in a sequence 900 according to some example implementations of the present disclosure. In this example, the virtual workpiece model may be refined based on one or more measurements made by (tactile on-machine) probing and / or by a coordinate measuring machine (CMM).

[0124] In this example, initial (ideal) contour_1 and target contour_1 are provided to the machining plan. Machining is then planned in step 902 (which may be identical to 802 in sequence 800). Data NC_1 is provided as input to a numerical control in step 904, which is used to control pre-machining. The raw part is machined in pre-machining.

[0125] NC Trace_1 is output by the numerical control and is used in step 906 as input in a machining tool (cutting tool)-workpiece engagement simulation (CWES) with (optional force and) deformation calculations based on the measured machine trace data. Based on the machining tool (cutting tool)-workpiece engagement simulation, a virtual workpiece model is generated and provided (together with target outline_2) to machining planning step 908.

[0126] Further, in this example, step 904 includes tactile probing at the machine that is used to generate a point measurement cloud that is provided along with the virtual workpiece model as input to the machining plan in step 908. Further, in this example, an external CMM 907 is provided to generate the point measurement cloud data that is input to the machining plan 908. As will be appreciated, in some examples, only machine tactile probing (without an external CMM) may be used, or only an external CMM (without tactile probing at the machine) may be used.

[0127] From the machining plan in step 908, data NC_2 is output and, in this example, provided to a numerical control 910 which performs post-machining of the rough machined part.

[0128] FIG. 10 illustrates a schematic diagram of an improved virtual workpiece model coordinate system according to some example implementations of the present disclosure.

[0129] The schematic diagram shows an actual workpiece 1002 and a virtual workpiece model 1004 (shown here based solely on a geometric representation of the virtual workpiece model). The zero point 1006 of the virtual workpiece model is shown at the center of the virtual workpiece model 1004. Additionally, the zero point 1008 of the zero point clamping (ZPC) system is depicted.

[0130] When a complete virtual process chain is used in parallel to a physical process chain, in the real world, the evolution of errors due to misalignment between the virtual and real worlds can be corrected. The effects of loose clamping devices can be compensated.

[0131] FIG. 11 illustrates a schematic diagram of a system configuration 1100 according to some example implementations of the present disclosure.

[0132] In this example, the system configuration 1100 comprises an edge PC 1102 that comprises a virtual work generator 1104 and a CAM 1106. Different options for the deployment of a path planning or adaptive engine are shown (1106, 1108, 1112).

[0133] The Edge PC 1102 is an additional computing unit inside the machine tool that enables power-intensive calculations without interfering with critical NC operations. It also enables pseudo-machining parallel calculations. It may host any one or more of the algorithms outlined throughout this disclosure. In this example, the Edge PC 1102 is securely connected to the cloud, where path planning and / or path adaptation are performed by the Path Planning and / or Adaptation Engine 1108.

[0134] Additionally, in this example, the edge PC 1102 is connected to a cell controller 1110, which is provided on-premise, i.e., where the machining tools are machining, providing work job specific metadata. Such metadata may be part ID and / or tool data and / or NC data and / or work material data. Additionally, in this example, the CAM 1112 is provided on-premise and connected to the edge PC 1102.

[0135] In this example, the Edge PC 1102 is further connected to a Computer Numerical Control (CNC) / Programmable Logic Controller (PLC) 1114. Reference 1116 represents the kinematics from the cutting tool to the workpiece where the force loop acts in the machining. Note that the force loop is not part of the machining tool. A spindle-integrated force sensor 1118 is provided to measure the forces acting in the machining.

[0136] FIG. 12 illustrates a flow diagram of a method 1200 according to some example implementations of the present disclosure.

[0137] In this example, a method 1200 for machining a workpiece includes, in step S1202, machining the workpiece by pre-machining.

[0138] In step S1204, a virtual workpiece model as a representative / representation of the (actual) workpiece is generated after and / or during pre-machining.

[0139] In step S1206, post-machining of the workpiece is planned using the virtual workpiece model.

[0140] The method 1200 for machining a workpiece may be implemented in any one or more of the exemplary implementations outlined throughout this disclosure, and in particular in any one or more of the sequences 100, 200, 300, 400, 600, 700, 800, and 900 outlined above.

[0141] FIG. 13 illustrates a schematic block diagram of a system 1300 according to some example implementations of the present disclosure.

[0142] In this example, system 1300 includes a data source 1302, a data transmitter 1304, and a data processing system 1306. System 1300 is configured to perform methods according to any one or more of the example implementations outlined throughout this disclosure, in particular, any one or more of sequences 100, 200, 300, 400, 600, 700, 800, and 900 outlined above and / or method 1300 outlined above.

[0143] In some examples, data source 1302 is a machine tool having a data interface that frequently transmits and / or reads internal machine data. The internal machine data may relate, for example, to the position of the machine tool as it passes through, the current, and / or the forces that may act on one or more motors of the machine tool. Generally, internal machine data may refer to data that controls the machine tool. In some examples, data obtained by subsequent measurements may not be taken into account for the internal machine data.

[0144] The internal machine data may relate to data resulting from the current machining process. In some examples, the internal machine data may relate to one or more of forces, accelerations, temperatures, vibrations, and other parameters related to the machining process, such as bending of the workpiece to be produced (e.g., at a resolution of less than 50 μm) and / or mathematical calculations for the machine tool drilling / cutting through the workpiece to be produced. The data may be acquired during the (current) machining process. The data may originate from a controller that controls the machine tool and / or from sensors that may not be connected (at least directly) to the controller.

[0145] In some examples, the data source 1302 (for generating the virtual workpiece model), the data transmitter 1304, and the data processing system 1306 comprise software units for computer-aided path planning, in particular a software unit for material removal simulation and a software unit for determining deformation, for which the machine tool is provided with an Edge PC housed therein. Any two or all of the above-mentioned software units may be integrated into a single software unit.

[0146] It should be noted that path planning as used throughout this disclosure may not be limited to being understood as being implemented solely via computer-aided manufacturing, and may include, for example, one or more offset tables relative to target location data and / or relative to actual location data.

[0147] Examples as outlined throughout this disclosure may be applied to die and mold technology, particularly in manufacturing and / or finishing cast and / or printed and / or forged products in serial production, for example, but not limited to, automotive, agricultural, medical, aerospace, semiconductor, and other areas. Examples as outlined throughout this disclosure may include all machining processes, such as, but not limited to, milling, turning, grinding, etc., in pre-machining and / or post-machining steps.

[0148] Additionally or alternatively, machine internal data as outlined throughout this disclosure may relate to or comprise one or more of tool deformation, workpiece deformation, static and / or dynamic loads on the machine, and compensation for machine and tool geometry related to volumetric and / or thermal effects.

[0149] In some exemplary implementations outlined throughout this disclosure, approaches for adapting path locations on a machine may be taken. All approaches may start after generating a virtual workpiece and analyzing the deviation from the target contour. Any variables for adaptation may be based on the deviation between the virtual workpiece and the target contour. Path adaptation based on edge kernels may allow for path adaptation under predefined boundary conditions (to reduce the risk of collisions or machine damage, etc.). This may not provide for fundamental changes in the number or orientation of paths.

[0150] The following examples are also encompassed by the present disclosure and may be incorporated into embodiments in whole or in part.

[0151] 1. A method for machining a workpiece, comprising: A step of machining the workpiece by pre-machining; generating a virtual workpiece model as a representation of the workpiece after and / or during the pre-machining; planning post-machining of the workpiece using the virtual workpiece model; A method comprising:

[0152] 2. The method of clause 1, wherein the pre-machining and / or post-machining is performed using one or more NC code blocks.

[0153] 3. The method of clause 1 or 2, wherein at least one of the pre-processing and post-processing is planned via computer-based path planning.

[0154] 4. The method of any one of clauses 1 to 3, wherein at least one machine tool is used to perform the pre-machining and the post-machining, and the number of the at least one machine tool is less than or equal to the number of machining steps used to machine the workpiece using the pre-machining and the post-machining.

[0155] 5. The method of claim 4, wherein data from a controller of the machine tool and / or data from an embedded sensor in the machine tool is used to generate the virtual workpiece model.

[0156] 6. The method of any one of clauses 1 to 5, wherein the virtual workpiece model is generated pseudo-parallel to and / or after the pre-machining.

[0157] 7. The method of clause 6, wherein pseudo-parallel means with a latency of less than 50 ms, preferably less than 10 ms.

[0158] 8. The method of any one of clauses 1 to 7, wherein the virtual workpiece model is generated by considering one or more displacements of one or more physical components, the one or more displacements being caused by one or more machining forces acting along a force loop.

[0159] 9. The method of any one of clauses 1 to 8, wherein the virtual workpiece model is generated by taking into account one or more compensation algorithms executed in a machine and / or NC controller.

[0160] 10. The method of any one of clauses 1 to 9, wherein the generation of the virtual workpiece model is performed with a local geometric resolution that is smaller than a part-specific local geometric dimension tolerance (GDT).

[0161] 11. The method according to any one of clauses 1 to 10, wherein after said pre-processing, micron / sub-micron precision measurements, in particular performed by coordinate measuring machines and / or machine-mounted tactile probing, and / or optical measurements and / or measurement point clouds are used to refine and / or correct one or more areas of said virtual workpiece model.

[0162] 12. The method of any one of clauses 1 to 11, wherein calibration of the machining model as a function of one or more boundary conditions is performed in parallel to the pre-machining.

[0163] 13. The method of claim 12, wherein the calibrated machining model is used to plan the post-machining.

[0164] 14. The method of any one of clauses 1 to 13, wherein calibration of the tool-material model is performed in parallel with the post-machining.

[0165] 15. The method of any one of clauses 1 to 14, wherein the planning of the post-processing is performed using an initial workpiece shape based on the virtual workpiece model.

[0166] 16. The method of any one of clauses 1 to 15, wherein the planning of the post-processing is performed after the pre-processing and the generation of the virtual workpiece model.

[0167] 17. The method of any one of clauses 1 to 16, wherein one or more machining parameters are adjusted based on higher order shape deviations with respect to the virtual workpiece model in the plan for the post-machining.

[0168] 18. The method of any one of clauses 1 to 17, wherein one or more supplementary sensor signals, in particular acceleration data, are added to the virtual workpiece model in a location-related manner.

[0169] 19. The method according to any one of clauses 1 to 18, wherein the planning of the post-processing is performed by using the ideal outline obtained in the planning of the pre-processing as the initial workpiece outline.

[0170] 20. The method of any one of clauses 1 to 19, further comprising planning one or more paths for said post-processing.

[0171] 21. The method of any one of clauses 1 to 20, wherein one or more initial calculated paths for the post-machining are adjusted based on additional input generated from the virtual workpiece model.

[0172] 22. The method of any one of clauses 1 to 21, wherein one or more variables for the parameterized NC code and / or a posture-dependent offset table according to the contour deviation and / or the tool center point displacement are generated using the virtual workpiece model.

[0173] 23. The method of clause 21, or clause 22 when dependent on clause 21, wherein the path adjustment is performed by a controller of the machine tool such that one or more final paths are generated in the NC device and / or machine tool.

[0174] 24. The method of clause 21, clause 22 when dependent on clause 21, or clause 23, wherein the one or more target paths for post-processing are coordinated on-premise and / or in the cloud.

[0175] 25. The method of clause 21, clause 22, clause 23, or clause 24 when dependent on clause 21, wherein the path adjustment is less than a predetermined threshold, and the predetermined threshold is based on one or more machining parameters for machining the workpiece and / or based on a tool geometry of a tool used to machine the workpiece.

[0176] 26. The method of clause 25, wherein the threshold value is less than half the tool diameter of the tool.

[0177] 27. The method of clause 21, clause 22 when dependent on clause 21, or any one of clauses 23 to 26, wherein the one or more paths are adjusted by adding a single path segment.

[0178] 28. The method of any one of clauses 1 to 27, wherein the planning of the post-machining includes determining a virtual tool-workpiece engagement and calculating a tool center point displacement.

[0179] 29. The method according to clause 28, wherein the tool-material model set and / or calibrated in the pre-machining is used in the planning.

[0180] 30. The method according to clause 28 or 29, wherein a virtual NC controller, particularly including one or more offset tables, in particular NC internal corrections / compensations, is used to calculate a predicted actual path associated with an a priori simulation of said virtual workpiece model.

[0181] 31. The method of any one of clauses 28 to 30, wherein the target path is iteratively generated taking into account the displacement of the tool center point.

[0182] 32. The method of any one of clauses 1 to 31, wherein the post-machining is performed by an electric discharge machine.

[0183] 33. The method of any one of clauses 1 to 32, wherein the post-processing is performed by an electrochemical processing machine.

[0184] 34. The method according to any one of clauses 1 to 33, further comprising a step of a micron / submicron precision part measurement process after said pre-machining, wherein the corresponding measurement point cloud is used to correct a virtual workpiece coordinate system relative to a reference point, in particular relative to the zero point clamp of the electrode (EDM) or cathode (ECM).

[0185] 35. A system configured to perform the method of any one of clauses 1 to 34, comprising: a data source; a data transmitter; and a data processing system.

[0186] 36. The system of clause 35, wherein the data source is a machine tool having a data interface for sending and reading machine internal data.

[0187] 37. The system of clause 36, wherein the data is provided by the data interface at a frequency of less than 2 kHz to provide PLC data, and / or at a frequency between 100 Hz and 20 kHz to provide servo data, and / or at a frequency between 2 kHz and 40 kHz to provide rotor shaft deformation.

[0188] 38. The system of clause 36 or 37, wherein the data includes one or more of the following: current supplied to a motor, one or more signals from a rotary and / or linear encoder, a tool center point displacement, one or more tool tables, one or more compensation tables, and / or an NC block.

[0189] 39. The system of any one of clauses 35 to 38, wherein the data is obtained from sensors measuring rotor shaft deformation in front of and / or between the bearing pair.

[0190] 40. The system of any one of clauses 35 to 39, wherein the data source is a machine internal job manager and / or a cell controller and / or a manufacturing execution system.

[0191] 41. The system of clause 40, wherein the system is configured to provide job information and / or context information from one or more pre-processing steps and / or one or more corresponding images of the workpiece.

[0192] 42. The system according to any one of clauses 35 to 41, wherein the data source, the data transmitter and the data processing system for the generation of the virtual workpiece model comprise a software unit for computer-aided path planning, in particular a software unit for material removal simulation and a software unit for determining deformation, provided with a machine tool including an edge PC housed therein.

[0193] Numerous other useful alternatives will no doubt occur to those skilled in the art, and it will be understood that the present invention is not limited to the described embodiments, but encompasses modifications that would be obvious to those skilled in the art and that lie within the scope of the claims appended hereto.

Claims

1. A method for machining a workpiece, comprising: A step of machining the workpiece by pre-machining; generating a virtual workpiece model as a representation of the workpiece after and / or during the pre-machining; planning post-machining of the workpiece using the virtual workpiece model; A method comprising:

2. The method of claim 1 , wherein the pre-machining and / or post-machining is performed using one or more NC code blocks.

3. The method of claim 1 , wherein at least one of the pre-machining and post-machining is planned via computer-based path planning.

4. 2. The method of claim 1, wherein at least one machine tool is used to perform the pre-machining and the post-machining, and the number of the at least one machine tool is equal to or less than the number of machining steps used to machine the workpiece using the pre-machining and the post-machining.

5. The method of claim 4 , wherein data from a controller of the machine tool and / or data from an embedded sensor in the machine tool is used to generate the virtual workpiece model.

6. The method of claim 1 , wherein the virtual workpiece model is generated pseudo-parallel to and / or after the pre-machining.

7. The method of claim 6, wherein pseudo-parallel means with a latency of less than 50 ms, preferably less than 10 ms.

8. 10. The method of claim 1, wherein the virtual workpiece model is generated by considering one or more displacements of one or more physical components, the one or more displacements resulting from one or more machining forces acting along force loops.

9. The method of claim 1 , wherein the virtual workpiece model is generated by considering one or more compensation algorithms implemented in a machine and / or an NC controller.

10. The method of claim 1 , wherein the generation of the virtual workpiece model is performed at a local geometric resolution that is smaller than a part-specific local geometric dimensional tolerance (GDT).

11. 2. The method according to claim 1, wherein after the pre-processing, micron / sub-micron precision measurements, in particular performed by coordinate measuring machines and / or machine-mounted tactile probing, and / or optical measurements, and / or measurement point clouds are used to refine and / or correct one or more areas of the virtual workpiece model.

12. The method of claim 1 , wherein calibration of a machining model as a function of one or more boundary conditions is performed in parallel to the pre-machining.

13. The method of claim 12 , wherein the calibrated machining model is used to plan the post-machining.

14. The method of claim 1 , wherein calibration of the tool-material model is performed in parallel to the post-machining.

15. The method of claim 1 , wherein the planning of the post-machining is performed using an initial workpiece geometry based on the virtual workpiece model.

16. The method of claim 15 , wherein the planning of the post-machining occurs after the pre-machining and the generation of the virtual workpiece model.

17. The method of claim 1 , wherein one or more machining parameters are adjusted based on higher order shape deviations for the virtual workpiece model in the plan for the post-machining.

18. The method of claim 1 , wherein one or more supplementary sensor signals, in particular acceleration data, are added to the virtual workpiece model in a location-related manner.

19. The method according to claim 1 , wherein the planning of the post-machining is performed by using an ideal outline obtained in the planning of the pre-machining as an initial workpiece outline.

20. The method of claim 19 further comprising planning one or more paths for the post-processing.

21. The method of claim 1 , wherein one or more initial calculated paths for post-machining are adjusted based on additional input generated from the virtual workpiece model.

22. 22. The method of claim 21, wherein one or more variables for a parameterized NC code and / or a pose-dependent offset table depending on contour deviation and / or tool center point displacement are generated using the virtual workpiece model.

23. 22. The method of claim 21, wherein the path adjustment is performed by a controller of the machine tool such that one or more final paths are generated in an NC device and / or machine tool.

24. The method of claim 21 , wherein the one or more target paths for post-processing are coordinated on-premise and / or in the cloud.

25. 22. The method of claim 21, wherein the path adjustment is less than a predetermined threshold, the predetermined threshold being based on one or more machining parameters for machining the workpiece and / or based on a tool geometry of a tool used to machine the workpiece.

26. 26. The method of claim 25, wherein the threshold is less than half a tool diameter of the tool.

27. The method of claim 21 , wherein the one or more paths are adjusted by adding a single path segment.

28. The method of claim 1 , wherein the planning of the post-machining includes determining a virtual tool-workpiece engagement and calculating a tool center point displacement.

29. The method according to claim 28, wherein a tool-material model set and / or calibrated in the pre-machining is used in the planning.

30. 29. The method of claim 28, wherein a virtual NC controller, particularly including one or more offset tables, particularly NC internal corrections / compensations, is used to calculate a predicted actual path associated with an a priori simulation of the virtual workpiece model.

31. 29. The method of claim 28, wherein a target path is iteratively generated to account for the displacement of the tool center point.

32. The method of claim 1 , wherein the post-machining is performed by an electric discharge machine.

33. The method according to claim 1 , wherein the post-processing is performed by an electrochemical machine.

34. 2. The method according to claim 1, further comprising a step of a micron / submicron precision part measurement process after the pre-machining, wherein the corresponding measurement point cloud is used to correct a virtual workpiece coordinate system relative to a reference point, in particular relative to a zero point clamp of an electrode (EDM) or a cathode (ECM).

35. A system configured to perform the method of claim 1, comprising: a data source; a data transmitter; and a data processing system.

36. 36. The system of claim 35, wherein the data source is a machine tool having a data interface for transmitting and reading machine internal data.

37. 37. The system of claim 36, wherein the data is provided by the data interface at a frequency of less than 2 kHz to provide PLC data, and / or at a frequency between 100 Hz and 20 kHz to provide servo data, and / or at a frequency between 2 kHz and 40 kHz to provide rotor shaft deformation.

38. 37. The system of claim 36, wherein the data includes one or more of the following: current supplied to a motor, one or more signals from rotary and / or linear encoders, tool center point displacement, one or more tool tables, one or more compensation tables, and / or NC blocks.

39. 36. The system of claim 35, wherein the data is obtained from sensors that measure rotor shaft deformation in front of and / or between the bearing pairs.

40. 36. The system of claim 35, wherein the data source is a machine internal job manager and / or a cell controller and / or a manufacturing execution system.

41. 41. The system of claim 40, wherein the system is configured to provide job information and / or context information from one or more pre-processing steps and / or one or more corresponding images of the workpiece.

42. The system of claim 35, wherein the data source, the data transmitter and the data processing system for the generation of the virtual workpiece model comprise a software unit for computer-aided path planning, in particular a software unit for material removal simulation and a software unit for determining deformation, provided with a machine tool including an edge PC housed therein.

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