Method and device for determining process parameters
Patent Information
- Application Number
- EP2023813573
- Authority / Receiving Office
- EP · EP
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2022-11-28
- Filing Date
- 2023-11-10
- Publication Date
- 2025-07-02
AI Technical Summary
Existing process devices in industrial manufacturing often use excessive amounts of process media, leading to economic inefficiencies, environmental pollution, and health risks, as the amount of media used is determined independently of component-specific parameters and primarily based on empirical values rather than actual process needs.
A computer-aided method that determines optimized process parameters by simulating the machining process, considering component-specific and machining parameters, to minimize media usage and environmental impact, involving steps like defining component and machining parameter sets, providing a simulation model, setting limit values, and iteratively selecting media parameter sets to adhere to these limits, resulting in an optimized media parameter set for efficient and sustainable processing.
This approach allows for a resource-saving and sustainable machining process by optimizing the amount and composition of process media, reducing waste and health risks, while ensuring process robustness and adherence to safety limits, thereby enhancing economic efficiency and environmental sustainability.
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Figure 1.1
Abstract
Description
[0001] Description
[0002] Method and device for determining process parameters
[0003] The present invention relates to a method for determining process parameters of a process device, wherein the process device is designed for an automated machining process on a component in which at least one process medium is used. Furthermore, the invention relates to a method for machining a component in such a process device, as well as a computer program product and a device for carrying out the method.
[0004] The applicant points out at this point that, regardless of the grammatical gender of a particular personal term, it should always include persons with male, female and other gender identities.
[0005] Many process devices known from the state of the art use process media, for example liquid or gaseous media, which are either used up during the process as part of a chemical reaction or support the process as auxiliary media. Such process media are used, for example, in industrial manufacturing processes for cooling, lubricating, inerting, cleaning or transporting, as process reagents and for possible combinations thereof. Processing and recycling these process media after their intended use is often not technically possible or at least not economical, so that they are subsequently disposed of as process waste. In addition, they are often used in excessive quantities and / or regardless of actual process requirements or process downtimes. Neither of these aspects is advantageous from a sustainability perspective.Known process devices in industrial manufacturing are typically controlled in such a way that the best possible process robustness is achieved under the given boundary conditions. The amount of a process medium used is usually set independently of the parameters of the individual component so that the process goal is reliably achieved and the other boundary conditions of the respective process step are reliably adhered to. For example, the amount of a (liquid or gaseous) coolant is selected so that overheating of the component to be processed is avoided with a high degree of certainty. Or the amount of a cleaning fluid is selected so that any contaminants that may be present are removed with a high degree of certainty. With this approach, the individual parameters of the component to be processed are often not taken into account.Rather, the amount of process medium used is determined primarily by the processing parameters set in the process device, with empirical values with the processing parameters being used to estimate the necessary dosage. This approach often leads to large amounts of process medium being used. The correspondingly high material consumption can have a negative impact on the economic efficiency of the processing process. Further disadvantages can also arise from the fact that the large amounts of medium can lead to correspondingly high environmental pollution (e.g. during production and / or disposal of the process medium) or to health risks for the personnel working with the process device.
[0006] The object of the invention is therefore to provide a method for adjusting process parameters in a process device that overcomes the aforementioned disadvantages. In particular, a method is to be provided that enables a comparatively resource-efficient use of the process medium. A further object is to provide a corresponding processing method, as well as a computer program product and a device designed to carry out the respective method.
[0007] These objects are achieved by the method for setting process parameters described in claim 1, the machining method described in claim 11, the machining method described in claim
[0008] 14 and the computer program product described in claim
[0009] The device described in 15 is released.
[0010] The method according to the invention is in particular a computer-aided method and serves to determine process parameters for a process device. This process device is designed for an automated machining process on a component, wherein at least one process medium is used in the process. The method comprises the following steps: a) defining a component parameter set for the component to be machined, b) defining a machining parameter set for the machining process to be carried out, c) providing a simulation model for the machining process, which describes one or more parameters of the machining process as a function of the component parameter set, the machining parameter set and a variable media parameter set for the process medium to be used, d) defining a limit value to be observed during the machining process for a selected parameter,e) Simulation of the machining process using the simulation model in several sub-steps e±), whereby different media parameter sets are selected for each of the individual sub-steps e±), whereby an overall optimized media parameter set is determined in which the limit value for the selected parameter is maintained, f) Setting the optimized media parameter set for the implementation of the automated machining process in the process device.
[0011] Steps a) to e) can be carried out in a simulation device which can either be part of the process device mentioned or can be outsourced from it. The order, in particular of steps a) to d), does not have to correspond to the specified order, but can in principle be arbitrary. However, step e) is expediently carried out after the four steps a) to d), since the fixed parameters and boundary conditions essential for the simulation are defined in steps a) to d).
[0012] In step a), the component-specific parameters are defined. In principle, the process device can be used to process different components which may differ, for example, in their geometric shape, size and / or material composition. In step b), the parameters of the processing process are defined, in particular the processing sequence and / or the parameters of a tool used in the process device. Different processing processes can be carried out in the process device which differ, for example, in terms of the tool used (e.g. milling, drilling, cutting, welding or cleaning tool), the result to be achieved (e.g. shape to be achieved, degree of removal, etc., which is set by a tool path) or other process parameters such as the process temperature.In other words, process parameters are defined here which are not primarily related to the process medium and which are therefore kept constant during the simulation cycle in step e). The process device can generally be an industrial production device. In step c), the simulation model to be used for the actual simulation is prepared, by which one or more parameters are predicted depending on the defined parameters.
[0013] In step d), at least one limit value to be observed for at least one selected parameter is defined as a boundary condition for the simulation. Advantageously, several limit values can also be defined here for several associated parameters, since typically a large number of predefined boundary conditions have to be observed during the process. The at least one parameter is in particular a parameter which is significantly influenced by the use of the process medium, so that the respective quantity of process medium to be selected depends crucially on the limit value defined here. For example, the selected parameter can be a measure of the stress on the component, for which a maximum value to be observed is expediently defined here. Alternatively, it can also be, for example, a measure of contamination of the component, for which a maximum value can also be specified.Such an impurity limit can, for example, be defined as an upper limit for a concentration, an amount of substance or a degree of coverage of an undesirable material component.
[0014] After the essential input data for the simulation have been provided in steps a) to d), the actual simulation is carried out in step e). This is carried out in several sub-steps e±), with different media parameter sets being selected in the individual sub-steps e±). At least one essential media parameter should therefore be varied from step to step, for example the amount of media used and / or the chemical composition of the process medium. In each sub-step, a calculated value is obtained for the selected parameter, and this calculated value is compared with at least one limit value to be observed. The sequence of the sub-steps can, in particular, be iterative. However, this is not absolutely necessary, and individual sub-steps can alternatively be carried out in parallel.Overall, a media parameter set is determined in each case which just meets the limit value for the selected parameter. In particular, a minimum required amount of media can be determined in this way for a given composition. Alternatively or additionally, the composition of the process medium can also be optimized with regard to a predefined optimization criterion (e.g. low process costs, lowest total amount required, good environmental compatibility and / or low health impact). Overall, in step e) an optimized media parameter set tailored to the component and processing parameters is determined by simulation. This set is then set as a process parameter for carrying out the processing in the subsequent step f).In particular, in this step f) the optimized media parameter set z can be passed on to a control device present within the process device and set there as a process parameter.
[0015] Overall, the method described achieves the result that, with the help of a computer-aided simulation prior to the actual machining process, an optimized set of media parameters is found which is optimized in particular for the lowest possible amount of media and / or low environmental pollution or low health risks. It is important that this optimization is component-specific, i.e. that the optimization depends not only on the other machining parameters, but also on the component parameters, for example on the size, shape and / or the material of the individual component to be machined. By taking this individual consideration of the component properties in the prior simulation, the process medium used can be optimized particularly precisely.Overall, this component-specific optimization enables a particularly resource-efficient and sustainable machining process to be implemented. The method according to the invention for machining a component in an automated processing device comprises the steps a) to f) already described and then the following step: g) machining the component using the optimized media parameter set.
[0016] The advantages are analogous to the parameter setting procedure described above, with the difference that the optimized media parameter set is not only determined and set for the process, but that the machining process is actually carried out with this parameter set.
[0017] The computer program product according to the invention comprises instructions, wherein the instructions, when the computer program product is executed on a computer, cause the computer to carry out the method according to the invention.
[0018] The device according to the invention comprises a simulation device and a process device. The process device is designed for an automated machining process on a component in which at least one process medium is used. The simulation device is designed to carry out the following steps: a) defining a component parameter set for the component to be machined, b) defining a machining parameter set for the machining process to be carried out, c) providing a simulation model for the machining process which describes one or more parameters as a function of the component parameter set, the machining parameter set and a variable media parameter set for the process medium to be used, d) defining a limit value to be observed during the machining process for a selected parameter,e) Simulation of the machining process using the simulation model in several sub-steps e±), whereby different media parameter sets are selected for each of the individual sub-steps e±), whereby an overall optimized media parameter set is determined in which the limit value for the selected parameter is maintained. The process device has a control device which is designed to carry out the following step: f) Setting the optimized media parameter set for carrying out the automated machining process in the process device.
[0019] The advantages of the computer program product according to the invention and the device according to the invention arise analogously to the advantages of the method according to the invention described above.
[0020] Advantageous embodiments and further developments of the invention emerge from the claims dependent on claims 1 and 11 and from the following description. The described embodiments of the method for parameter adjustment, the processing method, the computer program product, and the device can generally be advantageously combined with one another.
[0021] The process medium can generally advantageously be a coolant, a lubricant, an inerting agent, a process gas, a process liquid, a cleaning agent and / or a transport medium. What all these process media and auxiliary materials have in common is that, on the one hand, a certain minimum quantity of the process medium must be available so that the machining process runs robustly, but on the other hand, an excess of the process medium used should be avoided for reasons of cost-effectiveness and / or sustainability. For example, the process medium can be a process fluid, i.e. either liquid or gaseous. Such fluid media are used in many industrial manufacturing processes either as auxiliary materials or as reagents, and resource-saving use is generally desirable here.Alternatively, the process medium can also be a solid (e.g. a powder for abrasive blasting) or a suspension of a solid in a liquid or an aerosol. The only important thing is that the process medium fulfills a function that supports the machining process. In general, the medium can be used up either wholly or partially during the process (e.g. by chemically reacting) or it can remain unchanged afterwards. The medium remaining after the process can either be disposed of as a waste product or it can be fully or partially recovered. According to some specific embodiments, the process medium can, for example, be a cooling lubricant for a machining process in a machine tool, an inert gas in a welding process, or a cleaning fluid in a cleaning step.This cleaning step can optionally be carried out before or after another processing step within an overall machining process. Alternatively, it can be a reaction gas (e.g. for hardening a component), a process liquid or a process gas for applying a coating, a liquid or a gas for an etching process, or a starting material for plasma treatment of a component. Another example is a solid process medium for mechanical treatment, for example solid carbon dioxide for a CCh jet process or a powder for an abrasive powder jet process.
[0022] Generally speaking, the simulation model can advantageously be a multi-physical simulation model that takes phenomena from multiple physical domains into account. For example, in addition to effects of structural mechanics, thermal, fluid-dynamic, chemical, and / or electrical relationships can also be considered in the model. Such a multi-physical model ensures that the relationships between the mechanical processes of the machining process on the component and the fluid-dynamic, thermal, chemical, and / or electrical interactions between the process medium, the component, and the process device are adequately considered in the simulation.In other words, it is a coupled simulation model which describes at least the structural-mechanical domain and additionally at least one further physical aspect of the interaction of the process medium with the component and / or the processing device. The simulation in step e) is then based on the use of this model and is carried out in particular with computer support. Numerical methods for solving coupled systems of differential equations (with or without the additional use of algebraic equations) from these different physical domains can advantageously be used. These can be discretization methods, for example the finite element method, the finite difference method or the finite volume method, which can be particularly advantageous.
[0023] According to a first advantageous embodiment for step e), the optimized media parameter set determined here can have an optimized total media quantity as a parameter, wherein the optimized total media quantity is determined as the minimum media quantity at which the specified limit value for the selected parameter is maintained. This optimization of the total media quantity is achieved in particular by increasing or decreasing it in the individual sub-steps, wherein the chemical composition of the process medium is initially kept constant. In this way, a minimum required total media quantity is obtained for a predefined chemical composition, which is also included in the media parameter set. If the composition is also varied, an associated minimum total media quantity can be determined for each individual composition.In addition to the composition of the process medium, numerous other parameters also influence the optimum, e.g. the process temperature, which is particularly part of the processing parameter set defined in step a).
[0024] The simulation can advantageously be started with a sub-step eo ) in which the total media quantity is zero , so that the simulation is carried out with the specified component and process parameters in the absence of the process medium . In general, the specified limit value for the selected parameter is not adhered to here, since otherwise the process medium would not be needed at all . Starting from this simulation step eo ) , the total media quantity can then be increased incrementally until the limit value is met for the first time . With this method, the exact value of the optimum obtained depends on the selected step size in increasing the total media quantity .In order to refine the result, after determining a first (rough) optimization result, a further optimization can be carried out by reducing the step size in the vicinity of the first result and performing further incremental simulation steps there until a sufficiently accurate value for the optimal total media quantity has been determined.
[0025] In addition to the total media quantity, the media parameter set can advantageously also contain further parameters, which can optionally be optimized within step e) using the simulation. In particular, an optimized profile for a temporally variable media inflow can be determined. Alternatively or additionally, an optimized profile for a spatially variable media inflow into different areas of the device can be determined. The temperature of the process medium used, the service life of the process medium and / or the number of process cycles until the process medium is replaced can also be optimized here with the help of the simulation.According to a second advantageous embodiment for step e), the optimized media parameter set determined here can have an optimized media composition as a parameter, wherein the optimized media composition is composed from a selection of available material components in such a way that the machining process is optimized with regard to at least one predetermined criterion. Particularly advantageously, this optimization of the media composition can be combined with the previously described optimization of the total media quantity (and optionally additional parameters), so that overall an optimized media parameter set is determined in which both the quantity and the composition are optimized by the simulation.
[0026] The predetermined optimization criterion for optimizing the media composition can, for example, be the smallest possible amount of media required, the lowest possible price for the required amount of media, and / or the lowest possible environmental impact or health risk due to the required amount of media. Optionally, a multi-criteria optimization can also be performed based on several such criteria, where appropriate, a weighting of the relevant criteria is defined in a higher-level cost function.
[0027] According to a first embodiment variant for step d), the at least one limit value specified there can be a maximum value, wherein the selected parameter is a measure of a stress on the component. Alternatively or additionally, a maximum stress on the process tool, the process device and / or the process medium can also be specified here. In other words, the at least one limit value is then a maximum stress on the component, the tool and / or the process medium to be observed during the machining process. For example, the corresponding stress can be a temperature load during the process, a mechanical force effect, a chemical change and / or a concentration of an acting substance.Such stresses can be reduced by using suitable process media, so that by setting a limit value for the stress the position of the optimum determined in step e) is influenced. For example, more coolant is required if the limit value for the temperature stress is low, or more inert gas is required if the limit value for the permissible residual oxygen is low. In general terms, the limit value for the stress can be set in such a way that a sensible safety margin is maintained from a known (e.g. thermal, mechanical or chemical) damage threshold of the component (or of the tool and / or the process medium). By selecting this safety margin appropriately, damage can be reliably prevented on the one hand, and an excessive excess of the process medium used can be avoided on the other.
[0028] According to an alternative, second embodiment variant for step d), the at least one limit value specified there can also be a maximum value, wherein the selected parameter is a contamination of the component and / or a contamination of a process tool and / or a contamination of the process medium used. Such a parameter for the contamination can, for example, be specified as a concentration or amount of substance or degree of coverage of an undesirable substance or an undesirable substance class. In this way, the limit value specifies a maximum permissible upper limit for the residual value of a contamination which, for example, may remain with the process medium after a cleaning step. Here, too, the simulation can ensure that cleaning with the process medium as the cleaning agent reliably achieves the process goal without the need to use an excess of cleaning agent.Optionally, during the simulation in step e), the location of the cleaning agent's action can also be varied, so that the media parameters of the cleaning agent are optimized not only in terms of quantity, but also in terms of spatial distribution. In other words, no more cleaning agent is used than necessary, and it is only used in those locations where contamination is actually present. The component-specific information about the presence of contamination at specific locations is then part of the component parameter set defined in step a).
[0029] According to an advantageous embodiment for step a), the component parameter set defined here can contain both geometric parameters of the component and one or more material parameters of the component. For example, a boundary surface of the component can be defined in Cartesian or other coordinates, thereby defining the shape and size of the component. Several geometric data sets can also be defined here, for example one data set for the geometry before processing of the component and one data set for the geometry after processing, optionally with corresponding data sets for intermediate geometries during the process. In addition, for example, the material composition of the volume filled by the component can be defined, whereby this composition can be either constant or variable across the volume.Optionally, additional information about the surface properties such as roughness, wetting properties and / or reactivity can also be available as part of the material parameters. From the combination of the geometric parameters and the material parameters, a component-specific limit value for the selected parameter can then be defined, particularly in step d). In this way, the definition of a permissible maximum stress on the component can generally advantageously depend on the respective component parameters. If, according to this embodiment, the defined limit value is also dependent on the component parameter set, an even more precise component-specific optimization of the media parameters for the machining process can be carried out.
[0030] Generally advantageously, the set of machining parameters defined in step b) can include the selection of a tool in the process device, a feed rate of the component relative to such a tool, a pressure force of such a tool on the component, an orientation of the tool with respect to the component, a tool path, a residence time of the component in the process device, an ambient temperature, a process temperature and / or a machining volume per time period. These are typical parameters of machining processes in industrial production plants which have a significant influence on the optimal composition and the required quantity of the process media typically used. The above-mentioned tool path can in particular be a complex tool path which is provided via an NC code (NC for “Numerical Control”) for what is known as Computer-Aided Manufacturing (CAM).Such a tool path can be programmed, for example, using G-code, i.e., in the standard machine language for programming CNC machines. The mechanical or thermal load capacity of the tool, as well as permissible contamination and / or material changes to the tool, can also be specified in this parameter set. However, the permissible limit values for the process are preferably defined within step d) as part of the limit values for the selected parameter(s).
[0031] According to a particularly preferred embodiment of the method, the entire step e) can be carried out multiple times, wherein in particular the component parameter set and / or the processing parameter set are varied from run to run. This creates an optimized parameter field overall which has a plurality of optimized media parameter sets for each different component parameter sets and / or processing parameter sets. In other words, the optimization of the media parameter set is not carried out just once, but multiple times for different components and / or different processing processes. In particular, this makes it possible to create a component-specific or process-specific parameter field in which the amount and / or composition of media to be used depends on the properties of the component to be processed and the selected processing process.Particularly advantageously, in this embodiment, the optimized parameter field in step f) can be used to set a media parameter set used in the automated machining process by means of an automatic control device. For example, such an optimized parameter field can be loaded into a programmable logic controller (PLC) of a CNC machine tool (CNC for "computerized numerical control"), thus providing a component-specific automatic process control system that sets a media parameter set optimized with the aid of the upstream simulation, depending on the component to be machined and the machining process to be performed.In particular, a new simulation does not have to be performed for each component and each machining process. Instead, the parameter field can be created once using a preceding simulation sequence, and the most favorable media parameters can then be derived from the generally optimized parameter field using the control system. Alternatively, it is of course also possible to perform a separate simulation for each component and each machining process in order to obtain an even more precisely optimized set of media parameters.
[0032] According to a particularly advantageous embodiment of the processing method, this can additionally comprise the following steps: h) measuring the selected parameter by means of a sensor within the process device and i) controlling the media parameter set used as a function of the measured value obtained in step h) by means of a control device within the process device.
[0033] The measurement of the selected parameter in step h) can be carried out either directly or indirectly, whereby an indirect measurement is understood to mean the measurement of a physical parameter that is related to the selected parameter. For example, the sensor can be a thermal imaging camera with which a thermal load on the component is measured. Or the sensor can be a force sensor with which a mechanical load is measured. Or the sensor can be an optical camera with which a deformation is measured or a contamination is detected. Or it can be a gas sensor with which a remaining amount of oxygen is measured. In a generally advantageous manner, the sensor can be designed to detect a load state and / or contamination on the component.
[0034] In general, and regardless of the precise design of the sensor and the measured parameter, the measured value obtained in step i) is used to control the media parameter set used in the machining process. In particular, the media parameter set set in step f) and optimized by simulation can be further refined by such control. If, for example, the measurement shows that component stress is well below the permissible load limit, the amount of media can be reduced to below the optimum obtained from the simulation. Conversely, if the measurement shows that a predefined safety margin from the damage limit is not maintained, the amount of media can be increased. In general, the media parameter set used in the process can be further refined by an in-situ measurement, starting from the calculated optimum.
[0035] Optionally , the method may comprise the following additional step : j ) feeding the measured value obtained back into the simulation model provided in step c ) and adapting the simulation model .
[0036] In particular, the simulation model can be further improved (adapted) in this way for a subsequent run of simulation step e). This allows even more optimized media parameter sets to be used for the machining process in subsequent runs through steps f) and g).
[0037] The device can also advantageously be designed such that it is adapted to carry out the optional steps h), i) and optionally j).
[0038] The invention is described below using some preferred embodiments with reference to the attached drawings, in which:
[0039] Figure 1 shows a schematic representation of a process device according to an embodiment of the invention and
[0040] Figures 2 to 4 show flow diagrams for various embodiments of the method.
[0041] In the figures, identical or functionally identical elements are provided with the same reference symbols.
[0042] Figure 1 shows a schematic representation of a processing device 10 according to a first exemplary embodiment of the invention. Shown is a CNC machine tool with a base plate 11 and a component 30 to be machined, which is fixed to the base plate 11 via a component holder 31. A machining tool 40 is attached to a tool arm 43 via a tool holder 42. This can be a milling tool, for example, so that the device 10 as a whole represents a CNC milling machine. Optionally, an automatic tool change can also be carried out using a changing device (not shown here), so that different machining tools can be used. The process parameters of the device 10 are set automatically by an automatic control device 60, which can optionally also act as a regulating device.This can, for example, be a programmable logic controller (PLC) for a CNC machine. Alternatively, the control and regulation device 60 can be implemented as an edge device.
[0043] During the machining of the component 30, a process medium 50 is fed into the process via a media feed 51. In this example, it is a liquid coolant / lubricant, as is frequently used in CNC machine tools. The use of such a coolant / lubricant supports the milling process, whereby on the one hand friction is reduced and on the other hand excessive thermal loads on the component 30 and the tool 40 are prevented due to the cooling. However, the use of such a coolant / lubricant leads to environmental pollution due to harmful material components and also to a potential health hazard for personnel who come into contact with the device.In order to reduce these negative consequences, the embodiment of the device according to the invention uses a simulation device 70 upstream of the control device 60, with which an optimized media parameter set can be determined, which is then used by the control device 60. The upstream simulation device 70 can, as indicated here, be integrated into the device 10. Alternatively, however, it can also be present as a separate device, for example on an external computer, which then makes the optimized parameters available to the control device 60 via an interface, advantageously via a wireless communication interface. The sequence of the method for determining parameters within the simulation device is described in more detail in connection with Figures 2 to 4.
[0044] The machining process can be monitored using an optional sensor 80, which is only shown schematically here. In particular, this can be used to monitor a parameter for which a predetermined limit value must be adhered to during the process. For example, the temperature of the component 30 can be monitored during the machining process using a temperature sensor. The measured value obtained with the sensor 80 can, on the one hand, be used to readjust the media parameters determined with the simulation device via the control and regulation device 60, for example to increase the amount of media if the component 30 gets hotter during the process than predicted by the simulation. On the other hand, the measured value obtained with the sensor 80 can also be used to adapt the simulation model used by the simulation device 70 if the measured value deviates from the predicted value.
[0045] Figure 2 shows a flowchart for a first exemplary embodiment of the method according to the invention for determining process parameters for a process device. The process device can be, for example, the machine tool 10 shown in Figure 1. However, the basic method can also be applied to any other examples of process devices in which process media are used.
[0046] Thus, in step a), a component parameter set P3 is defined for the component 30 to be machined. This parameter set P3 can, for example, include geometric parameters of the component and material parameters of the component.
[0047] In a step b), a machining parameter set P4 is defined for the machining process to be carried out, which can include, for example, the properties of the selected tool 40, an ambient temperature, a tool path, a contact force and / or other tool- and process-specific parameters.
[0048] In a step c), a simulation model M is provided, which can in particular be a multi-physics model. In the concrete example in Figure 2, the model M comprises a model component for structural mechanics M_m as well as a thermal model component M_th, a fluid dynamic model component M_fl and a chemical model component M_ch. Optionally, an electrical and / or electrochemical model component (not shown here) can also be used. Not all of the model components shown here are necessary. However, it is advantageous if, in addition to the model component for structural mechanics M_m, at least one further model component is present in order to describe thermal, fluid dynamic, chemical and / or electrical interactions between the process medium 50 and the component 30 and / or the process tool 40.
[0049] In a step d), at least one limit value K_lim is defined for at least one selected parameter K. This can be, for example, a load limit of the component 30 and / or the machining tool 40 and / or the process medium 50. For example, the load limit can be a thermal load limit. However, it can also be a mechanical load limit, a maximum contamination, or a maximum chemical material change.
[0050] The order of these steps a) to d) can in principle be arbitrary. Following these four steps, step e) is expediently carried out, in which the machining process is simulated using the simulation model M and the parameter sets P3, P4. The simulation is carried out in several sub-steps e±), whereby these sub-steps e±) can run iteratively and / or in parallel to one another. Only as an example, an iterative sequence is shown here, in which a sub-step e±) is followed by a sub-step em). The dots indicate that further such sub-steps can run before and after. For each sub-step, different media parameter sets P5 are selected, so that, for example, P5i represents the media parameter set in step e±) and P5i. +irepresents the media parameter set in step ei+i). The individual media parameter sets can, for example, include a total media quantity and / or a media composition as individual parameters. Optionally, further parameters such as a temporally variable feed quantity or a spatially variable feed quantity of the process medium can also be included as parameters and varied accordingly from sub-step to sub-step.
[0051] In general, in each sub-step e± ) with the aid of the simulation model M a predicted value for at least one parameter K is determined for the respectively specified parameters P3, P4, P5 and compared with the specified limit value K_lim. In this way an optimized media parameter set P5_opt is determined at which the limit value K_lim for the selected parameter K is adhered to, in particular at which it is just adhered to. If compliance with the limit value K_lim is possible for several media parameter sets, then in particular the optimum is determined in such a way that a higher-level cost function is optimized. This can be a cost function, for example, which contains a criterion for the economic viability of the process and / or a criterion for the environmental impact of the process and / or a criterion for a health hazard caused by the process.
[0052] In the subsequent step f), the optimized media parameter set z P5_opt obtained with the simulation e) is set in the process device 10 for carrying out the machining process. In particular, the optimized media parameter set z P5_opt can be passed on to the control and regulating device 60 and set there for carrying out the machining process. In this way, it is achieved that the media parameters are adapted to the at least one predefined limit value K_lim and no excessive excess of media is used. In particular, the calculated optimum P5_opt depends on the specific component to be machined and on the specific machining process selected. This can lead to a considerable reduction in environmental pollution and health hazards. Figure 3 shows a flow diagram for a second exemplary embodiment of the method according to the invention.Steps a) to d) are designed similarly to those in Figure 2 and are therefore only roughly outlined. This is followed by a first run through a simulation step e), which is also designed similarly to Figure 2. In contrast to the first method example, here the processing parameter set is changed in a subsequent step v), and the corresponding changed processing parameter set P4' is used in a subsequent run through the simulation step e). This is repeated a number of times, resulting in an overall optimized parameter field P5_opt (P4), i.e. a plurality of optimized media parameter sets P5_opt as a function of the processing parameter set P4. This optimized parameter field is then likewise used in a subsequent step f) for the processing process.In particular, the entire parameter field P5_opt (P4) can be transferred to the control and regulation device 60. There, the parameter field can be used, for example, to determine and use the optimized media parameter set P5_opt depending on a user-defined machining process. Alternatively, the control device 50 can also automatically determine a higher-level optimum, in which both optimized media parameters P5_opt and optimized machining parameters P4_opt are output and preset for a process goal to be achieved.
[0053] Figure 3 shows how the optimized media parameter sets P5_opt can be determined in the form of a parameter field for various processing parameter sets P4. Alternatively or additionally, such optimized media parameter sets P5_opt can also be determined in an analogous manner for different component parameter sets P3, so that a multidimensional optimized parameter field is transferred from the simulation device 70 to the control device 60. Particularly advantageously, an automated NC code for the control device can be created on the basis of this parameter field.
[0054] The described creation of such a multidimensional parameter field can generally be performed in a separate simulation device located upstream of the actual process device (e.g., a CNC machine). Alternatively, it is also possible to integrate the simulation device into the process device, for example, within an edge device.
[0055] Figure 4 shows a flow diagram for a third exemplary embodiment of the method according to the invention. Steps a) to f) are designed similarly to those in Figure 2 and are therefore only roughly outlined. Step f) is followed by a step g), in which the machining of the component 30 is carried out within the process device 10. Optionally, during this machining step, in a parallel step h), a measurement of at least one parameter K can take place. This can be done, for example, via the sensor 80 (Figure 1), which enables a (direct or indirect) measurement of a load condition or a contamination. This can basically be a load condition and / or contamination of the component 30, the tool 40 or the process medium 50. In any case, this enables monitoring and control of the simulation result.Optionally, in a step i), depending on the measurement result, the optimized media parameter set P5 obtained from the simulation can be adjusted. This allows even further improved control of the media usage to be achieved. Alternatively or additionally, in a further optional step), the measurement result can be fed back into the simulation model M and the simulation model M can be adjusted accordingly. This ensures that an even better optimized media parameter set P5_opt is obtained during a subsequent run through simulation step e). List of reference symbols.
[0056] 10 Process device (machine tool)
[0057] 11 Base plate
[0058] 30 components
[0059] 31 Component holder
[0060] 40 machining tool (milling tool)
[0061] 42 tool holder
[0062] 43 Tool arm
[0063] 50 Process medium
[0064] 51 Media feed
[0065] 60 Control device (optionally also regulating device)
[0066] 70 simulation device
[0067] 80 Sensor a Setting of P3 b Setting of P4 c Providing of M d Setting of K_lim e Simulation ei Substep of the simulation em Following substep of the simulation f Setting of P5_opt g Processing of the component h Measuring of K i Control of P5 j Feeding back the measurement in M
[0068] K selected parameter
[0069] K_lim Limit value for selected parameter
[0070] P3 component parameter set
[0071] P4 Machining parameter set
[0072] P4 ' changed machining parameter set
[0073] P5 Media parameter set z
[0074] P5i Media parameter set in step ei
[0075] P5 i+iMedia parameter set z in step em P5_opt optimized media parameter set z
[0076] P5_opt ( P4 ) Parameter field P5_opt as a function of P4
[0077] M multiphysics simulation model
[0078] M_m model component for structural mechanics M_th thermal model component
[0079] M_fl fluid dynamic model component
[0080] M_ch chemical model component v variation of P4
Claims
Patent claims 1. A method for determining process parameters (P4, P5) of a process device (10), wherein the process device (10) is designed for an automated machining process on a component (30) in which at least one process medium (50) is used, wherein the method comprises the following steps: a) defining a component parameter set (P3) for the component (30) to be machined; b) defining a machining parameter set (P4) for the machining process to be carried out; c) providing a simulation model (M) for the machining process, which describes at least one characteristic variable (K) of the machining process as a function of the component parameter set (P3), the machining parameter set (P4), and a variable media parameter set (P5) for the process medium (50) to be used; d) defining a limit value (K_lim) to be observed during the machining process for a selected characteristic variable (K);e) Simulation of the machining process using the simulation model (M) in several sub-steps e±), wherein different media parameter sets (P5) are selected for each of the individual sub-steps e±), whereby an optimized media parameter set (P5_opt) is determined overall, in which the limit value (K_lim) for the selected parameter (K) is maintained, f) Setting the optimized media parameter set (P5_opt) for carrying out the automated machining process in the process device (10).
2. The method according to claim 1, wherein the process medium (50) is a coolant, a lubricant, an inerting agent, a process gas, a process liquid, a cleaning agent and / or a transport medium.
3. Method according to one of claims 1 or 2, wherein the simulation model (M) provided in step c) is a multi-physical simulation model which describes phenomena of structural mechanics and additionally thermal, fluid dynamic, chemical and / or electrical phenomena.
4. Method according to one of the preceding claims, in which the optimized media parameter set (P5_opt) determined in step e) has an optimized total media quantity as a parameter, the minimum media quantity being determined as the optimized total media quantity at which the specified limit value (K_lim) for the selected parameter (K) is maintained.
5. Method according to one of the preceding claims, in which the optimized media parameter set (P5_opt) determined in step e) has an optimized media composition as a parameter, wherein the optimized media composition is composed of a selection of available material components in such a way that the machining process is optimized with regard to at least one predetermined criterion.
6. The method according to one of claims 1 to 5, wherein the limit value (K_lim) defined in step d) is a maximum value, wherein the selected parameter (K) is a measure of a stress on the component (30) or a tool (40) of the process device or the process medium (50), in particular a temperature load, a mechanical force effect, a chemical change and / or a concentration of an acting substance. 7 . Method according to one of claims 1 to 5 , in which the limit value (K_lim) determined in step d) is a maximum value, wherein the selected parameter is a contamination of the component (30) or a contamination of a process tool (40) of the process device or a contamination of the process medium used (50).
8. Method according to one of the preceding claims, in which the component parameter set (P3) determined in step a) contains both geometric parameters of the component (30) and Contains material parameters of the component (30).
9. Method according to one of the preceding claims, in which the processing parameter set (P4) comprises the selection of a tool (40) in the process device, a feed rate of the component (30) relative to a tool (40), a pressing force of a tool (40) on the component (30), an orientation of the tool (40) with respect to the component (30), a tool path, a residence time of the component (30) in the process device, an ambient temperature, a process temperature and / or a processing volume per time.
10. The method according to one of the preceding claims, in which step e) is carried out several times, the component parameter set (P3) and / or the processing parameter set (P4) being varied from run to run, so that overall an optimized parameter field (P5_opt(P4)) is created which has a plurality of optimized media parameter sets (P5_opt) for respectively different component parameter sets (P3) and / or processing parameter sets (P4), the optimized parameter field (P5_opt(P4)) being stored in an automatic control device (60) in step f) and being used there to set a media parameter set (P5_opt) for the automated processing process.
11. A method for processing a component (30) in an automated process device (10), in which the setting of the process parameters (P4, P5) is carried out using a method according to one of claims 1 to 10 and then the following step takes place: g) processing the component (30) using the optimized media parameter set (P5_opt).
12. The method according to claim 11, which additionally comprises the following steps: h) direct or indirect measurement of the selected parameter (K) by means of a sensor (80) within the process device (10) and i) control of the media parameter set used (P5) as a function of the measured value obtained in step h) by means of a control device (60) within the process device (10).
13. Method according to one of claims 11 or 12, which additionally comprises the following step: j) feeding the obtained measured value back into the simulation model (M) provided in step c) and adapting the simulation model (M).
14. A computer program product comprising instructions, wherein the instructions, when the computer program product is executed on a computer, cause the computer to carry out the method according to one of the preceding claims 1 to 13.
15. Device comprising a simulation device (70) and a process device (10), wherein the process device (10) is designed for an automated machining process on a component (30) in which at least one process medium (50) is used, wherein the simulation device (70) is designed to carry out the following steps: a) Specifying a component parameter set for the component to be machined, b) Specifying a machining parameter set (P3) for the machining process to be carried out, c) Providing a simulation model (M) for the machining process, which describes at least one parameter (K) as a function of the component parameter set (P3), the machining parameter set (P4) and a variable media parameter set (P5) for the process medium (50) to be used, d) Specifying a limit value (K_lim) to be observed during the machining process for a selected parameter (K), e) Simulating the machining process using the simulation model (M) in several sub-steps e±), wherein different media parameter sets (P5) are selected for each of the individual sub-steps e±), whereby an overall optimized media parameter set (P5_opt) is determined, in which the limit value (K_lim) for the selected parameter (K) is observed,and wherein the process device (10) has a control device (60) which is designed to carry out the following step: f) setting the optimized media parameter set (P5_opt) for carrying out the automated processing process in the process device (10).,