Method for setting up and operating machine for processing plastics and associated machine

Abstract

The invention relates to a method for setting up and operating a machine for processing plasticizable materials, comprising at least one electric motor for at least one machine shaft, the motor characteristic (K), in particular the torque-rotational speed characteristic M (n) of which is present as part of a machine-dependent mathematical model (190). In the method, a machine-independent process parameter curve of the ideal filling process is determined from a filling simulation (200) taking into account the field of the mould (10) and the material (Mat). In the process, in the simulation, machine-related setting parameters and machine-independent process parameters of a real filling process are determined by an iterative approach process based on the machine-independent process parameter curve of the ideal filling process and the machine-related mathematical model (190). During machine setup, machine-related setup parameters can be taught at least in part by an operator, and the machine, on the basis of the determined and optionally taught machine-specific setup parameters and the determined machine-independent process parameters, enables the setup parameters to be taught at least partially by the operator without requiring manual input of the parameters. The method is operated at an optimal operating point (WP) of the filling process, said optimal operating point being dependent on the process stage.

Description

[0001] Citation of relevant applications

[0002] This application relates to and claims priority to German patent application 10 2023 119 617.0, filed on July 25, 2023, the entire contents of which are hereby expressly incorporated into the subject matter of this application. Technical Field

[0003] This invention relates to a method for setting up and operating a machine for processing plastics and other plasticizable materials, such as an injection molding machine, particularly including the features of claim 1, or a machine for additive manufacturing. Furthermore, this invention relates to a machine for processing plastics and other plasticizable materials having the features of claim 13, the machine being set up, configured, and / or constructed to perform a method for setting up and operating a machine for processing plasticizable materials, and a computer program product according to claim 14, having program code stored on a computer-readable medium, including commands to cause the machine of claim 13 to perform the method steps according to claims 1 to 12.

[0004] As used herein, the term "plasticizable material" will be interpreted broadly and (in particular, but not limited to) includes not only plastics, silicones, or other thermoplastic and / or elastomer materials (e.g., ceramics, metals, and / or powdered substances), but also paper, cellulose, starch, cork, and the like, as well as mixtures containing such plasticizable materials. In principle, these materials can also be previously plasticized materials or plastic substances that harden spontaneously or with the aid of auxiliaries after application. The term also includes recycled materials.

[0005] As used herein, the term "domain" refers to a definable problem domain or specific application domain in a computer system or software, specifically in systems engineering and software engineering. A domain—or problem domain—typically imposes very specific requirements on a technical system for simulating or solving domain-specific tasks and problems. These requirements are incorporated into the development process, specifically during requirements analysis prior to system development and during system planning, and have a decisive influence on the formation or modeling of the models that form the basis for subsequent implementation. Background Technology

[0006] In the field of machinery used to process plastic materials (such as plastics and other malleable materials), processes are becoming increasingly complex due to variations in the materials being processed. At the same time, soaring energy prices are forcing machine operators to operate processes and, consequently, machines at optimal operating points based on process stages. This is typically the ideal balance between productivity, energy consumption, and output (number of good products). Operators are increasingly forced to operate machines in 24 / 7 shifts and are facing challenges in recruiting qualified personnel to operate and maintain them. This increases the demand for greater automation and further complicates machine operation.

[0007] DE 10 2017 131 032 A1 discloses a method for adjusting a molding machine, specifically an injection molding machine, comprising the following steps: a) Perform at least one filling simulation, using at least one process parameter describing the physical conditions of the molding process, specifically with respect to the mold and material, and at least one parameter as the basis for at least one of the machine-specific setting parameters of the molding machine, specifically for at least one drive for at least one machine axis, the drive characteristic existing as part of a machine-related mathematical model, to generate at least one characteristic field specifying at least one quality parameter depending on the process parameter and the machine-specific setting parameter.

[0008] b) Measure process parameters on the injection molding machine and use these parameters to determine machine-specific settings for the machine axis drive from the characteristic field of the filling simulation, so that the injection molding machine can be operated at the process stage-related optimal values ​​of quality parameters during the actual filling process without manual parameter input.

[0009] This addresses the problem that simulation results often do not match reality by using machine-related process parameter measurements. In addition to using at least one process parameter describing the physical conditions of the molding process for the simulation, at least one additional parameter is used as the basis for at least one machine-specific setting parameter. Furthermore, actual process parameters are measured on the machine.

[0010] DE 40 25 221 A1 discloses a method for setting up a new mold on a plastic injection molding machine, wherein machine operation begins from an initial working point, which is specified by a control program in the form of operating parameter setpoints based on computer-simulated filling of the corresponding mold. The working point of the injection molding machine is adjusted according to the quality of the plastic molded part produced in the trial production, and, if necessary, according to its demolding behavior. An optimization program is used to adjust the working point, which includes basic knowledge of plastic injection molding rules and a characteristic field consisting of operating parameters and quality characteristic data, wherein the characteristic field is created and refined based on experience or systematic learning and memory processes from the operating parameters and quality data that occur during the setting process of the corresponding mold, and wherein, after the setting process is completed, the optimal working point determined for each mold is stored in a retrievable manner.

[0011] DE 10 2022 102 748 A1 discloses a method for controlling a process on at least one plastic processing machine. The method includes the following steps: performing a simulation for producing at least one part, generating a simulation dataset related to the shape profile and / or material properties of the part; determining a process image for operating the machine at an idealized operating point based on the simulation dataset; generating a statistical test plan matrix; iteratively simulating the test plan matrix while calculating residual variations in process parameters, reducing the test plan matrix and obtaining a trained process model for the machine, which enables the manufacture of the part on the machine; verifying the residual variations in process parameters through real experiments, manufacturing and evaluating the part on the machine in experiments to generate a process parameter dataset for operating the machine at the operating point, wherein the operator interacts with a chatbot and / or engages in automated dialogue with an open-loop / closed-loop control device that communicates with at least one evaluation system for evaluating the part; and operating the machine at the operating point using the process parameter dataset.

[0012] EP 3 892 440 A1 discloses a method for setting at least one parameter curve for controlling an injection molding machine that operates cyclically and is used to process plasticizable materials. The method includes the steps of: providing and / or selecting at least one 3D model of at least one geometry of at least one molded part to be molded and / or at least one geometry of at least one cavity; providing and / or selecting at least one simulation program for simulating the production of at least one molded part and / or the filling of at least one cavity on the injection molding machine; providing and / or selecting at least one injection molding material having at least one processing parameter; and performing at least one simulation using the simulation program for at least one geometry. At least one machine-independent process parameter curve is calculated from the simulation as a function of the injection molding material, wherein the calculated process parameters are configured for an "idealized" injection molding process on an "ideal" injection molding machine. The at least one machine-independent process parameter curve is then converted into at least one machine-specific setting parameter for presetting the at least one parameter curve to control the real injection molding machine using construction and machine expertise that takes into account the structural characteristics and / or limitations of the real injection molding machine, and operating the real injection molding machine accordingly. This allows operators to quickly and easily use the results obtained from the simulation to set up the injection molding machine for the next injection process.

[0013] There are also known methods designed to automate the setup and operation of injection molding machines. One of these methods determines machine-independent process parameter curves for an ideal filling process based on filling simulation, taking into account both the mold and material domains. The mold and material domains are considered here. The machine domain is not considered. A common thread in all known methods is that the operator must make multiple inputs on the control panel to set up the process. Ultimately, the operator must rely on expertise that can only be acquired to a limited extent in the future. Furthermore, known methods do not allow injection molding machines to operate at their optimal levels in terms of productivity, energy consumption, and output.

[0014] The performance of injection molding machines is typically defined and configured for specific points based on EUROMAP recommendations (such as EUROMAP 4). In the industry, it is common practice to define the performance of the injection molding unit at an injection pressure of 2000 bar (200 MPa) and configure the pressure-holding axis between 2000 bar (200 MPa) and 1600 bar (160 MPa). The operating point is considered in the machine configuration, including, for example, the injection axis. For this purpose, those skilled in the art refer to the motor characteristics of servo motors and correlate process requirements with motor data, available power supply, efficiency, and reserves. Whether the servo drive drives a directly coupled mechanical system (ball screw, planetary roller screw drive, or rack and pinion), via a belt drive, or a hydraulic pump is irrelevant. This configuration represents the guaranteed performance of the machine axis during continuous operation, but is generally never the ideal operating point for mold operation.

[0015] There are known methods for analyzing and self-optimizing machine motion during operation. For example, the clamping force gradually decreases between cycles until the mold begins to "breathe" during the injection process, i.e., the position of the active mold half indicates that the injection pressure is slightly pushing the mold open. Then, the closing force is increased again with a safety margin, and the machine operates in this manner.

[0016] There are known methods that use filling simulation to find an initial operating point for the injection pressure and temperature profiles, and then transfer that initial operating point to the machine. However, this is optimized from the "filling process perspective," i.e., finding the "ideal" operating point for the filling process. The domains of mold and material are considered here. The focus is not on the optimal operating point of the machine.

[0017] Analysis of thousands of collected machine-mold datasets indicates that machines / molds rarely need to operate at extreme parameters. This means that, in rare cases, injection pressures of 2000 bar (200 MPa) or higher are programmed during operation. To protect sensitive mold inserts, injection pressures are typically limited to well below 2000 bar. Surprisingly, however, maximum closing forces are frequently programmed, which exacerbates mold wear and unnecessarily wastes energy. Summary of the Invention

[0018] The present invention therefore solves the problem of providing a method for setting up and operating a machine, which supports the machine operator in such a way that he / she can both set up the machine (e.g., using an injection mold) and operate the machine at an optimal operating point without inputting any parameters. The operator is supported by an auxiliary system that allows the operator to automatically find the optimal conditions between productivity, energy consumption, and output, and operate the machine accordingly.

[0019] This problem is solved by the method described in claim 1. This is a method for setting up and operating a machine for processing plastics and other plasticizable materials, specifically an injection molding machine, hereinafter referred to as the "machine," comprising at least one electric motor, preferably a servo motor, for at least one machine axis. In the simulation, machine-specific setpoint parameters and machine-independent process parameters for the actual filling process are determined by iteratively approaching the process, based on machine-independent process parameter curves and machine-dependent mathematical models of an ideal filling process. During machine setup, the machine-specific setpoint parameters can be at least partially taught by the operator, and the machine is operated based on the determined and, if necessary, taught machine-specific setpoint parameters and the determined machine-independent process parameters, without the need for manual input of parameters at the optimal operating point of the actual filling process, which represents the optimal conditions between productivity, energy consumption, and output.

[0020] The entire industry faces a growing problem: a shortage of skilled workers. However, these machines should be able to be set up and operated in shifts. This invention aims to ensure that even semi-skilled workers or those with language barriers can set up and operate the machines. This is done without parameter input; after setting up and calculating the mold dataset, the operator simply presses the start button to begin production.

[0021] Therefore, process sequences or process cycles are advantageously established automatically during setup and are subsequently fully available in the sequence editor, for example, via symbols, without the need for parameter input. Waypoints or axis endpoint markers can also be taught, for example, by manually moving machine parts or moving them to these markers in a controlled manner.

[0022] The advantage of this approach is that it allows for the complete determination of both machine-specific settings and machine-independent process parameters for the actual filling process without the need for using an actual injection molding machine, measuring process parameters on that machine, or performing any associated evaluations on a real product. This enables the determination of both machine-specific settings and machine-independent process parameters for the actual filling process without interference and independent of the operator's skill level.

[0023] The problem is also solved by a machine for processing plastic materials according to claim 13, which is set up, configured and / or constructed to perform a method for setting up and operating a machine for processing plastic materials, and by a computer program product according to claim 14, which has program code stored on a computer-readable medium, including instructions for causing the machine of claim 13 to perform the method steps according to claims 1 to 12.

[0024] The subject matter of the dependent claims is an advantageous development.

[0025] To advantageously accelerate the iterative process, the following additional steps are preferably performed according to the method: d) Check whether the operating point is within the motor's operating range based on the motor's characteristics. e) If the operating point is outside the motor's operating range due to being an unattainable operating point, reduce the speed and repeat steps a) to c) and d) of claim 1. f) If the operating point is within the operating range of the motor, then operate the machine at that operating point.

[0026] This allows for the rapid determination of the optimal operating point based on motor characteristics, which advantageously takes into account the desired requirements for the best operating point.

[0027] In an implementation of the preferred mathematical modeling method for mapping a machine, the machine can have a central servo motor, wherein the machine shaft is driven hydraulically in series, and the machine-related mathematical model includes servo motors for operating pumps, cylinder area of ​​the machine shaft, and characteristic data of the hydraulic motors. Advantageously, this allows the entire machine to be mapped.

[0028] Preferably, at least one machine shaft is an electromechanical machine shaft, which, according to the embodiment, may have, for example, at least one component in addition to a motor, including a gear mechanism, a spindle, gears, belts, or the like. This has the advantage that the parameters of these components can be incorporated into the simulation for further parameterization optimization.

[0029] Preferably, the machine can have multiple servo motors, wherein the hydraulically driven machine shaft interacts with multiple motor-pump units, which can be hydraulically coupled, and the machine-related mathematical model includes the servo motors and motor-pump units. This allows the effectiveness of the method to be advantageously used in constructing more complex machines with multiple drives.

[0030] In another preferred embodiment, each machine axis can be driven by a servo motor, wherein the machine-related mathematical model includes the servo motor, gear ratio, efficiency, inertia, and cooling type. This advantageously optimizes the machine model. In a particularly energy-efficient embodiment of the method, to determine the optimal operating point of at least one motor speed depending on the process stage, the optimal operating point is first determined by simulation for each process stage based on the mathematical motor characteristic model, focusing on the torque-speed characteristics. The optimal operating point is then adjusted to set the optimal operating point for each process stage based on the torque-speed characteristics.

[0031] Preferably, these advantages can also be utilized in more complex systems, if the machine-related mathematical model includes a combination of a motor-pump unit and a machine shaft with a servo motor.

[0032] In another energy-saving implementation of the method, at least one servo motor is capable of operating under field weakening conditions. Although field weakening generates current and causes losses, it allows the use of smaller or lower-power motors that are less prone to delays. Preferably, the determined operating point is within the range where the motor operates under field weakening conditions, which, among other things, enables energy-saving operation.

[0033] To facilitate machine operation in a preferred and advantageous manner, the machine can preferably be operated via a control panel, a mobile terminal, or an augmented reality device such as augmented reality glasses. Information content is reduced by displaying symbols rather than parameters.

[0034] Preferably, the machine-related mathematical model can be stored in the control system and / or at a higher control level than the control system. In these method implementations, the direct operational readiness of the machine and / or the feasibility of modular application are advantageously improved.

[0035] To facilitate automation of setup and operation, the machine-related mathematical model preferably includes the following additional machine-specific setting parameters: rated torque, rated speed, rated power, maximum torque, maximum speed, continuous stall torque, and inflection point speed. Furthermore, the machine-related mathematical model can preferably calculate at least the following values ​​for machine operation: injection pressure, injection pressure curve, holding pressure level, holding pressure time, holding pressure curve, dynamics, filling time, closing force, maximum clamping time, metering volume, and metering speed.

[0036] The features listed individually in the claims can be combined with each other in a technically feasible manner and can be supplemented by explanatory facts from the specification and by details from the drawings, in which further variations of the invention are presented. Attached Figure Description

[0037] The invention will now be explained in more detail with reference to the exemplary embodiments shown in the accompanying drawings, in which: Figure 1 This shows the change in the torque characteristics of the electric motor with speed. Figure 2 It shows according to Figure 1 Torque characteristics, with continuous and intermittent operation as shown by the shaded lines. Figure 3 It shows according to Figure 1 The torque characteristics, with continuous operation indicated by shading, Figure 4 It shows according to Figure 1 Its torque characteristics exhibit weak magnetic operation, indicated by shading. Figure 5 It shows according to Figure 1 The torque characteristics, with examples for determining the operating point, Figure 6 A schematic diagram of an injection molding machine and its components is shown. Figure 7 The corresponding process flow is shown. Detailed Implementation

[0038] The invention will now be explained in more detail with reference to the accompanying drawings. However, the exemplary embodiments are merely examples and are not intended to limit the inventive concept to a particular arrangement. Before describing the invention in detail, it should be noted that the invention is not limited to the corresponding components of the apparatus or the corresponding method steps, as these components and methods can vary. The terminology used herein is intended to describe particular embodiments only and is not used in a restrictive manner. Furthermore, when the singular or indefinite article is used in the specification or in the claims, this also refers to multiple such elements unless the context clearly indicates otherwise.

[0039] A method for setting up and operating a machine 150 for processing plastic materials, particularly an injection molding machine, comprising at least one electric motor, preferably a servo motor 170, for at least one machine axis 160, the motor characteristics, particularly the torque-speed characteristics M(n), of which are available as part of a machine-dependent mathematical model 190, wherein machine-independent process parameter curves for an ideal filling process are determined by a filling simulation considering the mold 10 and the material Mat domain. In the simulation, a) based on the machine-independent process parameter curves for the ideal filling process and the machine-dependent mathematical model 190, machine-specific setup parameters and machine-independent process parameters for the actual filling process are first determined by an iterative approximation process. Then, b) the machine-specific setup parameters can be at least partially taught by the operator during machine setup. c) the machine is operated based on the determined and optionally taught machine-specific setup parameters and the determined machine-independent process parameters without the need for manual input of parameters at an optimal operating point WP, which represents the optimal conditions between productivity, energy demand, and output rate, depending on the process stage of the actual filling process.

[0040] This simulation is used to approximate ideal filling processes and optimal processing procedures, such as injection molding. It is an iterative process designed to achieve optimal maximum productivity with minimal energy consumption. Forces are precisely set to the optimal operating requirements. Energy-intensive and unnecessary safety margins are eliminated, and machine 150 and mold 10 are protected. The closed curve (the moving and closing forces varying over time) is defined based on automatically set information and calculated iteratively determined values.

[0041] Preferably, the method for determining the operating point WP includes additional steps that enable iterative approximation of the desired optimal operating point: d) For this purpose, motor characteristics are used to check whether the determined operating point WP is within the operating range of the motor.

[0042] e) If the operating point is outside the motor's operating range, reduce the speed n and repeat steps a) to c) (see above) and d).

[0043] f) If the operating point 120 is within the operating range of the motor, then the machine 150 is operated at this operating point.

[0044] Mathematical model 190 can advantageously represent the first preferred technology of the machine, wherein the machine has only a central servo motor 170, and the machine shaft 160 is driven by hydraulic series connection. The machine-related mathematical model 190 can include servo motor for operating the pump, cylinder area of ​​machine shaft 160, and characteristic data of hydraulic motor.

[0045] Mathematical model 190 can also advantageously represent a second preferred technology for the machine, wherein each machine axis 160 of machine 150 is driven by a servo motor 170. The machine-related mathematical model 190 can include servo motors, gear ratios, efficiency, inertia, and cooling type. Machines with two or more servo motor / pump drives and / or combinations of these servo electric drives are also envisioned, referred to as hybrid machines. Figure 6 ).

[0046] Figure 6 A known machine 150 in the form of an injection molding machine is schematically shown in the upper front view, where the mold clamping unit is visible on the left side above the machine base 130, and the injection unit is visible on the right side. The various machine axes 160 are schematically labeled as follows; these axes could be for opening and closing the mold 10, for ejection 20, for core pulling 30, for nozzle movement 40 (applying the injection nozzle to the mold gate), for injection 60, or for metering 70. The machine 150 is equipped with a control system 185, which is typically integrated into the machine. The operating unit 180 is visible on the upper right side.

[0047] All these machine axes can be driven by electric motors, preferably servo motors 170. The machine can be configured in various ways, such as... Figure 6 As shown below. It can be equipped as a hydraulic injection molding machine (SGM) with a servo-hydraulic system, or as an electric injection molding machine with a servo-electric drive. Various hybrid machine configurations are possible, in which some machine axes are servo-hydraulic operated while others are servo-electric operated.

[0048] In order to produce in a particularly energy-efficient manner, it is possible to first use simulation based on a mathematical motor characteristic model of the torque-speed characteristic M(n) of each process stage to determine the optimal operating point for each process stage, and then adjust the optimal operating point so that the operating point is optimized relative to the torque setting speed for each process stage in terms of torque-speed characteristics.

[0049] If at least one motor is a servo motor 170 operating under weak field operation (FWO), energy savings are also possible. For this purpose, the motor can operate within its rated torque range M 额定 Operations outside of (continuously running S1) are within this range. Figure 2 The image is shown in shaded mode and can also operate outside the range of intermittent operation S3, allowing the motor to be driven to different operating points, a process known as field weakening operation (FWO). This operation allows only lower torque but simultaneously allows higher speeds, thus enabling, for example, higher injection speeds. However, higher injection speeds also mean higher injection pressures. Although field weakening results in applied current, which also incurs losses, savings are achieved, for example, by using smaller or lower-powered and therefore less sluggish motors.

[0050] Field weakening is a method to significantly increase the speed of a rotating electric motor above its rated speed. Once the speed n exceeds the voltage limit M... Umax Due to the characteristics of this, the torque M will decrease. Therefore, field weakening is used when high torque is required at low speeds and lower torque is required at high speeds. Field weakening allows the rotational speed to be increased beyond the additional speed to achieve the desired maximum range.

[0051] The machine can also be based on Figure 6 The device is conveniently operated via an operating unit 180, such as an operation panel, a mobile terminal device, or an augmented reality device such as augmented reality glasses. By displaying symbols instead of parameters, the amount of information is reduced, making operation easier. The mold 10 is set sequentially without requiring parameter input, thanks to the extended setup wizard E. Axes are moved automatically for setting, forces are limited, and paths and positions are taught. This defines mold movement and ejection movement.

[0052] like Figure 6 As shown, the machine-related mathematical model 190 can be stored in the control system 185 of the machine 150 and / or at a higher control level of the control system. In these method implementations, the machine's direct operational readiness state and / or modular application feasibility are improved.

[0053] Preferably, the machine-related mathematical model 190 can also include the following additional machine-specific setting parameters: rated torque M 额定 Rated speed, rated power, maximum torque M max Maximum speed n max Continuous stall torque M0, inflection point speed 50.

[0054] In plastic injection molding machines, the maximum injection speed (or injection flow rate relative to the screw diameter) is achieved at the maximum limited injection pressure at the corner speed / maximum torque 50 (at maximum power). The maximum continuously achievable holding pressure is defined by the continuous stall torque M0.

[0055] As described below, the machine-related mathematical model 190 can be used to calculate at least the following values ​​for machine operation: injection pressure, holding pressure level, holding pressure time, dynamic characteristics, filling time, closing force, and maximum clamping duration.

[0056] Key values ​​for operation of processing functions such as injection molding can be calculated from the motor characteristics of the servo motor. For example, torque M is a parameter mathematically related to injection pressure. The rotational speed n at maximum torque (rated speed at rated power), the gear ratio, inertia, and efficiency of the gearing system determine the dynamic characteristics, thus determining the filling time. The continuous stall torque M0 is an indicator of the achievable holding pressure level. The cooling type (air-cooled or water-cooled) plays a decisive role in the achievable holding pressure time for a cycle. For this purpose, the holding pressure curve is limited by I²t evaluation (I = current, t = time) and achievable cooling capacity. The same applies to the axis function "mold movement," where the closing force, dynamic characteristics (idle run time), and maximum clamping time can also be calculated from the motor characteristics.

[0057] For example, the following calculations can be performed using the following names in the formula: Formula symbols: p_injection: Injection pressure during the injection phase F - Injection pressure: Injection force SD: Diameter of the plasticized screw F_ (Clamping_WKZ): Mold clamping force A_Injection Molded Part: Projected area of ​​the molded part or cavity p_holding pressure: Injection pressure during the holding pressure phase. : Drive torque motor to move mold and establish clamping force i(s_WKZ): The transmission ratio of the toggle lever depends on the mold position. η: Efficiency of the corresponding drive spindle h_(WKZ) and h_injection: Spindle pitch driving the spindle M_(eff): Effective torque M_ (Drive_NDx): Drive torque during pressure phase x t_NDx: Continuous pressure maintenance phase x M_0: Continuous stall torque ω_drive: acceleration at the drive point M_ (Drive_max): Maximum motor torque M_Load: Load torque (e.g., caused by injection pressure, inertia, or clamping force). J_tot: Total inertia a_ (〖max〗_adm): Maximum permissible acceleration t_injection: filling time s_injection: injection course v_injection: injection speed a_injection: acceleration during injection Injection force depends on injection pressure (maximum 2000 bar) and is related to screw diameter: F_injection pressure=π 〖SD〗^2 / 4 p_injection The driving torque required for this injection force depends, in turn, on the spindle pitch and the efficiency of the drive spindle: M_(Drive_Injection) = F_Injection Pressure h〗_injection / (2 π η) If the motor and gears are not considered as a single unit, then the gear ratio / efficiency should be added to the formula. Otherwise, at the drive point of injection movement, the relationship between injection pressure and drive torque can be derived as follows: M_(Drive_Injection)~p_Injection The same applies to the holding pressure stage—the holding pressure is typically lower than the injection pressure, meaning a lower torque is required, and for long-term holding pressure, it should on average be lower than the aforementioned continuous stall torque M0. If necessary, the holding pressure level must be automatically adjusted by such a reduction, depending on the duration, so that the mean square of the holding time and pause time (e.g., during the cooling phase) is lower than the continuous stall torque M0.

[0058]

[0059] The clamping force of the mold depends on the injection pressure and the projected area of ​​the molded part: F_(clamp_WKZ)=p_injection A_Molded Parts During the holding pressure phase, the mold closing force depends on the holding pressure level and the projected area of ​​the molded part: F_(Clamping_WKZ) = p_Holding Pressure A_Molded Parts During the clamping force build-up, the torque requirement of the mold drive is proportional to the required clamping force and the variable transmission ratio of the toggle lever along the mold path: F (Clamping WKZ) ~ M (Drive WKZ) i(s_WKZ) (Note: The relationship between M and F, which have a spindle pitch and are used to drive the spindle, is not discussed here.)

[0060] This allows us to derive the relationship between injection pressure and drive torque at the mold movement drive: M_ (Driver_WKZ) i(s_WKZ)~p_injection To determine the set parameters, the limiting torque can be converted into the limiting pressure.

[0061] M_(Drive_Injection)~p_Injection

[0062] The rotational speed n at the operating point 120 can be converted into the injection speed.

[0063] v_injection = w_(point_120) i_ (tot, injection)

[0064] Therefore, it is possible to determine other set parameters that utilize the material properties, such as pressure and temperature.

[0065] In addition, the dynamic characteristics can be roughly estimated by subtracting the load (injection pressure, closing force, etc.) from the maximum torque. Friction is ignored.

[0066]

[0067] Here, a_max_adm is the acceleration specified in the control system, which can be less than the acceleration based on M. max The possible acceleration, the smaller the value, determines the dynamic characteristics.

[0068] M_drive_max does not describe the maximum possible motor torque, but rather the maximum torque approved in the control system.

[0069] To calculate the filling time, it can be estimated from the following equation, which applies to trapezoidal movement that reaches a specified acceleration (but not the torque limit) (assuming: single-stage injection, filling the cavity at the switching point to pressure control, braking during the holding pressure stage, ignoring system dynamics, i.e., no tracking error): t_injection = v_injection / a_injection + (s_injection - 1 / 2) [v_injection]^2 / a_injection) / v_injection However, the deceleration phase of the trapezoidal movement is ignored in the filling time formula, making the movement more like a "slope" movement in a strict sense.

[0070] Special cases such as triangular manipulation and multi-stage injection are not considered in this formula, but can be determined in a similar way.

[0071] From the perspective of the injection axis, the domain of mold 10 and the domain of material Mat can be determined as the ideal filling process based on the filling simulation, and then calculated together with the domain of the machine as the optimal operating point WP (the optimal condition between productivity, energy demand and output speed).

[0072] The injection speed (equivalent to the volumetric flow rate of the molten plasticized material) depends on, for example, viscosity and therefore also on the material being processed, the temperature profile of the plasticizing unit, and the hot runner of the mold, generating the injection pressure profile during mold / cavity filling. The required holding pressure (related to the continuous stall torque M0 in the motor characteristics) can also be simulated. The required closing force can be calculated based on the injection pressure and holding pressure, as well as the projected area of ​​the plastic in the mold 10 known in the filling simulation. The injection pressure profile and holding pressure profile thus directly determine the closing force profile. Based on the simulated plasticizing unit temperature and mold / hot runner temperature profiles, and the simulated holding pressure duration, the key parameters for operating an injection mold in a specifically defined machine are now calculated and known.

[0073] This is through the attached Figures 1 to 5 To illustrate, these figures show the torque characteristics of an electric motor (preferably a servo motor 170), expressed as torque M varying with rotational speed n.

[0074] Figure 1 The solid line indicates the typical operating range. The line above shows the maximum torque M related to the engine speed. max Maximum power is reached at the so-called corner speed of 50 rpm. After that, maximum torque drops to the rated torque M. 额定 The rated power at the specified location. Continuous stall torque M0 is the torque that the motor can continuously generate when stationary.

[0075] When the rated torque M is reached 额定 Then, the power is limited along the voltage M. Umax Decrease. In Figure 1 In the diagram, the dashed line is drawn to the right of the solid line. The dashed line indicates the operation of weakening the magnetic field, which will be discussed in detail below. Figure 4 Let's have a discussion.

[0076] Figure 2 and Figure 3A continuous operating region S1 and an intermittent operating region S3 are shown. The continuous operating region forms the rated torque range over which the motor typically operates, and the intermittent operating region lies above it. Figure 1 The image is shown in shaded lines. In continuous operation S1, as the name suggests, the motor can run continuously. However, in intermittent operation, which requires higher power, there is a percentage or temporary on-time, allowing overheating to dissipate during operation interruptions thanks to proper cooling. Therefore, intermittent operation consists of on-time and cooling gaps.

[0077] exist Figure 4 Medium, high-speed n-voltage limiting M Umax The area on the right (without field weakening operation) is shaded. This field weakening operation FWO area is outside the rated torque range. Figure 2 The shaded area (in the middle) allows the motor to be driven to different operating points, a technique known as field weakening operation (FWO). This operation only allows for lower torque M, but simultaneously enables higher speeds n, thus achieving, for example, higher injection speeds. However, higher injection speeds also mean higher injection pressures. This range is limited above by the voltage M during field weakening operation. Umax FWO Limited by, and subject to the maximum motor speed n on the right side. max The limitations are mitigated. In weak field operation, high torque can be achieved at low speeds and lower torque at high speeds. This allows the rotational speed to be increased beyond the additional speed required to reach the desired maximum range.

[0078] Figure 5 The procedure according to the present invention is shown in the torque characteristic diagram. The starting point in the diagram is an unattainable operating point 100, which is determined based on simulation.

[0079] The simulation is based on machine-independent process parameter curves and a machine-dependent mathematical model 190 for an ideal filling process, combining machine-specific setpoints and machine-independent process parameters of the actual filling process through an iterative approach process. Specific material properties of the material to be processed are also taken into account. During machine setup, the machine-specific setpoints can be at least partially taught by the operator, and the machine 150 operates at an optimal operating point 100 of the actual filling process, depending on the process stage, based on the determined and, if necessary, taught machine-specific setpoints and the determined machine-independent process parameters, without requiring manual parameter input. This optimal operating point represents the best conditions between productivity, energy demand, and output.

[0080] If this optimal operating point of 100 is outside the effective range of the motor, such as Figure 5 As shown, maintaining the torque level makes sense. This method produces operating point 110, however, this operating point is not speed-optimized. The iterative process utilizes material and machine properties to produce operating point 120.

[0081] Once the operating point 120 is found, the machine-specific settings can be determined using the above calculations based on the motor characteristics, simulation of machine-specific settings parameters, and machine-independent process parameters of the actual filling process.

[0082] Figure 7 An example of a schematic process flow is shown. The process is designed to set up and operate a machine 150, particularly an injection molding machine, for processing plastics and other plasticizable materials. The machine has at least one electric motor, preferably a servo motor 170, for at least one machine shaft 160, the motor characteristics K of which, in particular the torque-speed characteristics M(n), are available as part of a machine-related mathematical model 190.

[0083] exist Figure 7 In step 200, a filling simulation is first performed, taking into account the domain of mold 10 and material Mat, in order to determine the machine-independent process parameter curves of the ideal filling process in step 210.

[0084] In step 220, the machine-specific setpoint parameters and machine-independent process parameters of the actual filling process are now determined in the simulation. For this purpose, a machine-dependent mathematical model 190 is provided, which enables the determination of machine-specific setpoint parameters based on the machine-independent process parameter curves of the ideal filling process and the machine-dependent mathematical model 190 (step 230).

[0085] During the setup of machine 150, machine-specific setting parameters can also be taught at least partially by the operator in step 240.

[0086] Based on this information, and combined with the motor characteristic K, the actual operating point WP of the filling process can be determined in step 250 based on the determined and, if necessary, taught machine-specific setting parameters and the determined machine-independent process parameters. This process can be iterative. The operating point is determined without manual parameter input. The operating point is the process-stage-related optimal operating point WP, representing the optimal conditions between productivity, energy demand, and output. The machine can then operate at this operating point according to step 270.

[0087] Further iterative processes may require query 260 to check whether the operating point WP is within the motor's operating range based on motor characteristics. If the operating point is proven to be unreachable, then operating point 110 (…) Figure 5 If the operating point is outside the motor's operating range, then repeat steps 220 to 250 at a reduced speed. If the operating point is 120 ( Figure 5 If the motor is already within its operating range, then operate machine 150 at this operating point according to step 270.

[0088] This method can be used in machines for processing plastic materials, which are set up, configured and / or constructed to perform methods for setting up and operating the machine for processing plastic materials.

[0089] Furthermore, this method can be used in a computer program product that includes program code stored on a computer-readable medium, including instructions that cause machine 150 to perform method steps.

[0090] It goes without saying that various modifications, alterations, and adjustments can be made to this specification within the scope of equivalents of the appended claims.

[0091] List of reference numerals

[0092] 10 Molds

[0093] 20 ejector

[0094] 30 core pulls

[0095] 40 Moving nozzle

[0096] 50 rpm (maximum power)

[0097] 60 injections

[0098] 70 Measurement

[0099] 100 Unreachable work points

[0100] 110 Possible work locations

[0101] 120 operation points

[0102] 150 machines

[0103] 160 machine axis

[0104] 170 servo motor

[0105] 180 operating units

[0106] 185 Control

[0107] 190 Machine-related mathematical models

[0108] Steps 200 to 270 Figure 7 )

[0109] WP work location

[0110] E Setup Wizard

[0111] FWO Weak Field Operating Range

[0112] K characteristics

[0113] M0 Continuous stall torque

[0114] M 额定 Rated torque

[0115] M max Maximum torque

[0116] n rotational speed

[0117] n max Maximum speed

[0118] S1 Continuous Operation

[0119] S3 Intermittent Operation

[0120] M Umax Voltage limit for operation without field weakening

[0121] M Umax FWO Voltage limits during weak magnetic field operation.

Claims

1. A method for setting up and operating a machine (150) for processing plastics and other plasticizable materials, said machine, in particular an injection molding machine, said machine comprising at least one electric motor for at least one machine axis (160), said electric motor preferably a servo motor (170), said electric motor having motor characteristics (K), in particular torque-speed characteristics M(n), as part of a machine-related mathematical model (190), wherein, The machine-independent process parameter curves for an ideal filling process are determined by filling simulation considering both mold and material properties. Its features are, a) In the simulation, based on the machine-independent process parameter curves of the ideal filling process and the machine-dependent mathematical model (190), the machine-specific setting parameters and machine-independent process parameters of the real filling process are determined by an iterative approach process. b) During the setup of the machine, the operator can at least partially teach the machine specific setting parameters, and c) Based on the determined and optionally taught machine-specific setting parameters and the determined machine-independent process parameters, the machine is operated at an optimal operating point (WP) related to the process phase of the actual filling process without manual parameter input, the optimal operating point representing the best conditions between productivity, energy demand and output.

2. The method according to claim 1, characterized in that, It also includes other steps: d) Based on the motor characteristics, check whether the operating point (WP) is within the operating range of the motor. e) If the operating point is not within the operating range of the motor as an unreachable operating point (110), then reduce the speed (n) and repeat steps a) to c) and d) of claim 1 in sequence. f) If the operating point (120) is within the operating range of the motor, then the machine is operated at the operating point.

3. The method according to claim 1 or 2, characterized in that, An electromechanical machine shaft is used as the at least one machine shaft.

4. The method according to any one of the preceding claims, characterized in that, The machine has a central servo motor that drives the machine shaft in a hydraulic series manner. The machine-related mathematical model (190) includes the servo motor (170) for operating the pump, the cylinder area of ​​the machine shaft (160), and the characteristic data of the oil motor.

5. The method according to any one of claims 1 to 3, characterized in that, The machine includes multiple servo motors (170), wherein a hydraulically driven machine shaft (160) interacts with multiple motor pump units (195), the motor pump units being hydraulically aggregated, wherein the machine-related mathematical model (190) includes the servo motors and motor pump units.

6. The method according to any one of claims 1 to 3, characterized in that, Each machine axis (160) of the machine (150) is driven by a servo motor (170), wherein the machine-related mathematical model (190) includes the servo motor, gear ratio, efficiency, inertia and cooling type.

7. The method according to any one of claims 4 to 6, characterized in that, The machine-related mathematical model (190) includes a combination of a motor pump unit (195) and a machine shaft (160) with a servo motor (170).

8. The method according to any one of the preceding claims, characterized in that, To determine the optimal operating point (WP) of the speed for each process stage of the at least one electric motor, the optimal operating point is first determined by simulation for each process stage in the torque-speed characteristic M(n) based on a mathematical motor characteristic model, and then the optimal operating point (WP) is adjusted to set the optimal operating point of the speed relative to the torque in the torque-speed characteristic for each process stage.

9. The method according to any one of the preceding claims, characterized in that, The at least one motor is a servo motor (170) that operates in field weakening operation (FWO), wherein the determined operating point (WP) is preferably in field weakening operation.

10. The method according to any one of the preceding claims, characterized in that, The machine is operated via an operation unit (180), which may be, for example, an operation panel, a mobile terminal device, or an augmented reality device such as augmented reality glasses.

11. The method according to any one of the preceding claims, characterized in that, The machine-related mathematical model (190) is stored in the control system (185) of the machine (150) and / or stored at the higher control level of the control system.

12. The method according to any one of the preceding claims, characterized in that, The machine-related mathematical model (190) includes at least the following additional machine-specific setting parameters: rated torque (M 额定 Rated speed, rated power, and maximum torque (M) max ), maximum speed (n max ), continuous pause torque (M0), inflection point speed (50), and wherein at least the following values ​​for operating the machine are calculated from the machine-related mathematical model (190): injection pressure, injection pressure curve, holding pressure level, holding pressure time, holding pressure curve, dynamics, filling time, closing force, maximum clamping time, metering volume, and metering speed.

13. A machine (150) for processing plastics and other plasticizable materials, said machine in particular an injection molding machine, said machine being used for processing plasticizable materials, said machine being set up, configured and / or constructed to perform a method according to any one of the preceding claims for setting up and operating a machine for processing plasticizable materials.

14. A computer program product having program code stored on a computer-readable medium, the program code including instructions that cause the machine (150) according to claim 13 to perform the steps of the method according to any one of claims 1 to 12.

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