Method and system for improving injection molding process

Abstract

A method for improving an injection molding process, wherein a product (1) is produced from a precursor charge (3) of a precursor material by an injection molding process based on a process setting (5) applied to an injection molding device (2) by the injection molding process, wherein the injection molding process comprises injecting the precursor charge (3) into a mold (4) of the injection molding device (2), wherein the precursor charge (3) is produced by a precursor production process described by precursor production parameters (21), wherein the applied process setting (5) is determined prior to the injection molding process by a computer simulation of the injection molding process performed by a computing device (6), the computer simulation being based on a simulation model (7) of the injection molding process, the precursor production parameters (21) and given process conditions (8), the given process conditions (8) comprising a shape of the mold (4). The invention also relates to a corresponding system for improving an injection molding process.

Description

[0001] The present invention relates to a method for improving an injection molding process and a system for improving an injection molding process.

[0002] Production processes, and in particular injection molding processes, are complex. When a new product is to be produced by means of an injection molding process, a new mold is to be provided to the injection molding device. In order to achieve a desired high product quality, a plurality of process settings must be correctly set. However, because the correct process settings for achieving this desired product quality depend on a multitude of factors, among which in particular the shape of the mold used for the injection molding process and also the quality and parameters of the specific precursor material used, for a new mold a plurality of trial runs of the injection molding process and subsequent analysis of the products must be performed before satisfactory process settings can be determined. These numerous trial runs and themselves are cost- and time-intensive and thus undesirable.

[0003] Furthermore, even if satisfactory process settings are finally determined, again a similar plurality of trial runs will have to be performed at different locations because the same or very similar injection molding processes are to be performed at slightly different conditions at different locations.

[0004] EP 3511783 A1 from the prior art discloses a method for improving a chemical production process, wherein a plurality of derived chemical products is produced by a derived chemical production process based on at least some derived process parameters at respective chemical production facilities, each of the chemical production facilities comprising a separate respective intra-facility network, wherein at least some respective derived process parameters are measured from the derived chemical production process by a respective production sensor computer system within each intra-facility network, wherein a process model for simulating the derived chemical production process is recorded in a process model management computer system outside the intra-facility networks. The method is characterized in that the process model is transmitted from the process model management computer system to a respective computing module for performing a numerical analysis in each intra-facility network, the derived process parameters at each chemical production facility are provided to the respective computing module, and each computing module determines respective modification data for updating the process model by a numerical analysis based on the derived process parameters at the respective chemical production facility and the process model.

[0005] US 2019 / 0105826 Al, considered to be the closest prior art, discloses a system comprising a cavity, an injection nozzle configured to inject material into the cavity, and a plurality of sensors at various sensor locations. Each of the plurality of sensors is configured to measure a parameter at one of the sensor locations. The system has no strain gauges. The system further comprises a controller configured to control a flow rate of the injection of material into the cavity. The controller is configured to receive the measured parameters and compare the received information with a predetermined profile. The controller is configured to control the flow rate when the measured parameters deviate from the predetermined profile.

[0006] It is therefore an object of the present invention to provide a method and a system for improving an injection molding process which reduces the number of trial runs when introducing a new such injection molding process and which makes it easier to transfer results from a trial run at one location to a similar injection molding process at a different location.

[0007] With respect to a method for improving an injection molding process, the object of the present invention is achieved by a method for improving an injection molding process according to an aspect of the present invention. With respect to a system for improving an injection molding process, the object of the present invention is achieved by a system for improving an injection molding process according to another aspect of the present invention.

[0008] The present invention is based on the recognition that a computer simulation of an injection molding process, which simulation takes into account in particular not only the shape of the mold but also production information about the precursor filling, can be used to determine process settings for the injection molding process which are at least closer to those process settings which are found to result in products of acceptable quality. In other words, using a computer simulation which relies on the shape of the mold and additional production information about the precursor filling can permit to arrive at process settings which are just sufficient to achieve a desired product quality. Taking into account production information about the precursor filling enables to control variations of production-related parameters. Alternatively, even if the process settings arrived at by the computer simulation have not yet resulted in products of a desired quality, they will provide a better starting point for trial runs than would have been possible without the computer simulation. In this way, the number of trial runs is reduced in any case.

[0009] Furthermore, such a computer simulation can also be used to achieve a process setting which is not used in order to obtain a product with a desirable quality for actual use, but to perform an injection molding process and a subsequent analysis of the product on the basis of which the simulation model of the computer simulation itself can be improved. In other words, the computer simulation can be used as a tool for design of experiments (DOE). Such an attempt at an injection molding process then does not directly contribute to achieving a process setting for realizing a desirable product quality for a specific product, but rather makes the simulation model more accurate. In this way, the number of remaining production attempts for all subsequent products using the computer simulation is reduced.

[0010] The method according to the present application is for improving an injection molding process. In the method according to the present application, a product is produced from a precursor charge of a precursor material by an injection molding process based on a process setting applied to the injection molding device by the injection molding device, wherein the injection molding process comprises injecting the precursor charge into a mold of the injection molding device. The precursor material can comprise a mixture of any number of different components in various proportions.

[0011] Further, in the method according to the present application, the precursor charge is produced by a precursor production process described by precursor production parameters. Additionally in the method according to the present application, the process setting applied is determined prior to the injection molding process by a computer simulation of the injection molding process performed by a computing device, the computer simulation being based on a simulation model, on the precursor production parameters and on given process conditions of the injection molding process, the given process conditions comprising a shape of the mold. In other words, the computer simulation relies on a simulation model, which can be a computer program of its own right or specific data to be used by a general-purpose computational modeling program. The computer simulation relies on this simulation model and as input on any number of given process conditions of the injection molding process and on any number of precursor production parameters. These given process conditions can be given because they are based on actual measurements and thereby reflect a reality as it exists previously. The given process conditions can also relate to any other known or assumed physical facts. They can also be boundary conditions assumed to exist previously only. In any case, the given process conditions comprise a shape of the mold. Thereby, the computer simulation relies on the shape of the mold. The nature of this reliance is in principle arbitrary as long as the shape of the mold is taken into account in the computer simulation and in particular in the process setting determined by the computer simulation performed. Likewise, the reliance of the computer simulation on any one or more precursor production parameters can be in principle arbitrary as long as the one or more precursor production parameters are taken into account in the computer simulation and in particular in the process setting determined by the computer simulation performed.

[0012] The injection molding process can in principle be any kind of injection molding process. According to a preferred embodiment of the method, the injection molding process comprises a thermoplastic process. Herein, the precursor charge can comprise a thermoplastic material, in particular a thermoplastic polymer material. Preferred thermoplastic polymer materials can comprise polycarbonate (PC), polyethylene terephthalate (PET), acrylonitrile butadiene styrene (ABS), polyamide (PA), polyvinyl acetate (PLA), polymethyl methacrylate (PMMA), polyethylene (PE), polypropylene (PP), polystyrene (PS), polyether ether ketone (PEEK) and / or polyvinyl chloride (PVC) or mixtures or blends thereof. In particular, in case a thermoplastic material is used in the precursor charge, the thermoplastic material can be ready for processing and is supplied as bulk material, e.g. in particulate form, provided from a storage in form of any kind of packaging, e.g. bags, packs, etc.

[0013] According to a further preferred embodiment of the method, the injection molding process comprises a reaction process. In particular, the reaction process can be a thermoset curing process. Preferably, the product is a polyurethane product and the precursor charge comprises an isocyanate and a polyol for forming the polyurethane product. Thus, the precursor charge can comprise any number of precursor sub-charges. The precursor charge can also comprise any number of further components and ingredients in this case.

[0014] In principle, the computer simulation of the injection molding process can simulate the process in any way. Preferred embodiments of the method are characterized in that the computer simulation comprises simulating the flow of the injected precursor charge through the mold based on the shape of the mold. In other words, the simulation of the flow is based on the shape of the mold. Thereby, the shape of the mold is taken into account in the computer simulation and the process settings determined therefrom. In particular, it is possible that the simulation of the flow of the injected precursor charge through the mold takes into account substantially the entire inner surface of the mold. In this way, the most accurate and comprehensive simulation of the flow through the mold can be achieved. The flow of the injected precursor charge through the mold is one of the most relevant aspects of the injection molding process and one of the aspects in which the shape of the mold plays a key role.

[0015] Further preferred embodiments of the method are characterized in that the precursor charge is produced at a precursor production facility remote from an injection molding facility comprising the injection molding device and that the precursor charge is transported to the injection molding facility. Thus, the injection molding process can be improved based on information observed outside the site. It is also possible that the precursor charge is produced at a plurality of precursor production facilities all remote from the injection molding facility.

[0016] According to a preferred embodiment of the method, the precursor filler comprises a granulated polymeric material for injection molding. Preferably, the precursor filler is produced from a starting material by a precursor production process. It is also possible that the precursor filler is produced from a plurality of starting materials by the precursor production process. The plurality of starting materials can further comprise at least one additive. The at least one additive can comprise a catalyst, in particular hydrochloric acid, water, a blowing agent, and / or a foam stabilizer.

[0017] The starting material can in particular be a polymeric precursor. It is further preferred that the precursor production process comprises a compounding process for producing the granulated polymeric filler. In particular, the precursor production process is performed by a heated twin-screw extruder.

[0018] According to another preferred embodiment of the method, the precursor filler is a liquid filler for injection molding. The plurality of starting materials can comprise aniline, formaldehyde, phosgene, ethylene oxide, and / or propylene oxide.

[0019] According to a further preferred embodiment of the method, the precursor production parameters comprise precursor production settings applied to the precursor production process. Such precursor production settings can thus be set by a user of the precursor production process and thus input. In this way, a correlation of production settings during the production of the precursor filler can be taken into account in the injection molding process.

[0020] Alternatively or in addition, the precursor production parameters can comprise precursor process variables measured from the precursor production process. In contrast to the precursor production settings, these precursor process variables are not directly determined by a user of the precursor production process, but instead occur as a result and are thus an output of the precursor production process. In terms of a correlation for the injection molding process, the precursor process variables can be equivalent in importance to the precursor production settings.

[0021] A preferred embodiment of the method is characterized in that starting material parameters are measured from the starting material, and the computer simulation is further based on the measured starting material parameters. It is also possible that starting material parameters are measured from a plurality of starting materials. Such starting material parameters can relate to any physical data characterizing a specific batch of a given starting material from different batches of the given starting material having a specific material composition. The starting material parameters thus serve to distinguish individual batches of the starting material. Alternatively or in addition, additive parameters are measured from the at least one additive, and the computer simulation is further based on the measured additive parameters. Thereby, not only the precursor filler and its properties can be taken into account, but also the properties of the precursor of the precursor filler.

[0022] A further preferred embodiment of the method is characterized in that starting material history data are determined for the starting material, and the computer simulation is further based on the starting material history data. Such starting material history data can represent past processing data related to the starting material. This can include production data and / or storage duration indications.

[0023] According to a further preferred embodiment of the method, precursor product parameters are measured from the precursor charge prior to the injection molding process, and the computer simulation is further based on the measured precursor product parameters. Such measurement of precursor product parameters can in principle be any kind of measurement, and can also be any kind of measured property of the precursor charge. This enables properties that can be determined by measuring the precursor charge to be taken into account.

[0024] A further preferred embodiment of the method is characterized in that simulating the flow of the injected precursor charge through the mold includes simulating the fluid dynamics of the flow of the precursor charge. Using fluid dynamics for this simulation ensures greater accuracy for the simulation. Preferably, simulating the flow of the injected precursor charge through the mold includes simulating the effect of the surface of the mold on the fluid dynamics of the flow of the precursor charge. Taking this effect into account for the simulation further improves the accuracy of the simulation.

[0025] The given processing conditions can in principle include any information or parameter that determines or influences the injection molding process. According to a preferred embodiment of the method, the given processing conditions are the material composition of the precursor charge. The material composition of the precursor charge defines the materials that make up the precursor charge and their respective proportions. It is further preferred that the simulation of the flow of the injected precursor charge through the mold is based on the material composition of the precursor charge. In other words, the simulation reflects any influence that the material composition of the precursor charge can have on the flow of the injected precursor charge.

[0026] According to a further preferred embodiment of the method, the given processing conditions include environmental conditions of the injection molding process. Such environmental conditions of the injection molding process can include the ambient temperature and / or the ambient humidity of the injection molding device. Preferably, the environmental conditions of the injection molding process are measured by sensor instrumentation of the injection molding device. In additional or alternative preferred embodiments of the method, the given processing conditions include fixed characteristics of the injection molding device. These can be construction features of the injection molding device that are predefined and do not undergo changes. Such fixed characteristics can include, for example, the maximum output power of the injection molding device.

[0027] In principle, the basis for the computer simulation can be any measurement or approximation of the injection molding apparatus. A preferred embodiment of the method is characterized in that the computer simulation is based on a data representation for computer-aided design, which describes the geometry of the physical components of the injection molding apparatus, which data representation is constituted by the given processing conditions. Such a data representation is particularly suitable for use in the simulation, since it avoids measurement or approximation errors. Preferably, the data representation is configured to enable production of the physical components by a component production apparatus. Further, it is possible that the data representation has already been used for production of the physical components by a component production apparatus. In this case, the highest possible conformity of the data representation to the actual physical components of the injection molding apparatus can be guaranteed. In particular, it is possible that the physical components are molds. Since the molds and in particular their geometry are of particular importance for determining the flow of the injected precursor mass, the data representation of the molds in particular facilitates an accurate simulation.

[0028] A further preferred embodiment of the method is characterized in that the computer simulation comprises a numerical simulation of the injection molding process. Such a numerical simulation is particularly useful when an analytical method is not possible or appropriate. However, it is also possible that the computer simulation comprises determining an analytical solution for simulating the injection molding process.

[0029] The method according to the application can be used to reduce the number of production attempts for injection molding a given product in a desired degree of quality. In a corresponding preferred embodiment of the method, a product target specification is provided to the computing device. It is further preferred here that the computer simulation is based on applying the product target specification to the simulation model. In particular, it is possible to determine processing settings for bringing the product into conformity with the product target specification. In other words, the product target specification is applied to the simulation model to determine from the simulation model processing settings that are suitable for meeting the product target specification.

[0030] In the method according to the application, the product is measured by a product measuring device for determining product data, and a quality measure is applied to the product data to determine a measure result for describing the conformity of the product to a product target specification that prescribes properties of the product. In other words, the product data represents properties of the product independent of a specific target, such as size, weight, surface roughness, etc. On the other hand, the measure result is a quantitative or qualitative representation of how close the product is to complying with the product target specification according to the product data. The quality measure defines how the measure result is determined. For example, some properties, such as weight, can allow a wide range, while other properties, such as a length dimension, can be specified much more narrowly. Likewise, deviations from the product target specification for one property can be weighted differently than deviations for another property.

[0031] The results of the measurements are fed back to the simulation model and used to make the simulation model more accurate. In the method according to the application, the simulation model is updated by the computing device on the basis of the product target specifications and the measurement results.

[0032] The results of the measurements can also be fed back to the precursor production. Thus, it is preferred that updated precursor production settings are generated by the computing device on the basis of the product data. Preferably, the updated precursor production settings are generated by the computing device on the basis of the product target specifications and the measurement results. The updated precursor production settings are in particular configured to be applied to the precursor production process.

[0033] The method of the application can also be used for experimental design. Thus, a preferred embodiment of the method is characterized in that a process setting is determined in order to improve the accuracy of the simulation model on the basis of the product target specifications and the product data. Such a determination of a process setting can in addition or alternatively be based on the measurement results. In these cases, the purpose of the process setting and the product produced according to the product settings is not to make the product meet certain specifications, but to have a product whose analysis can be particularly useful for updating the simulation model. For example, it can be determined that the simulation model is not accurate enough in modeling the flow behavior in a certain temperature range. In this case, it can be advantageous to set the temperature in the process setting within this temperature range. On the basis of measurements on products produced with those settings, the simulation model can be updated and thereby improved for this temperature range.

[0034] In principle, the simulation model can be updated on the basis of any data from an injection molding process. Thus, such data is not limited to being based on products produced according to process settings generated by the simulation model. In other words, if a third-party product is produced by a different injection molding device, data measured from this product can also be used to update the simulation model together with data that was the basis for this production process. Such data is referred to as external data in the following. Thus, a further preferred embodiment of the application is characterized in that the simulation model is updated before the computer simulation on the basis of external data of an external injection molding process for an external product from an external precursor charge of an external precursor material on the basis of external process settings applied to an external injection molding device provided to the computer system. In each case, the prefix "external" indicates that the entity in question is external to the present injection molding device. It is further preferred that the external data comprises external process settings and external process conditions of the external injection molding device.

[0035] According to a preferred embodiment of the method, the external data comprises external product data that has been determined by measuring an external product. Preferably, the external data comprises external product target specifications that specify properties of the external product. It is further possible that the external data comprises external measurement data that describes the conformity of the external product with the external product target specifications.

[0036] The system according to the application serves to improve an injection molding process and comprises an injection molding device for producing a product from a precursor charge of a precursor material by an injection molding process based on process settings applied to the injection molding device. In the system according to the application, the precursor charge has been produced by a precursor production process described by precursor production parameters.

[0037] The system according to the application further comprises a computing device for determining the applied process settings prior to the injection molding process by performing a computer simulation of the injection molding process based on a simulation model, based on the precursor production parameters and based on given process conditions of the injection molding process, the given process conditions comprising a shape of a mold.

[0038] In the system according to the application, the computer simulation is further based on the precursor production parameters, the product is measured by a product measurement device for determining product data, and a quality measure is applied to the product data for determining a measure result, the measure result serving to describe a conformity of the product to a product target specification specifying product properties.

[0039] Further, in the system according to the application, the simulation model (7) is updated by the computing device (6) based on the product data (11), the product target specification (10) and the measure result.

[0040] Preferred embodiments, features and advantages of the system according to the application correspond to preferred embodiments, features and advantages of the method according to the application, and vice versa.

[0041] Further advantageous and preferred features are discussed in the following description with respect to the figures. In the following, the figures are shown in:

[0042] Figure 1 is a schematic diagram of an embodiment of the system according to the application for performing the method according to the application, and

[0043] Figure 2 is a schematic diagram of a system according to the application for Figure 1 additional aspects of the system of

[0044] Figure 1The system according to the embodiment of the application shown in the middle relates to an injection molding process for producing a product 1, which is accordingly an injection molded product, and here a polyurethane product. The system described comprises an injection molding device 2 at which the injection molding process is performed to produce the derived physical product 1. In the injection molding process, a precursor charge 3 of precursor material, which here is a liquid charge and comprises isocyanate and polyol, is injected into a mold 4 of the injection molding device 2. In particular, the precursor charge 3 comprises isocyanate and polyol as respective sub-charges. The injection molding process is based on and determined by process settings 5, which are applied and thus input into the injection molding device 2.

[0045] The precursor charge 3, in turn, is produced at a precursor production facility 24, which is remote and thus separate from an injection molding facility 25 having the injection molding device 2. Thus, the precursor charge 3 is transported to the injection molding facility 25 prior to the injection molding process. At the precursor production facility 24, a precursor production machine 27 of the precursor production facility 24 is used to produce the precursor charge 3 from a plurality of starting materials 26. Of these starting materials 26, only a first starting material 26 is shown to be aniline and a second starting material 26 is formaldehyde. In particular, these are starting materials 26 for producing the isocyanate of the precursor charge 3.

[0046] The production of the precursor charge 3 at the precursor production facility 24 is described by precursor production parameters 21. These precursor production parameters 21 comprise on the one hand precursor production settings 23, which are set and applied to the precursor production process. Thus, the precursor production settings 23 are user-set or at least user-settable. The precursor production parameters 21 comprise on the other hand precursor process variables 22, which are measured from the precursor production process. Unlike the precursor production settings 23, the precursor process variables 22 represent an output rather than an input of the precursor production process.

[0047] Furthermore, starting material parameters 28 are measured from the starting materials 26. Furthermore, precursor product parameters 29 are measured from the precursor charge 3. In this way, comprehensive information about the precursor charge 3, the starting materials 26 on which it is based, and its production process is available prior to the injection molding process.

[0048] These process settings 5 are determined in advance by a computer simulation of the injection molding process. The computer simulation is performed on a computing device 6 of the system, which in the present case is a desktop computer, but can also be a cloud computing system. The computer simulation relies on a simulation model 7 stored in the computing device 6. The simulation model is a software module that replicates the physical process of the injection molding process. The computer simulation relies on given process conditions 8 of the injection molding process, which are input into the computing device 8.

[0049] These given process conditions 8 comprise basic technical information about the injection molding device 2. They also comprise environmental conditions of the injection molding process measured by sensor instruments 9 of the injection molding device, which are here thermometers. In order to provide information about the geometry of the mold 4, which in the present example is a new mold 4 that has not been used for an injection molding process before, the given process conditions 8 comprise a data representation derived from a computer-aided design for the mold 4. This data representation is the data representation used for producing the mold 4, thereby ensuring the accuracy of the actual mold 4 utilized with the injection molding device 2.

[0050] The computer simulation also relies on the precursor production parameters 21, the starting material parameters 28 and the precursor product parameters 29 described above. In this way, the computer simulation can also take into account comprehensive information about the specific precursor filler 3 to be used for the injection molding process in simulating the injection molding process.

[0051] In the computer simulation, the flow of the injected precursor filler 3 through the mold 4 is simulated numerically, for example by the finite element method. The fluid dynamics of the process are simulated comprehensively taking into account the geometry of the mold 4 including the influence of the inner surface of the mold 4. The computer simulation 4 also takes into account temperature, pressure and other factors influencing, for example, the viscosity and other physical properties of the injected precursor filler during the injection molding. Other given process conditions are taken into account equally in the computer simulation. The computer simulation of the process comprises several individual simulation runs, wherein each simulation has different underlying simulation parameters.

[0052] In the present case, a product target specification 10 is also provided to the computing device 6. The product target specification 10 specifies certain values to be met for some physical properties of the product 1. This product target specification 10 is used in the computer simulation. In particular, the computer simulation performs several simulation runs in order to achieve a process setting 5 that is assumed to result in a product 1 meeting the product target specification 10 according to the given process conditions 8, in particular the shape of the mold 4 defined by the data representation.

[0053] After the product 1 has been produced from the computer simulation according to the process setting 5, the product 1 is measured by a product measurement device 12, which in the present case is a high-resolution camera and analysis equipment. The product measurement device 12 generates product data 11 from the measurement, which is provided to the computing device 6.

[0054] In the computing device, a quality measure relating to the product target specification 10 is first applied to the product data 11, which results in a measure quantifying the conformity of the product 1 with the product target specification. Depending on the measure, the finished product 1 can be considered satisfactory or not.

[0055] Secondly, based on the product data 11, the simulation model 7 can be updated. If the product data 11 substantially corresponds to what is expected from the results of the computer simulation, then little or no change to the simulation model 7 can be appropriate. On the other hand, if a significant deviation of the product data 11 from the computer simulation prediction is observed, then a more significant change to the simulation model 7 can be in order. In any case, the updated simulation model 7 can be used for the next determination of the process settings 5.

[0056] Further, based on the product data 11, also updated precursor production settings 30 are generated. These updated precursor production settings 30 are to obtain a more suitable precursor charge 3 from the results measured from the product 1. The updated precursor production settings 30 are provided to the precursor production process for the subsequent production of further precursor charges 3.

[0057] Figure 1 The system and method of the invention in

[0001] can also be used for experimental design. To this end, instead of aiming at making the product 1 comply with the product target specification 10, but instead aiming at improving the simulation model 7, the process settings 5 are determined by the computer simulation executed by the computing device 6 and based on the simulation model 7 and based on given process conditions 8, such as the shape of the mold 4. In this case, the process settings 5 are determined such that, based on the analysis of the product data 11 of the product 1 produced at that time, the simulation model 7 can be improved in the areas where improvement is needed.

[0058] However, the simulation model 7 can also be improved by external data 13 obtained from an injection molding process that does not in any way rely on the process settings 5 determined by relying on the simulation model 7. The prefix “external” here indicates that the entity immediately following is not a feature of the inventive system itself, but instead comes from a distinguished and thus different system. This different system can be identical or similar in construction and operation to the inventive system according to

[0001] . Figure 1

[0059] Because such external data 13 still provides data of an effective observation, it can also be used to improve the accuracy of the simulation model 7. With reference to

[0001] , the simulation model 7 can be updated based on the external data 13. Figure 2 The case is explained where only the computing device 6 and the simulation model 7 of the system of

[0001] are shown for reasons of more clarity. Figure 1

[0060] As shown in

[0001] , the external product 14 is produced from the external precursor charge 15 in an external injection molding process by the external injection molding device 17 based on the external process settings 16 applied to the external injection molding device 17.

[0061] As shown in

[0001] , the external product 14 is produced from the external precursor charge 15 in an external injection molding process by the external injection molding device 17 based on the external process settings 16 applied to the external injection molding device 17. Figure 2 ​​​​As shown in the middle, the external data 13 comprises external process settings 16 and external process conditions 18, which are similar to the process settings 5 and the given process conditions 8, respectively, with respect to the external injection molding device 17. The external data 13 further comprises external product data 19 determined by a measurement of the external product 14 by an external product measurement device 20.

Claims

1. A method for improving injection molding processing, wherein an injection molding apparatus (2) produces a product (1) from a precursor filler (3) of a precursor material by injection molding processing based on processing settings (5) applied to the injection molding apparatus (2), wherein the injection molding processing includes injecting the precursor filler (3) into a mold (4) of the injection molding apparatus (2), wherein the precursor filler (3) is produced by a precursor production process described by precursor production parameters (21), wherein the applied processing settings (5) are determined prior to the injection molding processing by a computer simulation of the injection molding process executed by a computing device (6), the computer simulation being based on a simulation model (7) of the injection molding process and given processing conditions (8), the given processing conditions (8) including the shape of the mold (4), characterized in that, The computer simulation is also based on the precursor production parameters (21), and the product (1) is measured by the product measuring device (12) to determine the product data (11), and quality metrics are applied to the product data (11) to determine the following measurement results: the measurement results are used to describe the degree of conformity of the product (1) with the product target specification (10) that specifies the product properties, and the simulation model (7) is updated by the computing device (6) based on the product data (11), the product target specification (10) and the measurement results.

2. The method according to claim 1, characterized in that, Injection molding processes include thermoplastic processing.

3. The method according to claim 1, characterized in that, Injection molding process includes reaction processing.

4. The method according to claim 3, characterized in that, Product (1) is a polyurethane product, and the precursor filler (3) includes isocyanate and polyol for forming the polyurethane product.

5. The method according to any one of claims 1 to 4, characterized in that, Computer simulation includes simulating the flow of the injected precursor filler (3) through the mold (4) based on the shape of the mold.

6. The method according to claim 5, characterized in that, The flow of the injected precursor packing (3) through the mold (4) is simulated, including the fluid dynamics of the flow state of the precursor packing (3).

7. The method according to claim 6, characterized in that, The flow of the injected precursor packing (3) through the mold (4) was simulated, including the effect of the surface of the mold (4) on the fluid dynamics of the flow state of the precursor packing (3).

8. The method according to claim 5, characterized in that, The given processing conditions (8) include the material composition of the precursor filler (3), and the simulated flow of the injected precursor filler (3) through the mold (4) is based on the material composition of the precursor filler (3).

9. The method according to any one of claims 1 to 3, characterized in that, The given processing conditions (8) include the environmental conditions for injection molding, which are measured by the sensor instruments (9) of the injection molding device (2).

10. The method according to any one of claims 1 to 3, characterized in that, The given processing conditions (8) include the fixed characteristics of the injection molding device (2).

11. The method according to any one of claims 1 to 3, characterized in that, The computer simulation is based on a data representation for computer-aided design, which describes the geometry of the physical components of the injection molding apparatus (2). The given processing conditions (8) include the data representation, which is configured to enable the production of the physical components by the component production apparatus.

12. The method according to claim 11, characterized in that, The physical component is the mold (4).

13. The method according to any one of claims 1 to 3, characterized in that, Computer simulation includes numerical simulation of injection molding processes.

14. The method according to any one of claims 1 to 3, characterized in that: The product target specification (10) is provided to the computing device (6); the computer simulation is based on applying the product target specification (10) to the simulation model (7); and the processing settings are determined to make the product (1) conform to the product target specification (10).

15. The method according to any one of claims 1 to 3, characterized in that, Based on the product target specifications (10) and product data (11), the processing settings are determined in order to improve the accuracy of the simulation model (7).

16. The method according to any one of claims 1 to 3, characterized in that, Based on the measurement results, the processing settings are determined in order to improve the accuracy of the simulation model (7).

17. The method according to any one of claims 1 to 3, characterized in that, The simulation model (7) is updated before computer simulation based on external data (13) for external injection molding processing of external product (14), external product (14) is external precursor filler (15) from external precursor material based on external processing settings (16), external processing settings (16) are applied to external injection molding device (17) and provided to computing device (6).

18. The method according to claim 17, characterized in that, The external data (13) includes the external processing settings (16) and external processing conditions (18) of the external injection molding device (17).

19. The method according to claim 17, characterized in that, External data (13) includes external product data (19), which has been determined by measuring external products (14).

20. The method according to claim 17, characterized in that, External data (13) includes external product target specifications that define the nature of external products (14).

21. The method according to claim 17, characterized in that, External data (13) includes external metrics that describe the degree of conformity between the external product (14) and the target specifications of the external product.

22. A system for improving injection molding processing, comprising: an injection molding apparatus (2) for producing a product (1) from a precursor filler (3) of a precursor material by injection molding processing based on a processing setting (5) applied to the injection molding apparatus (2), wherein the precursor filler (3) has been produced by a precursor production process described by precursor production parameters (21); and a computing device (6) for determining the applied processing setting (5) prior to injection molding processing by performing a computer simulation of the injection molding process, the computer simulation being based on a simulation model (7) of the injection molding process and given processing conditions (8), the given processing conditions (8) including the shape of a mold (4), characterized in that, The computer simulation is also based on the precursor production parameters (21), and the product (1) is measured by the product measuring device (12) to determine the product data (11), and quality metrics are applied to the product data (11) to determine the following measurement results: the measurement results are used to describe the degree of conformity of the product (1) with the product target specification (10) that specifies the product properties, and the simulation model (7) is updated by the computing device (6) based on the product data (11), the product target specification (10) and the measurement results.

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