SOFTWARE IMPLEMENTED METHOD TO PROCESS RESULTS OF A SIMULATION CREATED WITH FINITE ELEMENTS ANALYSIS SOFTWARE

Abstract

A software-implemented method is described for processing results of a simulation carried out with finite element analysis software, the software being adapted to simulate a filling process of a molded piece in a mold by a molten material injected into it, wherein: results are taken from a file of simulation results, a computer Database containing technical specifications of injection molding machines is accessed and a search is performed in the Database comparing the results read from the file with technical specifications stored in the Database and associated with each press to determine whether or not one or each press of the Database is able to perform the process.

Claims

1. Software-implemented method for processing results of a simulation carried out with finite element analysis software, the software being adapted to simulate a filling process of a molded piece in a mold by a molten material injected into it, wherein: results are taken from a file of simulation results, a computer Database containing technical specifications of injection molding machines is accessed and a search is performed in the Database comparing the results read from the file with technical specifications stored in the Database and associated with each press to determine whether or not one or each press of the Database is able to perform the process.

2. Method according to claim 1, wherein a search is carried out in order to generate a first group comprising the presses of the Database unable to perform the process, and/or a second group comprising the presses of the Database able to perform the process.

3. Method according to claim 1, with the step of finding which presses of the Database are and/or are not able to perform the process, and such presses are presented to a user.

4. Method according to claim 1, wherein the search is performed verifying whether the data found in the Database of presses fulfill an order relationship with respect to a corresponding simulation data.

5. Method according to claim 4, wherein for the order relationship it is checked whether the data found in the Database are: greater or less than a % of the corresponding simulation data and/or greater or less than the corresponding simulation data multiplied by a coefficient.

6. Method according to claim 1, wherein the search is performed setting a threshold for the data found in the Database of presses with respect to a corresponding simulation data.

7. Method according to claim 1, wherein a set of set-up parameters is generated for a press as a function of: the data contained in the simulation file and data expressing press technical features associated with a compatible press found during the Database search.

8. Method according to claim 1, wherein the set of parameters is calculated by means of corrective coefficients and/or processing applied to the data contained in the simulation file.

9. System comprising: a finite elements analysis software, adapted to simulate a mold filling process by a molten material injected thereinto and adapted to generate a file of simulation results: a computer Database containing technical specifications of injection presses, a processor programmed for taking data from the simulation file, accessing the computer Database and comparing the data taken/extracted from the file with technical specifications in the Database to establish whether or not a press of the Database is able to practice the process.

10. System comprising: a computer Database containing technical specifications of injection presses, a processor programmed for taking data from a simulation file generated by a finite element analysis software, adapted to simulate a mold filling process by a molten material injected into it and adapted to generate a file of simulation results, accessing the computer Database and comparing the data taken/extracted from the file with technical specifications in the Database to determine whether or not a press of the Database is able to carry out the process.

11. Method according to 2, with the step of finding which presses of the Database are and/or are not able to perform the process, and such presses are presented to a user.

Description

[0066] The advantages of the invention will be even clearer from the following description of a preferred device, in which reference is made to the attached drawing in which

[0067] FIG. 1 shows a schematic view of a processing system for a Database of presses.

[0068] In the FIGURES: equal numerical references indicate equal elements, and the parts are described as in use.

[0069] The method applies to simulation results related to the filling of a piece to be molded with a machine (press) or an injection molding center. The simulation results are generated by a simulation software 10, which saves them and outputs them in a file 12.

[0070] The machine or press is generally equipped with a mold with one or more hot runners. A control unit, provided with intelligence, drives the various members of the molding machine during the molding phases. The control unit is programmed with configuration parameters P to perform the molding operations, and the parameters are deduced from the simulation results.

[0071] Via a device 50 (e.g. a mobile phone or a smartphone or a PC) an operator reads the file 12. On the device 50 e.g. there is loaded and runs a program (or App) to read the file 12 and extract simulation data from it, such as the maximum injection pressure, which characterize the simulated molding process.

[0072] With this data a data packet is transmitted by the device 50, e.g. via GSM or Internet, to a remote computer application 60, e.g. on a Server, via a wireless or wired signal 52. The computer application 60 may also run in the device 50.

[0073] The signal 52 is received by a receiver stage 64 and processed by a microprocessor stage 62 (e.g. a PC or Server), which can access a Database 66 of machines or presses containing the operating specifications of the machine, in particular the maximum or minimum values for the operating variables, such as the maximum injection pressure.

[0074] The microprocessor stage 62 uses the received data to search (or it processes them first and then looks for the results) in the Database 66 by means of logical comparisons which machine or press is suitable for carrying out the process as simulated.

[0075] If there is a suitable machine in the Database 66, the microprocessor stage 62 continues by extracting from the Database 66 an identifier data relating to that machine and saves it in a group of suitable presses (the aforementioned second group).

[0076] At the end of the search, the microprocessor stage 62 generates a feedback signal 80 to be sent to the device 50 containing the data relating to the second group (including the parameters of each press), in order to make the suitable presses available on the device 50 and inform the user, e.g. with an SMS or a graphic web page or by driving a display.

[0077] Note that the device 50 is only a preferred example of interface for interacting with the Database 66. The user could use an equivalent device, e.g. portable as a tablet, a terminal or a dedicated device. Or the user could use a program that runs on the application 60 for launching the search in the Database 66 and populate the second group.

[0078] The application 60 is preferably structured as a website, accessible via the Internet, but not necessarily. Preferably, but without limitation, the application 60 is accessible via a smartphone APP.

[0079] The application 60 could for example be embedded into the simulation software or in the cloud or run in a local memory of the device 50.

[0080] For the feedback signal 80 all the options described for the signal 52 are possible.

[0081] As can be seen, the system of FIG. 1 allows each time a quick browsing of the Database 66 as a function of the simulation results 12. The knowledge of which presses are compatible or not, and the parameters of each one, simplifies a lot the programming work on the press, and avoids wasted resources on unsuitable presses. That is to say that the system avoids performing molding tests on unsuitable presses and/or avoids performing subsequent simulation or post-processing calculations, which lead to data relating to unsuitable presses.

[0082] There is a clear and evident cut in the set-up operations (containment of the consequent costs), in jargon called “mold test”, carried out necessarily manually thanks to the experience of the operator.

[0083] As an example of compatibility checks to be carried out to guarantee the suitability of a press, refer to the following.

[0084] 1) Check of the Press Tonnage

[0085] From the simulation file 12 the parameter Fs (maximum closure force estimated by the simulation) is detected or extracted/processed. From the Database 66 for each press the parameter Fn (nominal closing force of the press) is read or obtained. In order for the press to be considered suitable, and inserted into the second group (suitable presses), it must be Fn>c1.Math.Fs,

[0086] where c1 is a safety factor, e.g. around 1.2.

[0087] 2) Verification on Maximum Injection Pressure

[0088] From the simulation file 12, Pmax (maximum injection pressure estimated by the simulation) is read or obtained or extracted/processed. From the Database 66 the parameter Pn (maximum nominal injection pressure) is detected or extracted/processed.

[0089] In order for the press to be considered suitable, and inserted into the second group, it must be Pn>c2.Math.Pmax,

[0090] where c2 is a safety factor, e.g. around 1.2.

[0091] 3) Verification on Maximum Injection Volume

[0092] From the simulation file 12 the V_feed parameter is detected or extracted/processed (estimated dosage volume).

[0093] From the Database 66 the parameter Vn (nominal maximum injection volume) is detected or extracted/processed. In order for the press to be deemed suitable, and inserted into the second group, it must be Vn>c3.Math.V_feed,

[0094] where c3 is a security factor, e.g. about 1.3.

[0095] Note that the coefficients c1, c2, c3 allow discarding the presses that only nominally meet the numerical requirements of the file 12, but which in practice would give unsatisfactory performance. Otherwise in the search inside the Database 66 a confidence threshold or range can be set to select only the presses that abundantly meet the numerical requirements of the file 12.

[0096] A preferred variant of the invention envisages to further exploit the search results in the Database 66 to edit the results 12 optimizing them to calculate the configuration parameters P of a suitable press identified in the Database 66.

[0097] For this purpose, the user can select, through an interface, one of the presses belonging to the second group (or in any case a press found suitable). From the Database 66 (or other connected Database) technical specifications or functional or set-up parameters of the selected press are extracted, which describe construction and functional characteristics of the press.

[0098] With the extracted data, the simulation results of the file 12 are processed to obtain a set of parameters P potentially already suitable for input (manually or automatically) in the press control unit as set-up data.

[0099] This processing may be performed on the same device 50.

[0100] Below is an example of post-processing performed on the results in the file 12, i.e. the conversion of the injection speed profile.

[0101] The injection speed in the simulator is usually defined through a multi-step profile of a % flow rate of injected material as a function of the % injected volume, through the variables

[0102] Xaxis=the % injected volume [%] and

[0103] Yaxis=flow rate of injected material [%] with respect to the maximum flow rate,

[0104] For a press operator it is almost impossible to use an injection profile so defined, since he will have to define a multistep injection profile by setting the screw speed (or flow rate cm.sup.3/s) as a function of the position of the injection screw (or cylinder volume).

[0105] Consider as an example the 3-step profile defined by the operator:

[0106] 1st step: from 130 mm (dosing position) to 100 mm with a 5 mm/s speed;

[0107] 2nd step: from 100 to 40 mm with a 60 mm/s speed;

[0108] 3rd step: from 40 mm to the switching position (25 mm) with 30 mm/s.

[0109] Therefore, for the press control unit, the configuration parameters

[0110] Xaxis=screw positions [mm] or corresponding cylinder volume [cm.sup.3], and

[0111] Yaxis=screw speed [mm/s] or volumetric flow rate [cm.sup.3/s]

[0112] need to be defined,

[0113] For each step of the injection profile, the conversion is carried out as follows.

[0114] For the conversion relative to Xaxis, from % injected volume to screw position: from the file 12 the data are taken:

[0115] V_cavity (volume of the piece cavity (=volume of the piece));

[0116] y=V_v/p/V_cavity=0.95-0.98 (ratio between the filled volume of the piece at the switching time and the volume of the overall piece);

[0117] %: injected volume i: % injected volume at step i of the simulation profile.

[0118] So, at the i-th step, one has:

Xi=X_Feed−(% Injected Volume i/y)*(X_Feed−X_v/p),

and

Vi=Xi*A

[0119] where

[0120] X_feed: dosage position,

[0121] X_v/p: previously determined switching position,

[0122] Xi: screw position corresponding to %, Injected volume i

[0123] Vi: cylinder volume corresponding to Xi,

[0124] A: cylinder area.

[0125] For the conversion on Yaxis, from % flow rate of material injected at screw speed [mm/s]:

[0126] from the file 12 we take the data

[0127] FR_max (maximum flow rate [cm.sup.3/s]), and

[0128] Flow rate i % (percentage of the maximum flow rate injected in step i of the profile).

[0129] Then, in the i-th step, you have:

Flow rate i[cm.sup.3/s]=(Flow rate I %/100)*FR_max

Velocity i=Flow rate i/A

[0130] where

[0131] A=(π*D{circumflex over ( )}2)/4, the area of the cylinder.

[0132] The method is described with reference to a molding machine for injection of plastic material but it can also be replicated in the same way in presses used for the processing of metallic materials, in all types of presses.

[0133] The defined final molding data/parameters can be easily and quickly shared in different molding sites located in different areas of the world, perfectly replicating the working conditions, even in the absence of an expert operator.