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Injection moulding simulation results as an input to the injection moulding process
Journal of Materials Processing Technology 130–131 (2002) 310–314
Injection moulding simulation results as an input to the injection moulding process B. Nardina,*, K. Kuzmana,b, Z. Kampusb a
CAE Department, TECOS, Slovenian Tool and Die Development Centre, Mariborska 2, 3000 Celje, Slovenia b Faculty of Mechanical Engineering, Department of Manufacturing Technology and Systems, University of Ljubljana, Askrceva 6, 1000 Ljubljana, Slovenia
Abstract In the presented research work the authors tried to develop the software which will suit all the needs of the injection moulding when optimising the part-mould-technology system. The simulation results consist of geometrical and technological data. Geometrical data are useful for both: the part as well as the mould designers, because technological data help the moulders to understand the process parameters. On the basis of the simulation results, the part designers can optimise the geometry of the part and the mould designers can optimise the running and the cooling system of the mould. In this way the optimal input values for the technology optimisation can be defined. The paper provides evidence that the program with its open structure suits the needs of the laboratory environment as well as of the real production. # 2002 Elsevier Science B.V. All rights reserved. Keywords: Injection moulding; Technology optimisation; Computer simulation; CAE analysis; Injection moulding machines
1. Introduction Injection moulding technology is used for a variety of different products in almost all branches of industry. The most sophisticated parts can be found in automotive industry, where the quality requirements are among the toughest [2,5]. Injection moulding technology enables a plastic product to be made by means of the injection moulding machine, the mould and defined technology, which is defined in the mould. Simulation programs help the moulders to define the right injection technology and to set up the machine in the shortest possible time [1]. The optimisation process in non-simulation environment takes a lot of precious time before the injection moulding can be started [3]. During the research work the authors developed a program which helps the programmers of the injection moulding machine to transfer simulation data directly to the machine.
2. Presentation of the problem The presented results refer to an industrial problem, which was successfully solved by means of the simulations and the *
Corresponding author. Tel.: þ386-3-4900-921; fax: þ386-3-4264-611. E-mail address: [email protected] (B. Nardin). URL: http://www.tecos.si
program for the transfer of simulation data to the injection moulding machine. The product to be produced was the third braking light for an automotive producer with the code name TEC-LAP32/02. The product is presented in Fig. 4a. The breaking light is made of plastic material PMMA. The most important objective of the research was to bring a flawless product in the shortest possible time to the market, without exceeding the cost limit. The parameters to be considered were a flawless product, optimal runner position, minimal warpage, short injection cycles, low mould costs and the last but not the least optimal product design.
3. Research and experimental work During the research the facilities and equipment from both research institutions were used, performing the injection moulding analysis, developing of the program for the simulation data transfer to the machine and testing of the results on the injection moulding machine. The injection moulding simulation is a common tool for the determination of the injection moulding process in the virtual environment. The total volume of the product is 43.7 cm3 and is meshed with 8092 finite triangular elements. For the purpose of the optimisation, six simulations were performed. Table 1 presents the most important boundary conditions for all of them. Fig. 1 presents the time needed to
0924-0136/02/$ – see front matter # 2002 Elsevier Science B.V. All rights reserved. PII: S 0 9 2 4 - 0 1 3 6 ( 0 2 ) 0 0 7 3 4 - 3
B. Nardin et al. / Journal of Materials Processing Technology 130–131 (2002) 310–314
311
Fig. 1. Time needed for optimisation of the injection moulding.
perform each of the simulations. The total time needed for all optimisation work was 356 min. During the process optimisation, it was concluded, that the mould was designed correctly, the runner system allowed the plastic material to fill the mould in the optimal way, the simulations numbered 1, 2, and 3 were the ones, which enables us to fill the mould entirely and the simulations 4, 5 and 6 were the ones where the mould could not be filled entirely. The results of the filling time are presented in Fig. 2. This is also very suitable because the cycle time can be
reduced in this way too. From the simulations it was evident that the cycle time should be 17.15 s. The simulation gave some interesting results also in the clamp profile, which was obtained by filling phase. It could be used to determine the optimal process conditions. It is clear from Fig. 2, that the optimal results were obtained by the simulations 1 and 2. This is due to the shorter injection time and higher melt temperatures. In all the simulations, where the clamp force falls to zero, the result is a so called short shot Fig. 3.
Fig. 2. Filling times.
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B. Nardin et al. / Journal of Materials Processing Technology 130–131 (2002) 310–314
Fig. 3. Clamp force profile.
After the post-processing of the simulation, the decision about the optimal simulation results was made. The optimal simulation results needed to be transferred to the injection moulding machine. This was done by means of a computer program, which was developed by the authors. It is called DIPSIPOS. This program was laboratory tested on several different products. In the paper only the results on one of such products is presented. For the simulation data transfer to the machine, the simulation result file .txt was used. This file was then compiled to the universal interface language and then inserted in the program DIPSIPOS which enabled the compilation of the universal interface language to the language understandable to a specific machine. The program DIPSIPOS generates the output file with the data like flange temperature, temperatures of the heating units 1, 2, 3 and 4, temperature of the injection nozzle, temperature of the mould and the cooling media, injection speed profile, pressure limitations, needed plastification, Table 1 Boundary conditions Unit
Simulation 1
Mould temperature Melt temperature Flow speed Mould conductivity Ejection temperature No-flow temperature
2
3
4
5
6
8C 70 70 70 70 70 70 8C 215 235 235 235 215 200 mm/s 58 58 31 20 31 58 W/m/8C 0.24 0.24 0.24 0.24 0.24 0.24 8C 95 95 95 95 95 95 8C 184 184 184 184 184 184
contra pressure, packing profile (time, pressure), cooling time and cycle time. With these data, the injection moulding machine can be easily set up and in the operating position in the shortest possible time. One result of the testing is shown in Fig. 4a (simulation 2), since Fig. 4b shows the result of the simulation 6.
4. Conclusions The research work, which was carried out shows, that the co-operation between the industry, research institutions and universities always brings the best results. The results Table 2 Research time results (in min)
Research project description 3D modeling Simulation Analysis of the results Adjustments on the mould (two times)a Transfer time for mould adjustmentsb Data transfer to the machine Optimal injection mouldingc Total time a
New approach
Conventional approach
240 850 356 320 0 0 10 10 1786
0 0 0 0 5760 480 0 1440 7680
Mould must be adjusted two times in average, before it runs properly. The time needed for the transportation of the mould to the mould maker. c Time needed for the optimisation of the process cycle (try and error method). b
B. Nardin et al. / Journal of Materials Processing Technology 130–131 (2002) 310–314
313
Fig. 4. (a) Optimised product (simulation 2); (b) ‘‘short shot’’ of the product (simulation 6).
have a different value for each of the parties involved. They are easily quantified from the industrial point of view. Table 2 presents the summary of the time needed for reaching the optimal solution in the presented project. The results of the project were reached in less than 30 h, and the company was able to start the production of products of high quality. It is hard to estimate the time needed to start the production with the conventional approach because it was not possible to conduct comparative tests in the real industrial environment did not provide a chance for such testing. So the comparison is based primarily on the previous experiences with the introduction of a new product to the production. Normally complex moulds need to be changed twice before they are fully prepared for
the optimal injection moulding. The injection moulding technology can normally be optimised in three shifts, since the worker has to tune 15 different technological parameters. In the case of using the new approach, all this work was done already on the computer in the designing stage of the mould. The optimal solution lays in the multidimensional space, which is hard to define without the proper computer support. Since the development time of a new product is closely linked to the final production costs, the significant reduction of time achieved by the presented approach results also in a significant reduction of the final costs. For further reading see [4].
314
B. Nardin et al. / Journal of Materials Processing Technology 130–131 (2002) 310–314
Acknowledgements The authors are grateful to the Slovenian Ministry of Economy for supporting the researchers during the research work. In addition the authors would like to thank Matjaz Rot and Mojmir Pregel for their valuable contribution in this research project. References [1] P. Kennedy, Flow Analysis of Injection Moulding, Hanser Gardner Verlag, Munich, 1995.
[2] K. Kuzman, B. Nardin, M. Kovacˇ , B. Jurkosˇek, The integration of rapid prototyping and CAE in mould manufacturing, in: Proceedings of the AFDM’99, J. Mater. Process. Technol. 111 (1/3) (2001) 279– 285 (special issue). [3] B. Kecelj, B. Nardin, K. Kuzman, CAx in tool design and manufacturing, V: SANO, Toshio, KAWAI, Kenichi ICEM-2000, Slovenia, September 17–20, 2000, Celje: TECOS 2001, pp. 90–93. [4] S. No¨ ken, A. Altmu¨ ller, O. Auer, Th. Bergs, F.-B. Schenke, F. Spennemann, Chr. Wagner, H. Wirtz, Werkzeug-und FormenbauLo¨ sungen fu¨ r die Industrie Werkzeug-und Formenbau, VDI Berichte 1376, Symposium Aachen, May 1998, 161 pp. ISBN 3-18091376-2. [5] K. Kuzman, Problems and opportunities in slovene toolmaking industry keynote paper, in: Proceedings of the ICIT’99, Part II, TECOS, Celje, Slovenia, p. 1. ISBN 961-90401-4-7.
Injection moulding simulation results as an input to the injection moulding process B. Nardina,*, K. Kuzmana,b, Z. Kampusb a
CAE Department, TECOS, Slovenian Tool and Die Development Centre, Mariborska 2, 3000 Celje, Slovenia b Faculty of Mechanical Engineering, Department of Manufacturing Technology and Systems, University of Ljubljana, Askrceva 6, 1000 Ljubljana, Slovenia
Abstract In the presented research work the authors tried to develop the software which will suit all the needs of the injection moulding when optimising the part-mould-technology system. The simulation results consist of geometrical and technological data. Geometrical data are useful for both: the part as well as the mould designers, because technological data help the moulders to understand the process parameters. On the basis of the simulation results, the part designers can optimise the geometry of the part and the mould designers can optimise the running and the cooling system of the mould. In this way the optimal input values for the technology optimisation can be defined. The paper provides evidence that the program with its open structure suits the needs of the laboratory environment as well as of the real production. # 2002 Elsevier Science B.V. All rights reserved. Keywords: Injection moulding; Technology optimisation; Computer simulation; CAE analysis; Injection moulding machines
1. Introduction Injection moulding technology is used for a variety of different products in almost all branches of industry. The most sophisticated parts can be found in automotive industry, where the quality requirements are among the toughest [2,5]. Injection moulding technology enables a plastic product to be made by means of the injection moulding machine, the mould and defined technology, which is defined in the mould. Simulation programs help the moulders to define the right injection technology and to set up the machine in the shortest possible time [1]. The optimisation process in non-simulation environment takes a lot of precious time before the injection moulding can be started [3]. During the research work the authors developed a program which helps the programmers of the injection moulding machine to transfer simulation data directly to the machine.
2. Presentation of the problem The presented results refer to an industrial problem, which was successfully solved by means of the simulations and the *
Corresponding author. Tel.: þ386-3-4900-921; fax: þ386-3-4264-611. E-mail address: [email protected] (B. Nardin). URL: http://www.tecos.si
program for the transfer of simulation data to the injection moulding machine. The product to be produced was the third braking light for an automotive producer with the code name TEC-LAP32/02. The product is presented in Fig. 4a. The breaking light is made of plastic material PMMA. The most important objective of the research was to bring a flawless product in the shortest possible time to the market, without exceeding the cost limit. The parameters to be considered were a flawless product, optimal runner position, minimal warpage, short injection cycles, low mould costs and the last but not the least optimal product design.
3. Research and experimental work During the research the facilities and equipment from both research institutions were used, performing the injection moulding analysis, developing of the program for the simulation data transfer to the machine and testing of the results on the injection moulding machine. The injection moulding simulation is a common tool for the determination of the injection moulding process in the virtual environment. The total volume of the product is 43.7 cm3 and is meshed with 8092 finite triangular elements. For the purpose of the optimisation, six simulations were performed. Table 1 presents the most important boundary conditions for all of them. Fig. 1 presents the time needed to
0924-0136/02/$ – see front matter # 2002 Elsevier Science B.V. All rights reserved. PII: S 0 9 2 4 - 0 1 3 6 ( 0 2 ) 0 0 7 3 4 - 3
B. Nardin et al. / Journal of Materials Processing Technology 130–131 (2002) 310–314
311
Fig. 1. Time needed for optimisation of the injection moulding.
perform each of the simulations. The total time needed for all optimisation work was 356 min. During the process optimisation, it was concluded, that the mould was designed correctly, the runner system allowed the plastic material to fill the mould in the optimal way, the simulations numbered 1, 2, and 3 were the ones, which enables us to fill the mould entirely and the simulations 4, 5 and 6 were the ones where the mould could not be filled entirely. The results of the filling time are presented in Fig. 2. This is also very suitable because the cycle time can be
reduced in this way too. From the simulations it was evident that the cycle time should be 17.15 s. The simulation gave some interesting results also in the clamp profile, which was obtained by filling phase. It could be used to determine the optimal process conditions. It is clear from Fig. 2, that the optimal results were obtained by the simulations 1 and 2. This is due to the shorter injection time and higher melt temperatures. In all the simulations, where the clamp force falls to zero, the result is a so called short shot Fig. 3.
Fig. 2. Filling times.
312
B. Nardin et al. / Journal of Materials Processing Technology 130–131 (2002) 310–314
Fig. 3. Clamp force profile.
After the post-processing of the simulation, the decision about the optimal simulation results was made. The optimal simulation results needed to be transferred to the injection moulding machine. This was done by means of a computer program, which was developed by the authors. It is called DIPSIPOS. This program was laboratory tested on several different products. In the paper only the results on one of such products is presented. For the simulation data transfer to the machine, the simulation result file .txt was used. This file was then compiled to the universal interface language and then inserted in the program DIPSIPOS which enabled the compilation of the universal interface language to the language understandable to a specific machine. The program DIPSIPOS generates the output file with the data like flange temperature, temperatures of the heating units 1, 2, 3 and 4, temperature of the injection nozzle, temperature of the mould and the cooling media, injection speed profile, pressure limitations, needed plastification, Table 1 Boundary conditions Unit
Simulation 1
Mould temperature Melt temperature Flow speed Mould conductivity Ejection temperature No-flow temperature
2
3
4
5
6
8C 70 70 70 70 70 70 8C 215 235 235 235 215 200 mm/s 58 58 31 20 31 58 W/m/8C 0.24 0.24 0.24 0.24 0.24 0.24 8C 95 95 95 95 95 95 8C 184 184 184 184 184 184
contra pressure, packing profile (time, pressure), cooling time and cycle time. With these data, the injection moulding machine can be easily set up and in the operating position in the shortest possible time. One result of the testing is shown in Fig. 4a (simulation 2), since Fig. 4b shows the result of the simulation 6.
4. Conclusions The research work, which was carried out shows, that the co-operation between the industry, research institutions and universities always brings the best results. The results Table 2 Research time results (in min)
Research project description 3D modeling Simulation Analysis of the results Adjustments on the mould (two times)a Transfer time for mould adjustmentsb Data transfer to the machine Optimal injection mouldingc Total time a
New approach
Conventional approach
240 850 356 320 0 0 10 10 1786
0 0 0 0 5760 480 0 1440 7680
Mould must be adjusted two times in average, before it runs properly. The time needed for the transportation of the mould to the mould maker. c Time needed for the optimisation of the process cycle (try and error method). b
B. Nardin et al. / Journal of Materials Processing Technology 130–131 (2002) 310–314
313
Fig. 4. (a) Optimised product (simulation 2); (b) ‘‘short shot’’ of the product (simulation 6).
have a different value for each of the parties involved. They are easily quantified from the industrial point of view. Table 2 presents the summary of the time needed for reaching the optimal solution in the presented project. The results of the project were reached in less than 30 h, and the company was able to start the production of products of high quality. It is hard to estimate the time needed to start the production with the conventional approach because it was not possible to conduct comparative tests in the real industrial environment did not provide a chance for such testing. So the comparison is based primarily on the previous experiences with the introduction of a new product to the production. Normally complex moulds need to be changed twice before they are fully prepared for
the optimal injection moulding. The injection moulding technology can normally be optimised in three shifts, since the worker has to tune 15 different technological parameters. In the case of using the new approach, all this work was done already on the computer in the designing stage of the mould. The optimal solution lays in the multidimensional space, which is hard to define without the proper computer support. Since the development time of a new product is closely linked to the final production costs, the significant reduction of time achieved by the presented approach results also in a significant reduction of the final costs. For further reading see [4].
314
B. Nardin et al. / Journal of Materials Processing Technology 130–131 (2002) 310–314
Acknowledgements The authors are grateful to the Slovenian Ministry of Economy for supporting the researchers during the research work. In addition the authors would like to thank Matjaz Rot and Mojmir Pregel for their valuable contribution in this research project. References [1] P. Kennedy, Flow Analysis of Injection Moulding, Hanser Gardner Verlag, Munich, 1995.
[2] K. Kuzman, B. Nardin, M. Kovacˇ , B. Jurkosˇek, The integration of rapid prototyping and CAE in mould manufacturing, in: Proceedings of the AFDM’99, J. Mater. Process. Technol. 111 (1/3) (2001) 279– 285 (special issue). [3] B. Kecelj, B. Nardin, K. Kuzman, CAx in tool design and manufacturing, V: SANO, Toshio, KAWAI, Kenichi ICEM-2000, Slovenia, September 17–20, 2000, Celje: TECOS 2001, pp. 90–93. [4] S. No¨ ken, A. Altmu¨ ller, O. Auer, Th. Bergs, F.-B. Schenke, F. Spennemann, Chr. Wagner, H. Wirtz, Werkzeug-und FormenbauLo¨ sungen fu¨ r die Industrie Werkzeug-und Formenbau, VDI Berichte 1376, Symposium Aachen, May 1998, 161 pp. ISBN 3-18091376-2. [5] K. Kuzman, Problems and opportunities in slovene toolmaking industry keynote paper, in: Proceedings of the ICIT’99, Part II, TECOS, Celje, Slovenia, p. 1. ISBN 961-90401-4-7.