In this study, we developed a method for automatically generating computer-aided design (CAD) models of injection molding dies. The method only required 3D CAD models of products in the Standard Triangulated Language (STL) format as the input information. We also developed a system for automatically generating numerical control (NC) programs by automating the system process planning necessary for machining the injection molding dies. The method generated CAD models of the injection molding dies by dividing the STL files of the products into triangular meshes on a specified split plane. For injection molding dies with several free curved surfaces, we acquired the tool positions of a ball end mill (as approximated by a spherical shape) and flat drill (as approximated by a cylindrical shape) from the geometrical relationships of the triangles constituting the CAD model. We generated a CAD model of an injection molding die using the proposed method with respect to the CAD model of a product shape to verify the validity of the developed system. Then, we machined the product based on the NC programs and tool position. In addition, we injection molded a product with a machined die to mold it into its original product shape.

1. [1] T. Harada, N. Tanaka, and T. Fujitsuka, “Design of an Arc-Core Moving Mechanism for Injection Molding Using a Link and Cam Mechanism,” Int. J. Automation Technol., Vol.15, No.3, pp. 366-374, 2021. https://doi.org/10.20965/ijat.2021.p0366
2. [2] J. C. Park and K. Lee, “Computer Aided Design of a Mold Cavity With Proper Rigging System for Casting Processes: Part 2,” J. of Manufacturing Science and Engineering, Vol.113, Issue 1, 1991. https://doi.org/10.1115/1.2899624
3. [3] H. Koresawa, H. Fukumaru, M. Kojima, J. Iwanaga, H. Narahara, and H. Suzuki, “Design Method for Inner Structure of Injection Mold Fabricated by Metal Laser Sintering,” Int. J. Automation Technol., Vol.6, No.5, pp. 584-590, 2012. https://doi.org/10.20965/ijat.2012.p0584
4. [4] Y. Murata, H. Suzuki, and S. Kashiwagi, “Development of an Injection Mold Capable of Melt Flow Control and Induction Heating and Cooling,” Int. J. Automation Technol., Vol.11, No.6, pp. 985-992, 2017. https://doi.org/10.20965/ijat.2017.p0985
5. [5] A. C. Nee, M. W. Fu, J. Y. H. Fu, K. S. Lee, and Y. F. Zhang, “Determination of Optimal Parting Directions in Plastic Injection Mold Design,” CIRP Annals, Vol.46, Issue 1, pp. 429-432, 1997. https://doi.org/10.1016/S0007-8506(07)60858-0
6. [6] C. Guo, “Modeling and Simulation of Mold and Die Grinding, J. of Manufacturing Science and Engineering,” Vol.134, Issue 4, 2012. https://doi.org/10.1115/1.4006970
7. [7] T. Sawa, “Automating the Mold-Material Grinding Process,” Int. J. Automation Technol., Vol.13, No.6, pp. 722-727, 2019. https://doi.org/10.20965/ijat.2019.p0722
8. [8] H. Koresawa, H. Fujimaru, and H. Narahara, “Improvement in the Permeability Characteristics of Injection Mold Fabricated by Additive Manufacturing and Irradiated by Electron Beams,” Int. J. Automation Technol., Vol.11, No.1, pp. 97-103, 2017. https://doi.org/10.20965/ijat.2017.p0097
9. [9] H. Takizawa, H. Aoyama, and S. C. Won, “Prompt Estimation of Die and Mold Machining Time by AI Without NC Program,” Int. J. Automation Technol., Vol.15, No.3, pp. 350-358, 2021. https://doi.org/10.20965/ijat.2021.p0350
10. [10] M. Hashimoto and K. Nakamoto, “Process planning for die and mold machining based on pattern recognition and deep learning,” J. of Advanced Mechanical Design, Systems, and Manufacturing, Vol.15, No.2, 2021. https://doi.org/10.1299/jamdsm.2021jamdsm0015
11. [11] K. Nakamoto, K. Shirase, H. Wakamatsu, A. Tsumaya, and E. Ara, “Automatic production planning system to achieve flexible direct machining,” JSME Int. J. Series C, Vol.47, No.1, pp. 136-143, 2004. https://doi.org/10.1299/jsmec.47.136
12. [12] L. Wang, M. Holm, and G. Adamson, “Embedding a process plan in function blocks for adaptive machining,” CIRP Annals – Manufacturing Technology, Vol.59, Issue 1, pp. 433-436, 2010. https://doi.org/10.1016/j.cirp.2010.03.144
13. [13] Y. Woo, E. Wang, Y. S. Kim, and H. M. Rho, “A hybrid feature recognizer for machining process planning systems,” CIRP Annals – Manufacturing Technology, Vol.54, Issue 1, pp. 397-400, 2005. https://doi.org/10.1016/S0007-8506(07)60131-0
14. [14] A. Ueno and K. Nakamoto, “Proposal of machining features for CAPP system for multi-tasking machine tools,” Trans. of the JSME, Vol.81, No.825, 2015 (in Japanese). https://doi.org/10.1299/transjsme.15-00108
15. [15] E. Morinaga, M. Yamada, H. Wakamatsu, and E. Arai, “Flexible process planning method for milling,” Int. J. Automation Technol., Vol.5, No.5, pp. 700-707, 2011. https://doi.org/10.20965/ijat.2011.p0700
16. [16] E. Morinaga, T. Hara, H. Joko, H. Wakamatsu, and E. Arai, “Improvement of computational efficiency in flexible computer-aided process planning,” Int. J. Automation Technol., Vol.8, No.3, pp. 396-405, 2014. https://doi.org/10.20965/ijat.2014.p0396
17. [17] H. Sakurai, “Volume decomposition and feature recognition: part 1 – polyhedral objects,” Computer-Aided Design, Vol.27, Issue 11, pp. 833-843, 1995. https://doi.org/10.1016/0010-4485(95)00007-0
18. [18] H. Sakurai and P. Dave, “Volume decomposition and feature recognition, part II- curved objects,” Computer-Aided Design, Vol.28, Issues 6-7, pp. 519-537, 1996. https://doi.org/10.1016/0010-4485(95)00067-4
19. [19] I. Nishida and K. Shirase, “Automated process planning system for end-milling operation by CAD model in STL format,” Int. J. Automation Technol., Vol.15, No.2, pp. 149-157, 2021. https://doi.org/10.20965/ijat.2021.p0149
20. [20] I. Nishida, H. Nakatsuji, and K. Shirase, “Automated tool path generation for roughing using flat drill,” Int. J. Automation Technol., Vol.14, No.6, pp. 1036-1044, 2020. https://doi.org/10.20965/ijat.2020.p1036