Published 2023-09-25
Keywords
- Deep Drawing,
- Metal Forming,
- Forming Simulations,
- Optimization,
- Finite Element Model
How to Cite
Copyright (c) 2023 Top Academic Journal of Engineering and Mathematics
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Abstract
Deep drawing is a widely employed metal forming technique recognized for its ability to produce high-strength, lightweight components with remarkable cost efficiency compared to alternative methods. This article delves into the advantages inherent to deep drawing, including expedited press cycle times, reduced operations necessary to complete a part, and the capacity to fabricate intricate geometries that remain unattainable through alternative manufacturing processes. Presently, forming simulations predominantly follow a trial-and-error approach to formulate a forming process that yields acceptable results. However, as the complexity and scale of data in finite element models escalate, computational time proportionally surges. Hence, the primary objective is to develop an efficient, automated optimization method for the deep drawing process
References
- Bonte M.H.A., van den Boogaard A.H. (2005), A metamodel based optimisation algorithm for metal forming process, International Journal of Forming Processes, Special issue, 1-20, ISSN 12927775.
- Herderich, M. R. (1990), Experimental Determination of the Blankholder Forces Needed for Stretch Draw Die Design, SAE Paper No. 900281, 53-61.
- Hsu, C. W., Ulsoy, A. G., Demeri, M. Y. (2000), An Approach for Modeling Sheet Metal Forming for Process Controller Design, Transactions of ASME, Journal of Manufacturing Science and Engineering, Vol. 122, 717-724.
- Maier C., Epureanu Al., Marinescu V., Paunoiu V., Marin F. B. (2011), A new reduced order technique in metal forming modelling, Proceedings of the International Conference ModTech, 363-366, ISSN: 2066-3919.
- Maier C., Epureanu Al., Marinescu V., Marin F. B. (2010), A new concept of the reduced order modeling in metal forming, Proceedings of the 6th International Conference on Advanced in Dynamical Systems and Control, 133-136, ISSN 1790-5117.
- Maier Catalina, Epureanu Alexandru, Marinescu Vasile, Paunoiu Viorel, Afteni Mitica, Marin Florin Bogdan (2010), Metal forming process control based on reduced order model, Proceedings of ModTech International Conference, 363-366, ISSN 2066-3919.
- Viswanathan V., Kinsey B., Cao J. (2003), Experimental implementation of neural network springback control for sheet metal forming, J. Eng. Materials and Technology, 141-147.