This content is not included in your SAE MOBILUS subscription, or you are not logged in.
Multi-Objective Optimization of Sheet Metal-Polymer Hybrids Manufactured by the Integrated Process of Deep Drawing-Back Injection Molding
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 14, 2020 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
Lightweight constructions can no longer be achieved solely through material substitution. To stay competitive, design parameters and manufacturing technologies should be taken into consideration as well. The integrated process of Deep Drawing-Back Injection Molding (DDBIM) is such an advanced process in which the sheet metal blank is first deformed by tool movement and then calibrated to the shape of the cavity using polymer melt pressure during the injection process. Therefore, the traditional processes of sheet metal forming, and injection molding are combined into one step operation, thus reducing the process steps and required machinery. Even though the process has its own challenges, the best combination of weight, performance, cost, and quality can be achieved by defining a multi-objective optimization problem with respect to the influencing design parameters. This study aims to optimize the various parameters of the sheet metal-polymer structure using Taguchi-based Grey optimization. A system of orthogonal arrays is used as the design of experiment (DOE) in order to evenly distribute the design variables in the design space. Moreover, S/N ratio studies are employed to determine the parameters that have a higher impact on the objective functions. The profiles suggested by DOE are then simulated using ABAQUS, and the objective functions are reported for the optimization step. Finally, the results of the simulation step along with the corresponding design variables are used for the multi-objective optimization process. The optimization results suggest a remarkable improvement in the objective functions. The suggested optimal profile not only held high values of energy, stiffness, and maximum load, but also resulted in 11% and 14% reduction in mass and cost, respectively.
CitationFarahani, S., Malmir, F., Aggarwal, D., and Pilla, S., "Multi-Objective Optimization of Sheet Metal-Polymer Hybrids Manufactured by the Integrated Process of Deep Drawing-Back Injection Molding," SAE Technical Paper 2020-01-0622, 2020, https://doi.org/10.4271/2020-01-0622.
Data Sets - Support Documents
|[Unnamed Dataset 1]|
|[Unnamed Dataset 2]|
|[Unnamed Dataset 3]|
|[Unnamed Dataset 4]|
|[Unnamed Dataset 5]|
|[Unnamed Dataset 6]|
|[Unnamed Dataset 7]|
- Klein, G. , “Lanxess: Continued Growth,” Kunststoffe Int. 11:16-18, 2008.
- Amancio Filho, S.T. and Blaga, L.-A. , “Joining of Polymer-Metal Hybrid Structures : Principles and Applications,” 2018.
- Brecher, C. et al. , “Integrative Production Technology for High-Wage Countries,”. In: Integrative Production Technology for High-Wage Countries. (Berlin Heidelberg, Springer, 2012), 17-76.
- Farahani, S., Arezoodar, A.F., Dariani, B.M., and Pilla, S. , “An Analytical Model for Nonhydrostatic Sheet Metal Bulging Process by Means of Polymer Melt Pressure,” J. Manuf. Sci. Eng. 140(9):091010, 2018.
- Grzancic, G., Löbbe, C., Ben Khalifa, N., and Tekkaya, A.E. , “Analytical Prediction of Wall Thickness Reduction and Forming Forces during the Radial Indentation Process in Incremental Profile Forming,” J. Mater. Process. Technol. 267(December 2018):68-79, 2019.
- Kazan, H., Farahani, S., and Pilla, S. , “Feasibility Study for Manufacturing CF/Epoxy - Thermoplastic Hybrid Structures in a Single Operation,” Procedia Manuf. 33:232-239, Jan. 2019.
- Wargnier, H., Kromm, F.X., Danis, M., and Brechet, Y. , “Proposal for a Multi-Material Design Procedure,” Mater. Des. 56:44-49, 2014.
- Hopmann, C., Wurzbacher, S., Tekkaya, E., and Joghan, H.D. , “Deep-Drawing and Backmolding Process for Plastic-Magnesium Hybrids,” Light. Des. Worldw. 11(3):58-63, Jun. 2018.
- Farahani, S. , “Polymer Injection Forming: A New Age Technology for Manufacturing Polymer-Metal Hybrids,” Clemson University, 2018.
- Farahani, S., Yerra, V.A., and Pilla, S. , “Analysis of a Hybrid Process for Manufacturing Sheet Metal-Polymer Structures Using a Conceptual Tool Design and an Analytical-Numerical Modelling,” J. Mater. Process. Technol. 279:116533, May 2020.
- Shojaeefard, M.H., Khalkhali, A., Khakshournia, S.H., and Malmir, F. , “Static and Modal Analysis of Parabolic-Boundary Functionalized Carbon Nanotube-Reinforced Composite Plates Using FEM,” Int. J. Nano Dimens. 5(2):187-196, 2014.
- Yang, W.H. and Tarng, Y.S. , “Design Optimization of Cutting Parameters for Turning Operations Based on the Taguchi Method,” J. Mater. Process. Technol. 84(1-3):122-129, 1998.
- Barnes, R.F. and Meyer, P.L. , “Introductory Probability and Statistical Applications,” Am. Math. Mon. 80(9):1075, Nov. 1973.
- Jeyaprakash, N., Yang, C.-H., and Raj Kumar, D. , “Machinability Study on CFRP Composite Using Taguchi Based Grey Relational Analysis,” in Mater. Today Proc., Sep. 2019.
- Palanisamy, A. and Selvaraj, T. , “Optimization of Machining Parameters for Dry Turning of Incoloy 800H Using Taguchi - Based Grey Relational Analysis,” Materials Today: Proceedings 5(2):7708-7715, 2018.
- Aslantas, K., Ekici, E., and Çiçek, A. , “Optimization of Process Parameters for Micro Milling of Ti-6Al-4V Alloy Using Taguchi-Based Gray Relational Analysis,” Meas. J. Int. Meas. Confed. 128:419-427, Nov. 2018.
- “Raw Materials Real Time Price List,” [Online], available at https://plasticker.de/preise/pms_en.php?show=ok&make=ok&aog=A&kat=Mahlgut, accessed Nov. 18, 2019.
- “Buy Aluminum Sheet Online,” [Online], available at https://www.onlinemetals.com/en/buy/aluminum-sheet, accessed Nov. 18, 2019.
- Eshtayeh, M. and Hrairi, M. , “Multi Objective Optimization of Clinching Joints Quality Using Grey-Based Taguchi Method,” Int. J. Adv. Manuf. Technol. 87(1-4):233-249, Oct. 2016.