The design of injection molding systems for plastic parts relies heavily on experience and intuition. Recently, mold makers have been compelled to shorten lead times, reduce costs and improve process performance due to global competition. This paper presents a framework, based on a Multidisciplinary Design Optimization (MDO) methodology, which tackles the design of an injection mold by integrating the structural, feeding, ejection and heat-exchange sub-systems to achieve significant improvements. To validate it single objective optimization is presented leading to a 42% reduction in cycle time. We also perform multiple objective optimization simultaneously minimizing cycle time, wasted material and pressure drop. Sensitivity analysis shows a large impact of the sprue diameter (>1.5 normalized sensitivity) highlighting the importance of the feeding subsystem on overall quality. The results show substantial improvements resulting in reduced rework and time savings for the entire mold design process.
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Beaumont J, Nagel R et al (2002) Successful injection molding: process, design and simulation. Hanser, Cincinnati
Centimfe (2000) Projecto Delfim—Subprojecto Moldes
Centimfe (2003) Manual do projectista para moldes de injecção de plásticos
Chan WM, Yan L et al (2003) A 3D CAD knowledge-based assisted injection mould design system. Int J Adv Manuf Technol 22:387–395
Chin K-S, Wong TN (1996) Knowledge-based evaluation for the conceptual design development of injection molding parts. Eng Appl Artif Intell 9(4):359–376
Deb K, Pratap A et al (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182–197
Ferreira I, Cabral JA et al (2008) Customer’s satisfaction evaluation of Portuguese mould makers based on the ECSI approach. In: RPD 2008—rapid product development. Oliveira de Azeméis—Portugal
Ferreira I, Cabral JS et al (2007) A new conceptual framework based on the ECSI model to support axiomatic design. In: Virtual and rapid manufacturing. Taylor & Francis, New York
iSIGHT-FD 2.5, Software package, Ver 2.5.5 (2007) Engineous software
Kazmer DO (2007) Injection mold design engineering. Hanser, Cincinnati
Lam YC, Britton GA et al (2004a) Optimisation of gate location with design constraints. Int J Adv Manuf Technol 24:560–566
Lam YC, Zhai LY et al (2004b) An evolutionary approach for cooling system optimization in plastic injection molding. Int J Prod Res 42(10):2047–2061
Lasdon LS, Warren AD et al (1978) Design and testing of a generalized reduced gradient code for nonlinear programming. ACM Trans Math Softw 4:34–50
Lee KS, Lin JC (2006) Design of the runner and gating system parameters for a multi-cavity injection mould using FEM and neural network. Int J Adv Manuf Technol 27:1089–1096
Low MLH (2003) Application of standardization for initial design of plastic injection moulds. Int J Prod Res 41(10):2301–2324
Mehnen J, Micheltisch T et al (2004) Evolutionary optimization of mould temperature control strategies: encoding and solving the multiobjective problem with standard evolution strategy and kit for evolution algorithms. Proc Inst Mech Eng 218(Part B):657–665
Menges G, Walter M et al (2001) How to make injection molds. Hanser, Cincinnati
Mok CK, Chin KS et al (2001) An interactive knowledge-based CAD system for mould design in injection moulding processes. Int J Adv Manuf Technol 17:27–38
Qiao H (2006) A systematic computer-aided approach to cooling system optimal design in plastic injection molding. Int J Mech Sci 48:430–439
Rosato DV, Rosato DV et al (2001) Injection molding handbook. Kluwer, Dordrecht
Shen C-Y, Yu X-R et al (2004) Gate location optimization in injection molding by using modified hill-climbing algorithm. Polym-Plast Technol Eng 43(3):649–659
Sobieski I, Kroo I (1996) Aircraft design using collaborative optimization. In: AIAA 34th aerospace sciences meeting and exhibit. Reno, NV
Sobieski IP, Kroo IM (2000) Collaborative optimization using response surface estimation. AIAA J 38(10):1931–1938
Sobieszczanski-Sobieski J, Agte JS et al (1998) Bi-Level Integrated System Synthesis (BLISS). N. A. a. S. Administration. Hampton, Virginia
Sobieszczanski-Sobieski J, Altus TD et al (2002) Bi-Level Integrated System Synthesis (BLISS) for concurrent and distributed processing. In: 9th AIAA/ISSMO symposium on multidisciplinary analysis and optimization. Atlanta, Georgia, pp 1–11
Vasco J, Capela C et al (2007) Material selection for high performance moulds. In: Improving quality & tool efficiency within injection moulding—SPE meeting, K2007. Dusseldorf Society of Plastic Engineers
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Ferreira, I., de Weck, O., Saraiva, P. et al. Multidisciplinary optimization of injection molding systems. Struct Multidisc Optim 41, 621–635 (2010). https://doi.org/10.1007/s00158-009-0435-8
- Injection mold design
- Global design
- Cycle time