Warpage Analysis of Single and Dual Gates Designed for Injection Moulding Using Response Surface Methodology

Abstract:

This study focuses on the analysis of plastic injection moulding process simulation using Autodesk Moldflow Insight (AMI) software in order to correlate between process parameters as an input and warpage as an output for single and dual gates mould design. Nessei NEX 1000 injection moulding machine and P20 mould material details are incorporated in this study on top of Acrylonitrile Butadiene Styrene (ABS) as a moulded thermoplastic material. Coolant inlet temperature, material melt temperature, packing pressure and packing time are selected as a variable parameter. Design Expert software is obtained as a medium for analysis and optimization of input variables in order to minimize the warpage. RSM method as well as Analysis of Variance (ANOVA) has been applied in this study. The results of ANOVA show that some interactions between factors are significant towards warpage existence, which is coolant inlet temperature, material melt temperature and packing pressure. Furthermore, the model created using RSM can be used for warpage prediction and improvement due to a minimum value of error. From this study, the dual gate is the best solution which able to improve the warpage up to 80% instead of single.

• Periodical: Applied Mechanics and Materials (Volumes 754-755)
• Pages: 775-783
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.754-755.775
• Online since: April 2015
• Authors: S.M. Nasir*, Khairul Azwan Ismail, Z. Shayfull, M.A. Fairuz
• Keywords: Autodesk Moldflow Insight, Design Expert, Plastic Injection Moulding, RSM, Warpage

References

[1] J. Li, D. Li, Z. Guo, and H. Lv, Single gate optimization for plastic injection mold, J. Zhejiang Univ. Sci. A, vol. 8, no. 7, p.1077–1083, Jun. (2007).

DOI: 10.1631/jzus.2007.a1077

[2] F. Yin, H. Mao, L. Hua, W. Guo, and M. Shu, Back Propagation neural network modeling for warpage prediction and optimization of plastic products during injection molding, Mater. Des., vol. 32, no. 4, p.1844–1850, Apr. (2011).

DOI: 10.1016/j.matdes.2010.12.022

[3] Y. Gao and X. Wang, An effective warpage optimization method in injection molding based on the Kriging model, Int. J. Adv. Manuf. Technol., vol. 37, no. 9–10, p.953–960, Jun. (2007).

DOI: 10.1007/s00170-007-1044-6

[4] K. -T. Chiang and F. -P. Chang, Analysis of shrinkage and warpage in an injection-molded part with a thin shell feature using the response surface methodology, Int. J. Adv. Manuf. Technol., vol. 35, no. 5–6, p.468–479, Oct. (2006).

DOI: 10.1007/s00170-006-0739-4

[5] M. -C. Huang and C. -C. Tai, The effective factors in the warpage problem of an injection-molded part with a thin shell feature, J. Mater. Process. Technol., vol. 110, no. 1, p.1–9, Mar. (2001).

DOI: 10.1016/s0924-0136(00)00649-x

[6] T. Erzurumlu and B. Ozcelik, Minimization of warpage and sink index in injection-molded thermoplastic parts using Taguchi optimization method, Mater. Des., vol. 27, no. 10, p.853–861, Jan. (2006).

DOI: 10.1016/j.matdes.2005.03.017

[7] B. Ozcelik and T. Erzurumlu, Determination of effecting dimensional parameters on warpage of thin shell plastic parts using integrated response surce method and genetic algorithm, Int. Commun. Heat Mass Transf., vol. 32, no. 8, p.1085–1094, Aug. (2005).

DOI: 10.1016/j.icheatmasstransfer.2004.10.032

[8] H. Kurtaran and T. Erzurumlu, Efficient warpage optimization of thin shell plastic parts using response surface methodology and genetic algorithm, Int. J. Adv. Manuf. Technol., vol. 27, no. 5–6, p.468–472, Apr. (2005).

DOI: 10.1007/s00170-004-2321-2

[9] W. C. Chen, D. Kurniawan, and G. L. Fu, Optimization of Process Parameters using DOE, RSM, and GA in Plastic Injection Molding, Adv. Mater. Res., vol. 472–475, p.1220–1223, Feb. (2012).

DOI: 10.4028/www.scientific.net/amr.472-475.1220

[10] D. C. Montgomery, Design and analysis of experiments, 2nd ed. New York: Wiley, (2001).

[11] H. Öktem, T. Erzurumlu, and H. Kurtaran, Application of response surface methodology in the optimization of cutting conditions for surface roughness, J. Mater. Process. Technol., vol. 170, no. 1–2, p.11–16, Dec. (2005).

DOI: 10.1016/j.jmatprotec.2005.04.096