ANALYSIS ON VOLUMETRIC SHRINKAGE OF PLASTIC FOOD CONTAINER MADE FROM AN INJECTION MOLDING PROCESS

Rosidah Jaafar, Hambali Arep, Effendi Mohamad, Jeefferie Abd Razak, Muhamad Arfauz A Rahman, Rahmi Yuniarti

Abstract


The plastic injection molding process is one of the widely used of the manufacturing process to manufacture the plastic product with high productivity.  Moreover, the food packaging manufacturing industry undergoes the trials and errors to obtain the optimal setting of the process parameters in order to minimize the quality issues and these trials and errors are time consuming and costly.  The aim of this study is to improve the quality of the butter tub by minimizing the volumetric shrinkage. This study is to deal with the application of Moldflow integrating with the statistical technique to minimize the volumetric shrinkage the butter tub which depends on the process parameters of the plastic injection molding.  For this purpose, the rectangular shape of butter tub is designed by utilizing the SolidWorks.  Molflow is used to simulate the plastic filling of the single cavity mold of butter tub based on the Taguchi’s  orthogonal array table.  In addition, the analysis of variance (ANOVA) is applied to investigate significant impact of the process parameters on the quality of the butter tub. Minitab is used to optimize the response of the volumetric shrinkage by selecting the most appropriate process parameters that maximizing the desirability value.  Furthermore, the butter tub has a uniform thickness which was 1.2 mm and its factor of safety was 3.383 and the volumetric shrinkage response have optimized by 0.956 %. The melt temperature and mold temperature are found to be the most significant process parameters for the plastic injection molding process of butter tub and the volumetric shrinkage value obtained from the simulation is verified by the calculated volumetric shrinkage value.

Keywords


plastic injection molding;moldflow; volumetric shrinkage

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References


Ozcelik B, Erzurumlu T. Comparison of the warpage optimization in the plastic injection molding using ANOVA, neural network model and genetic algorithm. Journal of Materials Processing Technology. 2006;171: 437-445.

Behrooz F, Siavash G, Elyar M. Optimization of injection molding process parameters using sequential simplex algorithm. Journal of Materials and Design. 2011;32: 414-423.

Kim BJ, Shin JK, Lee JG, Sohn IS. Effects of Packing Parameter on Plastic Article Dimensions in the Plastic Injection Molding. Journal of the Korean Society for Precision Engineering. 2014;31(1): 9-13.

Erfan O, Behzad SH, Seyed MD, Mozhgan B, Saeed D, Iman H, Javad S. Warpage and shrinkage optimization of injection-molded plastic spoon for biodegradable polymers using Taguchi, ANOVA and Artificial Neural Network Methods. Journal of Materials Science and Technology, 2016;32: 710-720.

Song MC, Liu Z, Wang MJ, Yu TM, Zhao DY. Research on effects of injection process parameters on the molding process for ultra-thin wall plastic parts. Journal of Materials Processing Technology. 2007;187-188; 668-671.

Patcharaphun S, Zhang B, Mennig G. Simulation of three-dimensional fiber orientation in weld line areas during push–pull-processing. Journal of Reinforced Plastics and Composites. 2007;26(10): 977–985.

Chen CP, Chiang MT, Hsiao YH, Yang YK, Tsai CH. Simulation and experimental study in determining injection molding process parameters for thin-shell plastic parts via design of experiments analysis. Journal of Expert Systems with Applications. 2009;36: 10752-10759.

Altan M. Reducing shrinkage in injection moldings via the Taguchi, ANOVA and neural

network methods. Journal of Materials and Design. 2010;31: 599–604.

Myers RH, Montgomery DC. Response surface methodology: Process and product optimization using designed experiments (2nd ed.). New York. John Wiley and Sons Inc. 2002.


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