Pertanika J. Sci. & Technol. 25 (S): 233-240 (2017) SCIENCE & TECHNOLOGY Journal homepage: http://www.pertanika.upm.edu.my/ Analysis of Fill Time and Injection Pressure of Multiple 20 gram Parisons during Injection Moulding Process Najiy Rizal Suriani Rizal 1, Azuddin Mam 2 and Aidah Jumah 1 * 1 Faculty of Mechanical Engineering, Universiti Teknologi MARA (UiTM), 40450, Shah Alam, Selangor, Malaysia 2 Department of Mechanical Engineering, Faculty of Engineering, Universiti Malaya (UM), 50603 Kuala Lumpur, Malaysia ABSTRACT In recent years, injection moulding process is one of the most advanced and efficient manufacturing processes for mass production of plastic bottles. However, a good quality of parison is difficult to achieve due to uncontrollable humidity, pressure inlet and wer inlet velocity. This paper investiges the effect of using multiple mould cavities to improve the process fill time and injection pressure in the production of PET plastic bottles using MoldFlow software. The modelling of parison was developed using CATIA with the considerion of every part of the parison. MoldFlow software was used to analyse the flow of 20 g parison with different cavity numbers (1, 8, 16, 24 cavity), as well as its corresponding runner size towards its fill time and injection pressure. Other important parameters th affect the production of parison, such as melting temperure, mould temperure, mospheric temperure and cooling time, were remained constant. The fill time required to produce 24 moulds was improved by 60% compared to using 8 mould cavity only, and this enable the production of more plastic bottles in a day. Therefore, fill time and injection pressure are two important parameters to be considered in the injection moulding process, especially to reduce parison defect and increase its production re. Keywords: Injection moulding, MoldFlow, mould design, parison, thermoplastic ARTICLE INFO Article history: Received: 28 September 2016 Accepted: 03 February 2017 E-mail addresses: najiyrizal@gmail.com (Najiy Rizal Suriani Rizal), aidahjumah@salam.uitm.edu.my (Aidah Jumah), azuddin@um.edu.my (Azuddin Mam) *Corresponding Author INTRODUCTION The plastic industry is one of the most vibrant sectors in Malaysia. The growth of domestic downstream plastic processing activities is tributed to the tremendous development in the petrochemical sector in the country. However, higher production costs and environmental concerns are plaguing the ISSN: 0128-7680 2017 Universiti Putra Malaysia Press.
Najiy Rizal Suriani Rizal, Azuddin Mam and Aidah Jumah industry. The conventional injection moulding machine th is exported to Malaysia is small in size and limited in shape, both critical factors th affect the production process of parison, also called preform (Rizal et al., 2015). Daver and Demirel (2012) examined the effects of preform deformion behaviour and the optimum cooling time on the quality of bottle preform. These effects were determined by conducting structural analysis on the actual bottles. Hedia, Aldousari and Zager (2010) studied the optimal design for PET bottle in order to maximise its reliability by using numerical simulion to analyse the effect of the design ( Hedia, Aldousari, & Zager, 2010). De Miranda et al. (2011) studied the design optimision and weight reduction of 500 ml CSD PET bottle through FEM simulions. These studies examined the simulion of the process and the mechanical demands reled to the PET bottle applicion with the aim of assessing the efficiency of packaging design and enabling efficient and correct sizing. Chen (2011) used a genetic algorithm method to simule and analyse optimision process parameters for Multi-cavity injection moulding parts warpage. It was found th multi-cavity mould runner arrangements could seriously affect the warpage changes of the parts. Li and Jia (2011) studied the structural characteristics of mould for precise injection moulding. The current paper examined the influence of mould structure on the quality of injection-moulded parts. Taghizadeh et al. (2013) focused on warpage prediction in plastic injection moulded part using artificial neural network. Similarly, Nian et al. (2015) studied warpage control of thin-walled injection moulding using local mould temperures. Wang et al. (2013) investiged the reduction of sink mark and warpage of the moulded part in rapid he cycle moulding process. The amount of merials injected into the parison mould is difficult to control, contributing to low quality products. This leads to an increase in the number of rejected products, which transles into high production cost and wastage. There has been no comprehensive study on the effect of number of cavity on fill time and injection pressure. The present work used MoldFlow with Polyethylene Terephthale (PET) mechanical properties and parameters to stimule and investige the effect of 20 g parison on fill time and injection pressure. A robust design of parison mould with greener injection moulding system was modelled using CATIA V5R20. METHOD The Geometrical Acquisition and general parameter of actual mould 20 g parison was done and analysed. The mould is taken from Bakal Seji to undergo Coordine Measuring Machine (CMM) BEYOND707 Mitutoyo to get the geometrical measurement of the actual size of the parison. The general parameter for the injection moulding process was also acquired from the same company as shown in Table 1. 234 Pertanika J. Sci. & Technol. 25 (S): 233-240 (2017)
Parameter Analysis during Injection Moulding Process Table 1 General acquired parameters for 20 g parison Factor Mould Temperure 100 C Melt Temperure 280 C Packing time Packing Pressure Cooling time Parameter of 20 g Parison 10 Sec 140 MPa 17 Sec Cooling temperure 30 C Ambient temperure 35 C After the measurement was collected form CMM, the geometrical measurement is modelled using CATIA V5R20 Dassault System to produce a CAD model of 20 g parison as show in Figure 1. The measurement is based on the actual model with dimensions drawn in mm. Figure 1. The geometry of the 20 g parison The modelled geometry was then transferred to Autodesk MoldFlow Insight 2011 Educional Edition software to analyse the parison model by following the actual injection moulding process. The parameter and merial properties are input into this software. Simulion of the injection moulding process was conducted using a variion of number cavities consisting of 1 cavity, 8 cavities, 16 cavities and 24 cavities respectively, with the process parameter in Table 1. Figure 2 below is the parison modelled using MoldFlow simulion. The input parameters for simulion are shown in Table 2. Pertanika J. Sci. & Technol. 25 (S): 233-240 (2017) 235
Najiy Rizal Suriani Rizal, Azuddin Mam and Aidah Jumah Figure 2. The parison of multi-cavity using MoldFlow software Table 2 The parameter input for MoldFlow software Factor Mould temperure 100 C Melt Temperure 280 C Atmospheric temperure 35 C Cooling time Runner Size Parameter of 20 g Parison 17 s 8 mm The properties of merials correle with the process parameters of injection moulding and mould modelling. The Polyethylene Terephthale (PET) used in this research is Eastar Copolyester EN067 th was supplied by Eastman Chemical Products. PET is a thermoplastic polymer th has good ductility, strength, hardness and stiffness while the amorphous PET has better ductility. 20 g parison on the viscous plastic flow and the re of filling time is analysed. The effect of number of cavities and on fill time and on injection pressure is examined. RESULTS AND DISCUSSION Four different numbers of cavities (1 cavity, 8 cavities, 16 cavities and 24 cavities) were analysed using MoldFlow to determine the fill time and injection pressure. The number of cavities affect the fill time and injection pressure of the parison. The runner size also varies as the number of cavities increases. Figure 3 shows the time taken to fill 1, 8, 16 and 24 cavities are 0.5236 s, 0.7745 s, 0.8737 s and 1.145 s respectively. The result shows the increase in number of cavities actually increases production. The difference in time between these four cavities was an increase of about 60%. 236 Pertanika J. Sci. & Technol. 25 (S): 233-240 (2017)
Parameter Analysis during Injection Moulding Process Table 3 shows the percentage of volume filling specific flow time for 1 cavity, 8 cavities, 16 cavities and 24 cavities. Da shows th it takes a longer time to fill 24 cavities. However, in terms of production, the 24 cavity produced much higher parison compared with 8 cavities. The efficiency of the 24 cavity parisons in terms of production is better than a 16 cavity and 8 cavity parisons but in terms of overhead cost, it is more expensive to produce a 24 cavity parison. Figure 3. Viscous plastic flow analysis of PET merial for four different models; (i) 1 cavity; (ii) 8 cavities; (iii) 16 cavities; and (iv) 24 cavities Table 4 shows the result for the fill time and injection pressure for the four cavities (1 cavity, 8 cavities, 16 cavities and 24 cavities). From the tabulion below, the fill time for 24 cavity parison is within 1.145s which is higher compared with a single cavity. However, if the comparison is made in terms of fill time per parison, a 24-mould cavity parison filled much faster compared with single cavity, which is 0.0475 s per parison and 0.5236 s per parison respectively. Pertanika J. Sci. & Technol. 25 (S): 233-240 (2017) 237
Najiy Rizal Suriani Rizal, Azuddin Mam and Aidah Jumah Table 3 Percentage of volume filling specific flow time of parison by number of cavity Cavity & percentage Fill Time (s) 0 0% 0s 1 (%) 8 (%) 16 (%) 24 (%) 0% 0s 0% 0s 0% 0s 0.1 20.84% 0.1091s 16.67% 0.1291s 12.46% 0.1089s 12.50% 0.1431s 0.3 58.35% 0.3055s 41.67% 0.3227s 37.50% 0.3276s 29.16% 0.3339s 0.5 100% 0.5236s 66.66% 0.5163s 58.33% 0.5097s 45.83% 0.5247s 0.7 100% 0.7745s 83.34% 0.7281s 62.49% 0.7155s 0.8 100% 0.8737s 79.16% 0.9064s 1.0 100% 1.1450s Table 4 Parameter analysis for number of cavity Number of Cavity 1 8 16 24 Fill time (s) 0.5236 0.7745 0.8737 1.145 Fill time / parison 0.5236 0.0968 0.0546 0.0475 Injection pressure (MPa) 20.1371 36.8453 32.6802 30.6973 238 Pertanika J. Sci. & Technol. 25 (S): 233-240 (2017)
Parameter Analysis during Injection Moulding Process Figure 4. Fill Figure time 4. against Fill time number against number of cavities of cavities Figure 4 shows th when the number of cavity increases the fill time also increases. The number of cavities affects the fill time in mass production. Increasing the number of cavities will produce more parison in terms of mass production. In order to produce 24 parison, the process will take 1.145 s when using 24 cavities mould, whereas it takes 12.5664 s for single cavity and 2.3235 s for 8 cavities to produce 24 parison respectively. Figure 5. Injection pressure against number of cavities Figure 5 shows the injection pressure affects the number of cavities from 8 to 24 cavities. There was a decrease in injection pressure from 8 to 24 cavities mould. This was due to the increase of sprue, runner and ge as they automically change with the increase of mould cavity to reduce part malfunction from excessive pressure. Pertanika J. Sci. & Technol. 25 (S): 233-240 (2017) 239
Najiy Rizal Suriani Rizal, Azuddin Mam and Aidah Jumah CONCLUSION The main objective of this study was to investige the effect of number of cavity on fill time and injection pressure. The simulion using MoldFlow was carried out to study the effect of cavity numbers on fill time and injection pressure. The process parameters considered during the analysis are melting temperure, mould temperure, mospheric temperure and cooling time. The change in fill time and injection pressure differs based on Figure 4 and Figure 5. Future studies can look how to overcome the change in mould temperure. ACKNOWLEDGEMENTS The authors thank Institute of Research Management and Innovion (IRMI), Ministry of Educion Malaysia and Institute of Gradue Studies (IPSIS) UiTM for their financial support. This research was performed the Faculty of Mechanical Engineering, UiTM Malaysia under Grant BESTARI 600-IRMI/DANA 5/3/BESTARI (0006/2016). REFERENCES Chen, W. J. (2011). Simulion and Analysis of Optimizion Process Parameters for Multi Cavity Injection Molding Parts Warpage by Genetic Algorithm Method. Applied Mechanics and Merials, 142, 54 57. Daver, F., & Demirel, B. (2012). A simulion study of the effect of preform cooling time in injection stretch blow molding. Journal of Merials Processing Technology, 212(11), 2400 2405. https://doi. org/10.1016/j.jmprotec.2012.06.004 De Miranda, C. A. S., Camara, J. J. D., Monken, O. P., & Dos Santos, C. G. (2011). Design Optimizion and Weight Reduction of 500 ml CSD PET Bottle through FEM Simulions. Journal of Merials Science and Engineering B, 1(7), 947 959. Hedia, H. S., Aldousari, S., & Zager, F. B. (2010). Optimal Design for PET Bottle to Maximize Reliability: Finite Element Analysis and Experimental Work. Merials Testing, 52(6), 383-393. Li, H. L., & Jia, Z. X. (2011). Study of the Structural Characteristics of Mold for Precise Injection Molding. Advanced Merials Research, 291 294, 610 613. https://doi.org/10.4028/www.scientific. net/amr.291-294.610 Nian, S.-C., Wu, C.-Y., & Huang, M.-S. (2015). Warpage control of thin-walled injection molding using local mold temperures. Internional Communicions in He and Mass Transfer, 61, 102 110. https://doi.org/10.1016/j.ichemasstransfer.2014.12.008 Suriani Rizal, N. R., Jumah, A., Hashim, U. R., & Omar, M. S. (2015). Effect of Pet Parison Size on Injection Moulding Mould Design. Jurnal Teknologi, 76(6), 115-119. https://doi.org/10.11113/ jt.v76.5702 Taghizadeh, S., Ozdemir, A., & Uluer, O. (2013). Warpage Prediction in Plastic Injection Molded Part using Artifical Neural Network, 37, 149 160. Wang, X., Zhao, G., & Wang, G. (2013). Research on the reduction of sink mark and warpage of the molded part in rapid he cycle molding process. Merials and Design, 47, 779 792. https://doi. org/10.1016/j.mdes.2012.12.047 240 Pertanika J. Sci. & Technol. 25 (S): 233-240 (2017)