Multi-cavity mould design and simulation of polyethylene terephthalate (PET) plastic parison / Najiy Rizal Surianirizal

Injection moulding is one of the most popular manufacturing processes for producing good finishing plastic products with low cost and high volume production. The growth of domestic downstream bottle parison processing activities can be attributed to the tremendous development in petrochemical sector in Malaysia. There are several main factors that may contribute to low product quality such as improper design of injection mould, improper settings of process parameters and the properties of material. These factors will lead to the defects of bottle parison. This study is aimed to model the original and improved eight-cavity parison moulds using CATIA in order to produce a good quality of parison. The effect of product dimensions (sizes) on design parameters was studied. Then, further investigation on the effect of parison dimensions on process parameters was investigated using MoldFlow simulation software. Lastly, the optimum process parameters using Design of experiment (DOE) were determined. Using CATIA, the actual mould of parison was improved and the number of parts were reduced. The designing process was focused on the female core section that consists of four parts, i.e. plates A, B, C and D. Plate A consists of cavity plate and insert part. Plate B consists of insert cavity lock and control panel. Plate C consists of the pressure rods and pressure springs for the inlet material. Back plate D consists of the manifold sprue, runner, gates and heater rod. Polyethylene Terephthalate (PET) material was used in this study. Rheology analysis was conducted in order to evaluate the relationship between viscosity and shear rate of the material. The effects of parison sizes (of 15g, 20g and 30g) and number of mould cavity (1, 8, 16 and 24 cavities) on plastic flow behavior and process parameters were also studied using MoldFlow. The process parameters results, obtained from MoldFlow analysis, were optimized using DOE. The Li6 Orthogonal Array (OA) and Analysis of variance (ANOVA) were used for the optimisation process to assess the influence of each respond. Based on the results, the optimum parameters for producing an optimum fill time were Al, Bl and C4 of mould temperature=20°C, runner size=6 mm and melting temperature=280°C. The optimum parameters for producing an optimum injection pressure were A4, B4 and C4. The mould temperature of 80°C, runner size of 8mm and melting temperature of 280°C could optimise the injection pressure during injection process. The optimum density could be achieved using optimum injection parameters of Al, Bl and CI, i.e. the mould temperature=20°C, runner size=6mm and melting temperature=265°C. The optimum process parameters for volumetric shrinkage were mould temperature=20°C, runner size=9mm and melting temperature=265°C. Therefore, the optimisation results for the four individual respond of fill time, injection pressure, density and volumetric shrinkage were A1B1C4, A4B4C4, A1B1C1 and A1B4C1, respectively.