PARAMETRIC OPTIMIZATION OF INJECTION MOLD SETTINGS FOR THE WEIGHT EFFICIENCY OF POLYPROPYLENE PLASTIC CUPS USING RESPONSE SURFACE METHODOLOGY

This novel study focuses on the parametric optimization of injection mold settings to enhance the quality of polypropylene plastic cups. A model for the optimal injection mold settings, including cooling time, mold temperature, injection pressure, and injection speed (independent variables), was developed using the response surface methodology (RSM) to optimize the polypropylene plastic cup weight (dependent variable). Weight is an essential parameter in polypropylene plastic cups, directly influencing their durability, cost, and functional application. RSM was used for the experimental design, comprising multiple iterations of mold trial testings with variations in the input variables. The RSM model developed in this study produced the following optimal solutions for the input factors: cooling time – 15s; mold temperature – 57.270 °C; injection pressure – 95 MPa; and injection speed – 50 mm/s. The optimal solution for the response variable, weight, from the RSM analysis is 32.06g. The RSM analysis produced a global desirability (Dg) of 1 (100%) for achieving the optimal solutions. The RSM model explains 80.61% of the variance in the response variable, which is a strong contribution, as indicated by the coefficient of determination (R2). The selected model was the quadratic model, as indicated by the analysis of variance (ANOVA). The square (quadratic) term of the cooling time input factor and the interactive term between the cooling time and injection pressure were the two factors that had the most significant impact on the weight response variable of the finished polypropylene plastic cup product, as shown by the ANOVA. It is recommended that manufacturers implement the optimal solutions determined in this study in their production. This approach will mitigate waste and imperfections in plastic cups and allied products when implemented in injection molding. This study demonstrated the feasibility of determining optimal mold settings and materials to enhance product quality through the design of experiments (DOE).