| Abstrakt: |
In Indonesia, the need for plastic reaches 4.6 million tons per year with an average increase of 5% per year and the largest portion of 40% for packaging products. The use of plastics in various fields is due to the nature of plastics that can replace the function of other materials. More than 30% of all plastic parts are produced by injection molding. The production process of injection molding machines for bioball spike products is not yet perfect. Product defects cause losses in the process and production costs. The Taguchi method is selected to obtain optimal parameters in minimizing product defects. Not complete product defects and flash defects can be a big issue for manufacturing companies engaging in injection molding. Product defects have to be avoided or corrected by calculating, analyzing, and optimizing the parameters affecting the defects. This study used the experimental method by determining the experimental design through fractional factorial L9 (34) for thirty-five injection experimental cycles for the initial design and forty cycles for L9 (34) where the test object used a bioball spike product with ingredients of polypropylene. The parameters used were the injection speed, injection pressure, injection time, and melt temperature with three levels each. This study used mean analysis (ANOM) and verified using the Taguchi method to obtain the average effect on each level parameter and obtain plot effects. Analysis of variance (ANOVA) was performed to determine the effect of the average parameter on the output which aims to verify the Taguchi method. The results showed that this parameter combination was optimal in minimizing not complete defects and flash defects as well as the influence of the parameters. The results obtained determine the effect of each parameter, namely the melt temperature (MT) parameter of 69.33%, injection speed (IS) of 25.24%, injection time (IT) of 7.69%, and injection pressure (IP) of 1.64%. The optimal combination of parameters causes flash defects with a combination of injection speed (IS) parameters at level 3 (45 cm/s), injection pressure (IP) at level 2 (40 kg/cm2), injection time (IT) at level 2 (4 seconds), and melt temperature (MT) at level 2 (195). The results of the comparison of the value of the S/N Ratio before optimization (initial design) was 24712 and after optimization (optimal design) was 38,217 so there was an increase of 13.505. [ABSTRACT FROM AUTHOR] |
