Study on the traditional method for communication between vlans of IoT based on education simulation technology

Abstract

this paper proposes an optimization model of process parameters in Plastic Injection Molding (PIM). Firstly, the taguchi method is employed for experiment and data analysis in which the quality characteristics for the plastic injection product are length and warpage. Besides, the control factors for the process are melt temperature, injection velocity, packing pressure, packing time, and cooling time. Moreover, the signalto-noise (S/N) ratio and analysis of variance (ANOVA) are used to obtain a combination of parameter settings. Experimental data are set for the Response Surface Methodology (RSM) to analyze and create two quality predictors. two quality predictors, length and warpage, are associated with Genetic Algorithm (GA) to search for an optimal combination of process parameters that meets multiple-objective quality characteristics. the confirmation results show that the approach not only enhances the stability in the injection molding process including the quality in length and warpage but also saves the cost and time spent from the mold design to manufacturing.