Plastic injection molding is one of the most important technologies for manufacturing plastic products. The quality of products made by the plastic injection molding depends on materials, molds, injection molding machines and process parameters. Materials, molds, and injection molding machines are selected at the first stage of product development. Therefore, it is one of the most important issues to determine the optimal injection process parameters to improve the quality of products.
Various methods have been applied to optimize the process parameters. Trial and error method demands massive experiments and a huge amount of labor, time and cost. To overcome these drawbacks and determine optimal process parameters, various optimization techniques such as Taguchi method, genetic algorithm (GA), simulated annealing (SA) and particle swarm optimization (PSO) methods have been widely used in various works. Among them, Taguchi method has been applied most widely to solving many practical engineering optimization problems because of its simplicity and effectiveness.
Kim Ju Song, a researcher at the Faculty of Materials Science and Technology, has proposed a method to determine optimal process parameter values using Taguchi method and TOPSIS in plastic injection molding, and applied it to the determination of optimal process parameters such as melt temperature, packing pressure, cooling time and injection pressure in order to optimize the mechanical properties such as tensile strength, elasticity module, flexural modulus and impact strength with ABS compound as plastic materials and AISI 1020 as mold materials.
The proposed method can determine optimal values and effect ranking of the process parameters for simultaneously improving the multiple mechanical properties of plastic injection moldings.
For more information, please refer to his paper “Determining method of optimal process parameters using Taguchi method and TOPSIS in plastic injection molding” in “Journal of Reinforced Plastics and Composites” (SCI).
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