Multi-objective optimization in plastic injection molding with injection and packing time

Abstract

Plastic injection molding (PIM) is one of the most important manufacturing processes for producing plastic products. The process parameters in the PIM, such as mold temperature, melt temperature, and injection pressure affect the product quality and the manufacturing cost. In general, these are determined by a trial-and-error method, but computer-aided engineering coupled with optimization technique is recognized as one of the useful tools available. Numerical simulation in the PIM is so numerically intensive that response surface approach is valid for determining the optimal process parameters. In particular, a sequential approximate optimization (SAO) that response surface is constructed and optimized repeatedly is valid to find the optimal process parameters with a small number of simulation runs. In this paper, a cup-type plastic product is considered. The volume shrinkage is one of the major defects for dimension accuracy. In addition, it is important to produce the product with a minimum clamping force for the productivity. Short shot that the melt plastic is not filled into the die cavity is a serious defect, and this is handled as the design constraint. Thus, a multi-objective optimization problem is formulated. The pareto-frontier is identified by using the SAO with the radial basis function network. The difference of pareto-frontier with and without the injection and packing time is discussed. It is clear from the numerical result that the injection and packing time have influence on the product quality.

Untitled

“…Resinification is the replacement of steel parts with resin, and the purpose is to reduce weight and cost. The resin pulleys currently in practical use cannot be said to have sufficient characteristics as a substitute for steel pulleys in terms of strength and dimensional stability [2]. Section 2 of this paper outlines the injection molding process.…”