Comparison of Numerical and Experimental Data in Multi-objective Optimization of a Thermoplastic Molded Part

Abstract

Abstract Warpage reduction, dimensional tolerance accomplishment and time and cost saving are some of the most important problems in the injection molding production process. In this study, a real case of a thermoplastic injected part is analyzed. The mold for a pipeline connecting element has been designed, according to known technical and economical criterion to fulfill customer requirements. Particularly for this element, warpage of a specified surface and two diameter sizes are fundamental for correct part functionality and assembling. The analysis is centered on the effects of four process parameters, i. e. packing pressure, packing time, melt temperature and cooling time that heavily influence final results. A finite element model has been used to evaluate their effects on four important final objectives that are the geometrical entities and production cycle time. Each variable has been varied into its proper range, in accordance with a central composite design DoE plan; 25 simulations have been executed and results have been represented using response surfaces. Pareto Front for above listed objectives has been extracted using a genetic algorithm and the best set of parameters has been determined after application of specific selection criteria and a weighted objective function. After numerical evaluation, the CCD DoE plan has been experimentally repeated. Results have been measured on real components, and then represented with response surfaces as well. The same algorithm and objective function have been used for optimization, to determine the experimental optimum parameter set. Finally, the two parameter sets have been compared.