Using Multi-Objective Evolutionary Algorithms to Optimize Mechanical Properties of Injection Molded Parts

Abstract

Abstract An automatic optimization methodology based on Multi-Objective Evolutionary Algorithms (MOEA) is proposed to optimize the mechanical properties of injection molded products. For that purpose an MOEA is linked to a commercially available mould filling computer simulator code, CMOLD. The developed optimization methodology was applied to a practical case study where the processing conditions are optimized as a function of a desired morphological state (skin thickness, degree of crystallinity and/or level of molecular orientation; these latter are interpreted in terms of thermomechanical indices) and envisaged mechanical performance at two strain rates levels (of the order of 10–4 and 102 s1). Generally, the optimization methodology proposed is able to take into account the influence of the process parameters and produce solutions that are physically consistent. The processing conditions maximizing the morphological state of the moldings and their mechanical performance are identified. This latter is firstly maximized individually for distinct strain-rates and then a simultaneous optimization for both low and high strain-rate response is performed. The optimized sets of processing conditions leading to the maximization of the mechanical performance are analyzed by the computation of two thermomechanical indices aiming at interpreted the resultant morphological state of the moldings.