The use of commercially available injection moulding simulation software’s allows us to predict the process response to the operating conditions defined. These codes can be used to define better injection conditions to use in specific situations, i.e., to optimize the process. Generally, this is an iterative procedure requiring the analysis of multiple outputs (pressures, temperatures, shear stresses profiles) supported by pre-established decision criteria. Most of the cases the taken options may lead to opposed results. In this sense the development of optimization methodologies are of paramount importance in order to facilitate the definition of processing windows in injection moulding. In this work the results obtained by the use of an automatic optimization methodology based on Multi-Objective Evolutionary Algorithms (EMOA), where an EMOA is linked to an injection moulding simulation code (CMOLD), will be assessed experimentally. For that purpose the processing conditions will be optimized for a desired process performance, where criteria, such as the evolution of the pressure inside the cavity, the maximum pressure level, the pressure work and the shrinkage, are taken into account. Some of the computational results obtained, selected from the set of optimized and non-optimized solutions, will be compared with the corresponding experimental results in order to validate the optimization approach used.
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