-Today, around 30% of manufactured plastic goods rely on injection molding. The cooling time can represents more than 70% of the injection cycle. Moreover, in order to avoid defects in the manufactured plastic parts, the temperature in the mold must be homogeneous. We propose in this paper a practical methodology to optimize both the position and the shape of the cooling channels in 3D injection molding processes. For the evaluation of the temperature required both by the objective and the constraint functions, we must solve 3D heat-transfer problems via numerical simulation. We solve the heat-transfer problem using Boundary Element Method (BEM). This yields a reduction of the dimension of the computational space from 3D to 2D, avoiding full 3D remeshing: only the surface of the cooling channels needs to be remeshed at each evaluation required by the optimization algorithm. We propose a general optimization model that attempts at minimizing the desired overall low temperature of the plastic-part surface subject to constraints imposing homogeneity of the temperature. Encouraging preliminary results on two semi-industrial plastic parts show that our optimization methodology is viable.

Optimization and inverse identification are two procedures usually encountered in many industrial processes reputed gourmand for the computing time view point. In fact, optimization implies to propose a trial solution whose accuracy is then evaluated, and if needed it must be updated in order to minimize a certain cost function. In the case of mold cooling optimization the evaluation of the solution quality needs the solution of a thermal model, in the whole domain and during the thermal history. Thus, the optimization process needs several iterations and then the computational cost can become enormous. In this work we propose the use of model reduction for accomplishing this kind of simulations. Thus, only one thermal model is solved using the standard discretization technique. After that, the most important modes defining the temperature evolution are extracted by invoking the proper orthogonal decomposition, and all the other thermal model solutions are performed by using the reduced order approximation basis just extracted. The CPU time savings can be impressive.