Technical University of Kosice. Fakulty of Mechanical Engineering
Abstract
Thermoforming is a thermoplastic processing technique commonly used in the rigid packaging industry. The process comprises a heating stage, which aims at allowing the sheet to acquire the required deformability, a deformation stage, in which the sheets conform to the mould surface, and, finally, a cooling stage, which allows the part to be extracted from the mould without distorting. Since there are several processing variables associated with those stages, optimizing the thermoforming process is a complex task. In this work, a multi-objective optimization evolutionary algorithm is proposed to optimize the plastics thermoforming process. For that purpose, the thickness distribution of the final part was optimized considering that it is manufactured from uniform temperature sheets with different thickness distributions, such as constant and spline and concentric profiles. The aims were to minimize the sheet volume, as it implies less material use; assure a minimum value for the part thickness distribution, to avoid hindering its mechanical behavior; and minimize the thickness heterogeneity, i.e., the difference between the thickness of the part and a reference thickness. The Pareto optimal solutions found by the algorithm correspond to different thickness profiles for the three different sheet shapes. In all cases, an improvement of the different profiles along the successive generations of the evolutionary algorithm was obtained, which are related to the objectives considered. Moreover, the initial sheet thickness distribution was found to clearly influence the optimization process. The results obtained for these three different initial sheet shapes indicate that the proposed methodology is valid, providing solutions with physical meaning and with great potential to be applied in more complex cases
