Multi-Objective Optimization of Plastics Thermoforming

António Gaspar-Cunha, Paulo Costa, Wagner de Campos Galuppo, João Miguel Nóbrega, Fernando Duarte and Lino Costa
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António Gaspar-Cunha: IPC—Institute of Polymer and Composites, University of Minho, 4800-050 Guimarães, Portugal
Paulo Costa: IPC—Institute of Polymer and Composites, University of Minho, 4800-050 Guimarães, Portugal
Wagner de Campos Galuppo: IPC—Institute of Polymer and Composites, University of Minho, 4800-050 Guimarães, Portugal
João Miguel Nóbrega: IPC—Institute of Polymer and Composites, University of Minho, 4800-050 Guimarães, Portugal
Fernando Duarte: IPC—Institute of Polymer and Composites, University of Minho, 4800-050 Guimarães, Portugal
Lino Costa: ALGORITMI Center, University of Minho, 4800-050 Guimarães, Portugal

Mathematics, 2021, vol. 9, issue 15, 1-20

Abstract: The practical application of a multi-objective optimization strategy based on evolutionary algorithms was proposed to optimize the plastics thermoforming process. For that purpose, in this work, differently from the other works proposed in the literature, the shaping step was considered individually with the aim of optimizing the thickness distribution of the final part originated from sheets characterized by different thickness profiles, such as constant thickness, spline thickness variation in one direction and concentric thickness variation in two directions, while maintaining the temperature constant. As far we know, this is the first work where such a type of approach is proposed. A multi-objective optimization strategy based on Evolutionary Algorithms was applied to the determination of the final part thickness distribution with the aim of demonstrating the validity of the methodology proposed. The results obtained considering three different theoretical initial sheet shapes indicate clearly that the methodology proposed is valid, as it provides solutions with physical meaning and with great potential to be applied in real practice. The different thickness profiles obtained for the optimal Pareto solutions show, in all cases, that that the different profiles along the front are related to the objectives considered. Also, there is a clear improvement in the successive generations of the evolutionary algorithm.

Keywords: plastics thermoforming; sheet thickness distribution; evolutionary algorithms; multi-objective optimization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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