Multi-Objective Optimization of Plastics Thermoforming
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...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-07-01
|
| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/9/15/1760 |
| _version_ | 1797525333257224192 |
|---|---|
| author | António Gaspar-Cunha Paulo Costa Wagner de Campos Galuppo João Miguel Nóbrega Fernando Duarte Lino Costa |
| author_facet | António Gaspar-Cunha Paulo Costa Wagner de Campos Galuppo João Miguel Nóbrega Fernando Duarte Lino Costa |
| author_sort | António Gaspar-Cunha |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T09:12:16Z |
| format | Article |
| id | doaj.art-9f5b16ce9242406a959ddb763b91cfb6 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-10T09:12:16Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-9f5b16ce9242406a959ddb763b91cfb62023-11-22T05:56:21ZengMDPI AGMathematics2227-73902021-07-01915176010.3390/math9151760Multi-Objective Optimization of Plastics ThermoformingAntónio Gaspar-Cunha0Paulo Costa1Wagner de Campos Galuppo2João Miguel Nóbrega3Fernando Duarte4Lino Costa5IPC—Institute of Polymer and Composites, University of Minho, 4800-050 Guimarães, PortugalIPC—Institute of Polymer and Composites, University of Minho, 4800-050 Guimarães, PortugalIPC—Institute of Polymer and Composites, University of Minho, 4800-050 Guimarães, PortugalIPC—Institute of Polymer and Composites, University of Minho, 4800-050 Guimarães, PortugalIPC—Institute of Polymer and Composites, University of Minho, 4800-050 Guimarães, PortugalALGORITMI Center, University of Minho, 4800-050 Guimarães, PortugalThe 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.https://www.mdpi.com/2227-7390/9/15/1760plastics thermoformingsheet thickness distributionevolutionary algorithmsmulti-objective optimization |
| spellingShingle | António Gaspar-Cunha Paulo Costa Wagner de Campos Galuppo João Miguel Nóbrega Fernando Duarte Lino Costa Multi-Objective Optimization of Plastics Thermoforming Mathematics plastics thermoforming sheet thickness distribution evolutionary algorithms multi-objective optimization |
| title | Multi-Objective Optimization of Plastics Thermoforming |
| title_full | Multi-Objective Optimization of Plastics Thermoforming |
| title_fullStr | Multi-Objective Optimization of Plastics Thermoforming |
| title_full_unstemmed | Multi-Objective Optimization of Plastics Thermoforming |
| title_short | Multi-Objective Optimization of Plastics Thermoforming |
| title_sort | multi objective optimization of plastics thermoforming |
| topic | plastics thermoforming sheet thickness distribution evolutionary algorithms multi-objective optimization |
| url | https://www.mdpi.com/2227-7390/9/15/1760 |
| work_keys_str_mv | AT antoniogasparcunha multiobjectiveoptimizationofplasticsthermoforming AT paulocosta multiobjectiveoptimizationofplasticsthermoforming AT wagnerdecamposgaluppo multiobjectiveoptimizationofplasticsthermoforming AT joaomiguelnobrega multiobjectiveoptimizationofplasticsthermoforming AT fernandoduarte multiobjectiveoptimizationofplasticsthermoforming AT linocosta multiobjectiveoptimizationofplasticsthermoforming |