Property Optimisation of EPDM Rubber Composites Using Mathematical and Statistical Strategies
This paper describes a study in which EPDM-based rubber composites were investigated aiming at developing formulations subjected to restrictions on cost and the properties of the material. The contents of components other than calcium carbonate, paraffinic oil, and CBS vulcanising accelerator, as we...
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Online Access: | http://dx.doi.org/10.1155/2017/2730830 |
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doaj-a8b62fcfe7e047089b5b62d4b003cb342020-11-24T22:35:41ZengHindawi LimitedAdvances in Materials Science and Engineering1687-84341687-84422017-01-01201710.1155/2017/27308302730830Property Optimisation of EPDM Rubber Composites Using Mathematical and Statistical StrategiesSivaldo Leite Correia0Denilso Palaoro1Ana Maria Segadães2State University of Santa Catarina (UDESC), Center of Technology Sciences (CCT), 89223-100 Joinville, SC, BrazilState University of Santa Catarina (UDESC), Center of Technology Sciences (CCT), 89223-100 Joinville, SC, BrazilDepartment of Materials and Ceramics Engineering (CICECO), University of Aveiro, 3810-193 Aveiro, PortugalThis paper describes a study in which EPDM-based rubber composites were investigated aiming at developing formulations subjected to restrictions on cost and the properties of the material. The contents of components other than calcium carbonate, paraffinic oil, and CBS vulcanising accelerator, as well as additives and processing conditions, were kept constant. Fractional factorial design coupled with computational numerical optimisation was used to minimise the number of mixtures. The results demonstrate that statistical design of experiments and particle swarm optimisation (PSO) algorithms are promising methods to design composition variables. Mixture costs as low as 1.92 US$/kg can be achieved in compositions containing, for example, 107 phr of calcium carbonate, 95 phr of paraffinic oil, and 1.13 phr of CBS accelerator. The corresponding composite property-predicted values were 66.8 Shore A for hardness, tensile strength of 7.8 MPa, 570.8% elongation at break, and 23.0% rebound resilience. This demonstrates that, in this way, the desired product with specified characteristics can be comfortably manufactured at minimum cost.http://dx.doi.org/10.1155/2017/2730830 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sivaldo Leite Correia Denilso Palaoro Ana Maria Segadães |
spellingShingle |
Sivaldo Leite Correia Denilso Palaoro Ana Maria Segadães Property Optimisation of EPDM Rubber Composites Using Mathematical and Statistical Strategies Advances in Materials Science and Engineering |
author_facet |
Sivaldo Leite Correia Denilso Palaoro Ana Maria Segadães |
author_sort |
Sivaldo Leite Correia |
title |
Property Optimisation of EPDM Rubber Composites Using Mathematical and Statistical Strategies |
title_short |
Property Optimisation of EPDM Rubber Composites Using Mathematical and Statistical Strategies |
title_full |
Property Optimisation of EPDM Rubber Composites Using Mathematical and Statistical Strategies |
title_fullStr |
Property Optimisation of EPDM Rubber Composites Using Mathematical and Statistical Strategies |
title_full_unstemmed |
Property Optimisation of EPDM Rubber Composites Using Mathematical and Statistical Strategies |
title_sort |
property optimisation of epdm rubber composites using mathematical and statistical strategies |
publisher |
Hindawi Limited |
series |
Advances in Materials Science and Engineering |
issn |
1687-8434 1687-8442 |
publishDate |
2017-01-01 |
description |
This paper describes a study in which EPDM-based rubber composites were investigated aiming at developing formulations subjected to restrictions on cost and the properties of the material. The contents of components other than calcium carbonate, paraffinic oil, and CBS vulcanising accelerator, as well as additives and processing conditions, were kept constant. Fractional factorial design coupled with computational numerical optimisation was used to minimise the number of mixtures. The results demonstrate that statistical design of experiments and particle swarm optimisation (PSO) algorithms are promising methods to design composition variables. Mixture costs as low as 1.92 US$/kg can be achieved in compositions containing, for example, 107 phr of calcium carbonate, 95 phr of paraffinic oil, and 1.13 phr of CBS accelerator. The corresponding composite property-predicted values were 66.8 Shore A for hardness, tensile strength of 7.8 MPa, 570.8% elongation at break, and 23.0% rebound resilience. This demonstrates that, in this way, the desired product with specified characteristics can be comfortably manufactured at minimum cost. |
url |
http://dx.doi.org/10.1155/2017/2730830 |
work_keys_str_mv |
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