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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Main Authors: Sivaldo Leite Correia, Denilso Palaoro, Ana Maria Segadães
Format: Article
Language:English
Published: Hindawi Limited 2017-01-01
Series:Advances in Materials Science and Engineering
Online Access:http://dx.doi.org/10.1155/2017/2730830
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spelling 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
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