Development of a Rubber-Based Product Using a Mixture Experiment: A Challenging Case Study

Abstract

Many products used in daily life are made by blending two or more components. The properties of such products typically depend on the relative proportions of the components. Experimental design, modeling, and data analysis methods for mixture experiments provide for efficiently determining the component proportions that will yield a product with desired properties. This article presents a case study of the work performed to develop a new rubber formulation for an o-ring (a circular gasket) with requirements specified on 10 product properties. Each step of the study is discussed, including: 1) identifying the objective of the study and requirements for properties of the o-ring, 2) selecting the components to vary and specifying the component constraints, 3) constructing a mixture experiment design, 4) measuring the responses and assessing the data, 5) developing property-composition models, 6) selecting the new product formulation, and 7) confirming the selected formulation in manufacturing. The case study includes some challenging and new aspects, which are discussed in the article.

Using carboxyl groups to improve the compatibility of XNBR/lignin composites

“…The composite formulations were designed using the mixture design of experiment (MDOE), which is a type of response surface methodology. The choice of this method was based on its potential for assessing the individual contributions of each component to the ultimate property as well as confirming the presence of any interactions among the components within a blend or composite 29,30 . By fitting the experimental data to mathematical models derived from Equation S1, it is possible to generate empirical predictions regarding the properties of any possible combination of the components 29 .…”

“…The choice of this method was based on its potential for assessing the individual contributions of each component to the ultimate property as well as confirming the presence of any interactions among the components within a blend or composite. 29,30 By fitting the experimental data to mathematical models derived from Equation S1, it is possible to generate empirical predictions regarding the properties of any possible combination of the components. 29 More details about the MDOE can be found in the Supporting Information, along with the models obtained.…”

“…29,30 By fitting the experimental data to mathematical models derived from Equation S1, it is possible to generate empirical predictions regarding the properties of any possible combination of the components. 29 More details about the MDOE can be found in the Supporting Information, along with the models obtained.…”