RA-TeS Software for Response Surface Methodology of the Mixture Experiments

Abstract

Response surface methodology, or RSM, is a collection of mathematical and statistical techniques useful for the modeling and analysis of problems in which a response of interest is influenced by several variables and the objective is to optimize this response. In mixture experiments, the factors are the components or ingredients of a mixture, and consequently their levels are not independent. For example, if x1, x2, . . . , xp denote the proportions of p components of a mixture, then 0 ≤ xi ≤ 1 i = 1, 2, . . . , p and x1 + x2 + · · · + xp = 1 (i.e., 100 percent) This paper presents the RA-TeS software for RSM of three-component mixture systems developed at Faculty of Mechanical and Civil Engineering in Kraljevo. The fitted models are analyzed to assess their adequacy and to determine the significance of the model terms. This involves conducting analysis of variance (ANOVA) to test the statistical significance of the factors and their interactions. The optimized levels of the mixture components are determined based on the fitted models and the desired response. Optimization techniques, such as RSM, are employed to find the optimal factor settings that maximize or minimize the response variable. Overall, Response Surface Methodology for Mixture Experiments provides a systematic approach for studying and optimizing mixture processes. It allows for efficient exploration of the factor space, modeling of the relationship between mixture components and response variables, and identification of optimal factor settings to achieve desired outcomes.