Prediction and fuzzy synthetic optimization of process parameters in heavy clay brick production

Abstract

Many factors influence final clay brick properties, since the raw materials used are highly heterogeneous. Statistical analysis is rarely used, according to literature, but it would improve understanding of the overall system behavior and the quality of products. In this study, analysis of variance (ANOVA) showed that the most important parameters influencing compressive strength (CS) were the quadratic terms of firing temperature, CaO and SiO2 content in developed second order polynomial (SOP) models. Water absorption (WA) was mostly influenced by quadratic terms of CaO and SiO2. The most influential interchange terms in all the models were SiO2 x CaO, SiO2 x Na2O, Fe2O3 x Na2O, CaO x Na2O and CaO x K2O. Developed SOP models, which connected the influence of major oxides content and firing temperature on CS and WA, showed the highest r(2) values (0.926-0.967) obtained in the literature so far, for these naturally occurring heavy clay raw materials. Developed models were able to predict CS and WA in a wide range of chemical composition and temperature treatment data. The implementation of the SOP model is simple using the set of equations in a spreadsheet. The focus of this study was to determine the optimal composition and firing temperature, depending on final usage of the raw material in heavy clay brick industry. The study was conducted using fuzzy synthetic evaluation, through membership trapezoidal function, with pre-defined optimal interval values for every group of heavy clay products. The optimal samples chemical composition and firing temperature were chosen regarding the kind of the heavy clay product (I-solid bricks, II-hollow blocks and ceiling elements, and III-roof tiles).