An Experimental Design for the Optimization of Brick Manufacturing Procedure: Application on the Late Miocene Clays, Southern Tunisia

Application of Tunisian limestone material for chlorobenzene adsorption: characterization and experimental design

“…This method is suitable for fitting a cubic surface, and it helps to optimize the effective parameters within a minimum number of experiments, as well as to analyze the interaction between the parameters (Eloussaief et al 2012c). …”

“…This analysis was achieved by response surface methodology which gave satisfactory results (Eloussaief et al 2012c). Each response (Y) can be described by a second-order model adequate for predicting the responses in all experimental regions:…”

“…For each response (Y i ), the coefficients (b i , b ij ) of the postulated model were calculated on the basis of the experimental responses by least squares regressions using the New Efficient Methodology for Research using Optimal Design (NEMROD) software (Eloussaief et al 2012c). The Hoke D6 matrix consists of N experiments with N = K 2 + K + 1, where K is the number of variables studied.…”

“…The most controlling factors were found to be the salt percentage (X 1 ) and the activation temperature (X 2 ). Thus, in the present work, we prepared a series of activated limestone with different proportions of (X 1 ) and (X 2 ) integrated in the suitable range (Eloussaief et al 2012c). A Hoke D6 matrix (Eloussaief et al 2012c) was used to represent the responses of the two factors in all experimental studied areas.…”

“…Thus, in the present work, we prepared a series of activated limestone with different proportions of (X 1 ) and (X 2 ) integrated in the suitable range (Eloussaief et al 2012c). A Hoke D6 matrix (Eloussaief et al 2012c) was used to represent the responses of the two factors in all experimental studied areas. The choice of the Hoke D6 matrix was justified by a number of advantages such as: (i) the possibility of presenting an uniform distribution of experimental points in the studied space; (ii) the ability to explore the whole of the domain; (iii) the usefulness of interpolating the response; and (iv) the possibility to add new factors without altering the quality of the matrix.…”