Multi-Response Optimization via Desirability Functionfor the Black Liquor DATA

Abstract

The experiment that was conducted to examine the advanced oxidation of the black liquor effluent obtained from the pulp and paper industry using the dark Fenton reaction in a lab-scale experiment based on Central Composite Design. The three factors along with their range values in that experiment were temperature (298; 333, K), H2O2 concentration (29.4; 58.8, mM), and Fe(II) concentration (0.36; 8.95, mM). The range of the factors were examine at fixed phase pH=3. Three response variables studied in the experiment, namely, COD removal after 90 min(%), UV254 removal after 90 min(aromatic content,%), and UV280 removal after 90 min (lignin content, %). The most widespread application of the RSM is in the situation where input variables potentially influence some quality characteristics of a process. Due to the fact that the experiment has several response variables, we employed a desirability function approach to optimize the responses simultaneously at one best setting of available factors. The resulted simultaneous optimization of an experiment is, in fact, the real situation where the experimenter should deal with since in an experiment, there is certainly a single input setting. After analyzing the data, both separated for each response variable and simultaneous for all response variables provided the same terms (factors) which are significantly contribute to the quadratic model (H2O2 and Fe(II) concentration). Nevertheles, they produced different factor settings. Through desirability function approach, we found that the best settings are 46.84 mM and 6.771 mM of H2O2 and Fe(II) concentration, respectively. Those setting can be obtained at desirability function’s value of 0.782.