Sermin Elevli

Comparison of the results of response surface methodology and artificial neural network for the biosorption of lead using black cumin.

In this study, Response Surface Methodology (RSM) and Artificial Neural Network (ANN) were employed to develop an approach for the evaluation of heavy metal biosorption process. A batch sorption process was performed using Nigella sativa seeds (black cumin), a novel and natural biosorbent, to remove lead ions from aqueous solutions. The effects of process variables which are pH, biosorbent mass, and temperature, on the sorbed amount of lead were investigated through two-levels, three-factors central composite design (CCD). Same design was also utilized to obtain a training set for ANN. The results of two methodologies were compared for their predictive capabilities in terms of the coefficient of determination-R(2) and root mean square error-RMSE based on the validation data set. The results showed that the ANN model is much more accurate in prediction as compared to CCD.

Statistical evaluation and optimization of factors affecting the leaching performance of copper flotation waste.

Copper flotation waste is an industrial by-product material produced from the process of manufacturing copper. The main concern with respect to landfilling of copper flotation waste is the release of elements (e.g., salts and heavy metals) when in contact with water, that is, leaching. Copper flotation waste generally contains a significant amount of Cu together with trace elements of other toxic metals, such as Zn, Co, and Pb. The release of heavy metals into the environment has resulted in a number of environmental problems. The aim of this study is to investigate the leaching characteristics of copper flotation waste by use of the Box-Behnken experimental design approach. In order to obtain the optimized condition of leachability, a second-order model was examined. The best leaching conditions achieved were as follows: pH = 9, stirring time = 5 min, and temperature = 41.5°C.

Correspondence analysis of repair data: a case study for electric cable shovels

In mining operation, effective maintenance scheduling is very important because of its effect on the performance of equipment and production costs. Classifying equipment on the basis of repair durations is considered one of the essential works to schedule maintenance activities effectively. In this study, repair data of electric cable shovels used in the Western Coal Company, Turkey, has been analyzed using correspondence analysis to classify shovels in terms of repair durations. Correspondence analysis, particularly helpful in analysing cross-tabular data in the form of numerical frequencies, has provided a graphical display that permitted more rapid interpretation and understanding of the repair data. The results indicated that there are five groups of shovels according to their repair duration. Especially, shovels numbered 2, 3, 7, 10 and 11 required a repair duration of<1 h and maintained relatively good service condition when compared with others. Thus, priority might be given to repair them in maintenance job scheduling even if there is another failed shovel waiting to be serviced. This type of information will help mine managers to increase the number of available shovels in operation.

ADSORPTION OF NEUTRAL RED DYE FROM AN AQUEOUS SOLUTION ONTO NATURAL SEPIOLITE USING FULL FACTORIAL DESIGN

The main objective of factorial design is to construct an empirical model to understand complex phenomena such as a purification process up to a given level of accuracy. The present study aimed to investigate the adsorption of Neutral Red dye (NR) from an aqueous solution onto sepiolite using 24 full factorial design. The combined effect of initial dye concentration, adsorbent dosage, pH, and particle size on adsorption of the dye was studied. The results were analyzed statistically using the student’s t-test, analysis of variance (ANOVA), and an F-test to define important experimental factors and their relative levels of importance. A regression model which may be used to estimate the removal efficiency of NR without performing any experiments was suggested. The coefficient of determination (R2 = 0.9938) indicated that <1% only of the total variations remain unexplained by the regression model. The experimental factors selected were determined to influence the adsorption process, but their relative importance varied according to the following sequence: pH > adsorbent dosage > particle size > initial concentration. The magnitude of the effects measured in this work can be used as a guide for how to adapt the adsorption process for different process conditions. The results also indicated that natural sepiolite is a suitable adsorbent for NR.

A statistical analysis of GPS positioning using experimental design

In dam, bridge, railway, sewerage and pipeline projects and the measurement of crustal movements, point positioning must be determined. GPS is the most popular three-dimensional absolute positioning system on all world surfaces; however, the accuracy of GPS measurements is dependent on particular measurements or environmental factors. The main aim of this study is to characterize statistically the effects of selected factors on the individual GPS horizontal and vertical positioning. The factors were the measurement seasons and time of day for the environment aspect and the satellite system for the measurement aspect. A

Adsorption of copper and zinc ions on illite: Determination of the optimal conditions by the statistical design of experiments

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Performance Measurement of Mining Equipments by Utilizing OEE

23 factorial design was utilized to analyze the role of the selected factors in the GPS horizontal and vertical point positioning. The results indicated that the level (2nd season of the year) of measurement season gave the optimum conditions on the accuracy of the horizontal and vertical positioning, this situation could not be obtained for the same level of measurement time and satellite system. Therefore, the measurements factors of horizontal and vertical positioning must be selected and analyzed carefully according to aim of study.