COMPARISON OF LINEAR AND NONLINEAR STATISTICS METHODS APPLIED IN INDUSTRIAL PROCESS MODELING PROCEDURE

This paper presents the comparison of Multiple Linear Regression Analysis (MLRA) and Artificial Neural Networks (ANN) as the statistical analysis tools. Most influential statistical parameters for choosing right modeling tool are evaluated in this investigation. Investigation was performed on real statistical data set obtained after measurements of the process parameters underindustrial conditions

AN ANFIS – BASED AIR QUALITY MODEL FOR PREDICTION OF SO2 CONCENTRATION IN URBAN AREA

This paper presents the results of attempt to perform modeling of SO2concentration in urban area in vicinity of copper smelter in Bor (Serbia), using ANFIS methodological approach. The aim of obtained model was to develop a prediction tool that will be used to calculate potential SO2 concentration, above prescribed limitation, based on input parameters. As predictors, both technogenic and meteorological input parameters were considered. Accordingly, the dependence of SO2concentration was modeled as the function of wind speed, wind direction, air temperature, humidity and amount sulfur emitted from the pyrometallurgical process of sulfidic copper concentration treatment

ADAPTATION OF THE HP LIFE PROGRAM FOR PROMOTION OF THE ENTREPRENEURSHIP AMONG YOUNG PEOPLE

This text is dealing with attempt of Management department, of Technical faculty in Bor, todevelop and further sustain the „entrepreneurial spirit“among young people. The subject of the paperis the HP LIFE program, in which Technical faculty in Bor is the only partner institution from Serbia.Besides up-to-date IT equipment obtained by Hewlett Packard in previous phases of this project,during 2012 this project was financially sustained by the Serbian institution „Centre for promotionof science“. This support will increase the scope of project activities during this year, including newtarget groups

Development of the Algorithm for Selection of Appropriate Numerical Modeling Approach

This paper is dealing with review of different modeling approaches, available in contemporary literature, and analyses of their applicability on real technological processes. During the theoretical discussion the scope of potential options of techniques available for complex systems modeling are presented. Both analytical and statistical modeling approaches are described. The most important part of the paper is dealing with development of the algorithm for selection of appropriate numerical modeling approach – ASANMA, based on the structure of the system and the scope of input variables of the investigated process. Presented assumptions are based on real-life examples of the numerical models of the real systems. Developed algorithm can be used by decision makers for selection of the appropriate numerical modeling approach, in the practice

Potential impact of the science - technology park on the regional development

The impact of the Science and Technology Park (STP) on the development of one region can be considered through many reasons for establishment of STPs. STP represent useful instrument which creates conditions for promoting innovations, entrepreneurship, growth of knowledge-based companies, while the output results are reflected in economic growth of the region. Due to declining demographic trends in region of eastern Serbia, especially considering young population and phenomenon of “brain drain”, the goal of STP is to provide conditions for intellectual companionship at the highest level, to create chances to exchange knowledge and ideas, to improve potential of the community and to increase knowledge and achieve suitable bilateral cooperation with similar entities in the world. This paper provides review of possible benefits of establishing STP in city of Bor, based on scientific-research potential of Eastern Serbia region

TECHNOLOGICAL PROCESS MODELING AIMING TO IMPROVE ITS OPERATIONS MANAGEMENT

This paper presents the modeling procedure of one real technological system. In this study, thecopper extraction from the copper flotation waste generated at the Bor Copper Mine (Serbia), werethe object of modeling. Sufficient data base for statistical modeling was constructed using theorthogonal factorial design of the experiments. Mathematical model of investigated system wasdeveloped using the combination of linear and multiple linear statistical analysis approach. Thepurpose of such a model is obtaining optimal states of the system that enable efficient operationsmanagement. Besides technological and economical, ecological parameters of the process wereconsidered as crucial input variables

ANFIS based prediction of the aluminum extraction from boehmite bauxite in the Bayer process

This paper presents the results of nonlinear statistical modeling of the bauxite leaching process, as part of Bayer technology for alumina production. Based on the data, collected during the year 2011 from the industrial production in the alumina factory Birač, Zvornik (Bosnia and Herzegovina), nonlinear statistical modeling of the industrial process was performed. The model was developed as an attempt to defi ne the dependence of the Al2O3 degree of recovery as a function of input parameters of the leaching process: content of Al2O3, SiO2 and Fe2O3 in the bauxite, as well as content of Na2Ocaustic and Al2O3 in the starting sodium aluminate solution. As the statistical modeling tool, Adaptive Network Based Fuzzy Inference System (ANFIS) was used. The model, defi ned by the ANFIS methodology, expressed a high fi tting level and accordingly can be used for the effi cient prediction of the Al2O3 degree of recovery, as a function of the process inputs under the industrial conditions

Multi-criteria analysis of soil pollution by heavy metals in the vicinity of the Copper Smelting Plant in Bor (Serbia)

This study highlights the consequences on soil pollution of one hund­red years of manufacturing in the Copper Mining and Smelting Complex RTB-Bor (Serbia). Soil sediments were taken via a probe from the surface layer of the soil at twelve different measuring points. The measuring points were all within 20 km of the smelting plant, which included both urban and rural zones. Soil sampling was performed using a soil core sampler in such way that a core of a soil of radius 5 cm and depth of 30 cm was removed. Subsequently, the samples were analyzed for pH and heavy metal concentrations (Cu, Pb, As, Cd, Mn, Ni and Hg) using different spectrometric methods. The obtained results for the heavy metal contents in the samples show high values: 2,540 mg kg-1 Cu; 230 mg kg-1 Pb; 6 mg kg-1 Cd; 530 mg kg-1 Ni; 1,300 mg kg-1 Mn; 260 mg kg-1 As and 0.3 mg kg-1 Hg. In this study, critical zones of polluted soil were iden­tified and ranked according to their metal contents by the multi-criteria deci­sion method Preference Organization Method for Enrichment Evaluation/Geo­metrical Analysis for Interactive Assistance – PROMETHEE/GAIA, which is the preferred multivariate method commonly used in chemometric studies. The ranking results clearly showed that the most polluted zones are at locations holding the vital functions of the town. Therefore, due to the high bioavail­abi­lity of heavy metals through com­plex reactions with organic species in the sediments, consequences for human health could drastically emerge if these metals enter the food chain

Optimization of the arsenic removal process from enargite based complex copper concentrate

Selective arsenic extraction from enargite based complex concentrate from Copper Mine in Bor (Serbia), using sodium hypochlorite as a leaching agent, was investigated in this paper. The aim was to assess the optimal conditions for the most efficient arsenic removal from the investigated concentrate, based on factorial design applied to experimentally obtained data. Five important factors with three factor levels were used as the input variables and experimentally obtained arsenic extraction yield was taken as the output variable. The first and the second final order model equations were obtained. It was found that the leaching temperature had the strongest effect on the arsenic extraction. The strongest positive interaction was between the sodium hypochlorite molar concentration and the stirring speed during extraction

Monitoring of the Surface Ozone Concentrations in the Western Banat Region

This paper presents the results of measuring the concentrations of ozone, VOCs (benzene, toluene, m- and p-xylene, o-xylene and ethylbenzene), nitrogen oxides (NO, NO2 and NOx), CO, H2S, SO2 and PM10 in the ambient air in parallel with recording the meteorological parameters: temperature, solar radiation, relative humidity, barometric pressure, wind speed and direction during the year 2009. The measurements were performed at the measuring station located within an agricultural area near the city of Zrenjanin (Serbian Banat, Serbia). The results are presented in this paper as average values in winter and summer vs. time of day, and as average daily values vs. measurement date. Several correlations of the ozone concentration vs. atmospheric observables were made, together with Principal Component Analysis. The statistical analysis of the obtained data, based on Principal Component Analysis (PCA), led to result that 80.87 % of the variance in the measured values could be described with five factors. A high level of intercorrelation of VOCs, NOx and CO was determined. These pollutants were all grouped in factor 1, which described 42.85 % of variances of the measured values. According to the VOCs/NOx and VOCs/CO ratios (which were 0.26 and 0.029, respectively), it was determined that production of tropospheric ozone is a VOCs sensitive process for the investigated region