Technical Faculty in Bor
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Impact of aging parameters on different properties of the EN AW-6082 aluminum alloy
(Mining and Metallurgy Institute Bor, 2024) Stamenković, Uroš; Marković, Ivana; Ćosović, Vladan; Markoli, Boštjan
This research investigates how the thermal, mechanical, and structural properties of the EN AW-6082 aluminum alloy are affected by aging parameters (temperature and time). To investigate these properties, thermal diffusivity and hardness were measured, and scanning electron and transmission electron microscopes were used to detect structural changes. The heat treatments consisted of solutionizing at 550 °C for an hour and then quenching in ice water, followed by aging at two different temperatures (180 °C and 200 °C) for 1-8 hours. Investigation revealed that the hardness increases gradually with aging time, reaching a maximum of 124 HV 10 after aging at 180 °C for six hours. Similarly, thermal diffusivity increases with both aging time and temperature, peaking after aging at 200 °C for five hours. An SEM/EDS analysis shows the presence of finely dispersed precipitates that contain Mg, Si, and Fe. TEM investigation confirms the existence of nanometer-sized rod-shaped precipitates believed to be the strengthening β’’ phase.
Optimization of micronizing zeolite grinding using artificial neural networks
(University of Belgrade, Technical faculty in Bor, 2024) Nikolić, Vladimir; Trumić, Milan; Tanikić, Dejan; Trumić, Maja
The micronizing grinding of natural zeolite, of the clinoptilolite type, was investigated in a ring mill. The aim of the experiment was to determine the optimal grinding conditions to obtain a powder with appropriate physico-chemical and microstructural characteristics that would find its potential application as a binder and ion exchanger in structural composites. The analysis of specific size classes of zeolite e after micronization was performed by grinding kinetics.
The research was carried out on previously prepared zeolite samples, on wider and narrower size classes (-3.35 + 0 mm;-3.35 + 2.36 mm; -2.36 + 1.18 mm; -1.18 + 0 mm) and different starting masses (50 g, 100 g, 200 g). Fine grinding was carried out at different time intervals (20 s, 45 s, 75 s, 120 s, 300 s, 900 s). A sieve analysis was performed on the grinding products, the content of the size class (-5 + 0) μm and the specific surface area of these products were determined. XRD analysis was performed on individual grinding products to take into account possible changes in the zeolite material itself. Based on the results obtained, an artificial neural network was developed and then compared with the experimental results. The artificial neural network models have achieved a satisfactory prediction accuracy (0.989 - 0.997) and can be considered accurate and very useful for the prediction of variable responses.
Examination of the TAM model external factors' influence on the perceived ease of use: The case of SAP ERP system
(University of Belgrade, Technical Faculty in Bor, 2024) Radić, Aleksandra; Arsić, Sanela; Nikolić, Đorđe
This paper examines the influence of the external factors of the Technology Acceptance Model (TAM) on the perception of SAP system usability. TAM is a theoretical framework often used to analyze technology acceptance, while the SAP system is a complex Enterprise Resource Planning (ERP) system widely used in organizations. The external factors considered in this research are system complexity, system performance, user manual, social impact and work compatibility. A questionnaire was used to analyze the data using the structural equation modeling (SEM) technique. The results show that of the five external factors mentioned, only two factors have a statistically significant influence on perceived ease of use, namely system complexity and system performance. By considering external variables, these results can provide a deeper understanding of users' attitudes towards SAP ERP. This can help to better analyze and interpret the research results and suggest more effective strategies for the implementation and adoption of the system in companies.
Development and validation of measurement instrument for green knowledge management
(University of Belgrade, Technical Faculty in Bor, 2024) Radić, Aleksandra; Jovanović, Ivan; Milijić, Nenad
Green knowledge management represents a new direction of knowledge management in organizations. As an intensively represented concept, it has awakened the interest of many researchers to examine the cause-and-effect relationships of this concept and related variables. To analyze this concept more deeply using statistical analysis methods, it is necessary to develop an instrument that will be used for measurement and analysis. In this regard, this paper describes the process of developing and validating a measurement scale for comprehensive research on green knowledge management, green technology and innovation, organizational performances, and management commitment to the ecology. Thanks to the analysis results that show that the proposed questionnaire for measuring the mentioned variables is a valid and reliable measurement scale, it can be said that the main motive of the work is fulfilled and that the result of this research has a significant contribution to the growing body of literature.
Analysis of innovation in EU countries
(University of Belgrade, Technical Faculty in Bor, 2024) Nikolić, Ivica; Stojanović, Anđelka; Radić, Aleksandra; Đorđević, Predrag
This paper explores the level of innovativeness among European Union (EU) countries through the application of the Global Innovation Index (GII) and cluster analysis methodology. The research aims to identify the key factors contributing to innovation in various EU countries and to group these countries into homogeneous cluster groups to understand their innovation performance better. Cluster analysis is employed to identify similarities among countries based on their innovation characteristics. The research results provide insight into the relative position of EU countries in the domain of innovation, identifying innovation leaders as well as those lagging behind. Cluster analysis enables the grouping of countries into cluster groups based on similarities in their innovation profiles, facilitating the identification of common challenges and opportunities for collaboration.