Seminar for
DECISION MAKING – THEORY, TECHNOLOGY AND PRACTICE

 

PROGRAM

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Plan rada Seminara Odlučivanje - teorija, tehnologija, praksa za SEPTEMBAR 2024.

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Četvrtak, 03.10.2024. u 13:00, Pariske Komune bb, Niš i Online
Ivana Petkovski, Mathematical Institute of the Serbian Academy of Sciences and Arts
STRUCTURING THE DEVELOPMENT FACTORS OF THE DIGITAL SOCIETY USING MACHINE LEARNING
Using advanced statistical models, this investigation examines the impact of sustainability factors on digital development in the 21st century. It identifies key indicators shaping digital society and explores the influence of technological factors on globalization. The research covers three models: two analyzing the impact of sustainability factors on digitalization and one assessing the effect of technological factors on globalization. Methods include nonlinear polynomial regression, artificial neural networks, and partial least squares structural equation modeling. The findings highlight the significant positive relationship between education, economy, and energy on digital development, whereas environmental factors show a negative relationship. Additionally, the study reveals how digitalization, science, and ICT trade positively affect globalization, with notable differences between market and transition economies. This research offers new models and insights into the dynamics of digitalization and globalization.

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Četvrtak, 10.10.2024. u 13:00, Online
Saikat Ranjan Maity, National Institute of Technology Jamshedpur, Jharkhand, India
COATING MATERIAL SELECTION & PARAMETRIC OPTIMIZATION: A DECISION-MAKING APPROACH
Tool steels are alloy steels that play an important role in the tooling industries, where they manufacture tools and dies for different applications, namely sheet metal forming, forging, etc. Generally, two different tool steel (cold and hot work) are used for this two-metal forming process with different hardness. The present work has proposed hot work tool steel for sheet metal operation (cold work tool steel used in general), namely punching and bolt-hole coining. To meet the aim of this study, the wear behaviour of hot work and cold work tool steels were compared. Both the tool steels were heat treated to have a similar hardness. Wear results showed similar wear behaviour at low sliding velocity and applied load for both tool steels. As the sliding velocity increases from 0.20 m/s to 0.25 m/s, the wear rate of cold work steel increases rapidly, whereas no severe changes are observed in the wear rate of hot work tool steel. Microgrooves with plastic deformation, micro-cracks, adhesion, and oxidation were the dominant wear mechanisms for both tool steels. Sometimes, it was noticed that this hardness was insufficient for longer duty hours under fluctuating working conditions (contact stress, sliding behaviour, friction coefficient and contact temperature). Thus, another surface modification was employed to improve tool steel's surface properties (hardness and wear).
In this work, a total of eight different thin films were investigated, each having excellent properties at their condition. However, selecting the best thin film from the above directory is tedious. Hence, the present study has applied a fuzzy integrated MARCOS method to solve this selection problem. It was suggested that the AlCrN/TiAlN coating was the best thin film for tooling application, as mentioned above. Četvrtak, 17.10.2024. u 13:00, Pariske Komune bb, Niš i Online
Aleksandra Fedajev, Technical Faculty in Bor, University of Belgrade
IMPROVING MULTI-CRITERIA DECISION MAKING (MCDM) RESULTS USING COEFFICIENT OF VARIATION, CORRELATION, AND THE BORDA RULE
The selection of appropriate indicators is critical for effective Multi-Criteria Decision Making (MCDM). When multiple indicators represent each criterion, an excessive number of indicators can compromise the clarity, quality, and objectivity of results. To address this issue, reducing the number of indicators through the coefficient of variation and the correlation coefficient is can be performed. Additionally, improving the objectivity of results (particularly relevant for macroeconomic decision-making) can be achieved by applying multiple MCDM methods. Given their diverse methodological foundations, these methods may produce significantly different results. The Borda rule offers a way to synthesize ranking results from various methods. Furthermore, the Borda rule can be applied when different sets of indicators represent the same decision-making problem. In such cases, rankings obtained by the same MCDM method for different sets of indicators can be synthesized using the Borda rule. This approach can be applied with or without weights, which can be defined in various ways depending on the research context. Hence, the aim of this presentation is to demonstrate the application of these statistical measures and the Borda rule in diverse decision-making scenarios.

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Predavanja su namenjena sirokom krugu slusalaca, ukljucujuci studente redovnih i doktorskih studija. Seminar će se održavati svakog drugog četvrtka od 13:00 - 14:00^h, CIITLAB, Elektronski fakultet Niš, Aleksandra Medvedeva 14, Niš

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