Machinery - Repository of the Faculty of Mechanical Engineering, University of Belgrade
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Classification of offshore oil and gas plants
No full textOil and gas plants can be classified into onshore and offshore plants, colloquially called oil and gas platforms, or simply oil platforms. Oil rigs represent an enormous feat of engineering developed from over 150 years of industrial expertise. This paper shows the classification of oil and gas
platforms according to their structures and purposes, and describes the types of oil platforms, their structure, advantages and disadvantages
An Equivalent of Schwarz lemma and its Generalizations and Applications
No full textThe Schwarz lemma is one of the most influential results in complex analysis and it has a great impact to the development of several research fields, such as geometric function theory, hyperbolic geometry, complex dynamical systems, and theory of quasi-conformal mappings. It means that any holomorphic function f of the unit disc into itself such that f(0) = 0 maps each disc centered at zero into a smaller one. Moreover it maps each disc with center at zero into a strictly smaller disc if it is not a rotation. In first part of this talk will be presented a brief survey of results of Academician Mateljevi´ c which is connected with Schwarz lemma.
In second part of this talk will be proved one fixed point result from [1], which is equivalent with Schwarz lemma. Some generalizations and applications of this result will be also presented
RECENT ADVANCES IN THE FIELD OF BEEHIVE TEMPERATURE MONITORING
No full textThe most significant pollinator insect is the honey bee (Apis mellifera), which also provides honey and other
valuable products. The goal of smart apiculture is to assist beekeepers in remotely monitoring honey bee
colonies and recognising various colony states. Given that swarming can significantly reduce productivity, one
of the monitoring objectives through temperature measurement is the remote identification of this
phenomenon. Experiments show that before swarming, there is a warm-up phase of 1.5–3.4°C, approximately
20 minutes before takeoff, which varies from the usual range of 34–35°C in beehives. The temperature of
beehives was significantly impacted by the presence of bees. Hives missing bees had mean temperatures that
were 5.5°C lower and had wider temperature variations than hives with bees. Regardless of colony strength,
hives without bees attain their highest temperature earlier than hives with bees. Using wireless sensing
technologies, this apiculture method could be applied to monitor various bee colony parameters in real-time.
This would improve the detection of colony collapse disorder (CCD), which is an important issue in managing
the honey bee population. Machine learning algorithms are developed to predict temperature fluctuations in
bee colonies using daily thermal patterns with a root mean square error (RMSE) of less than 0.5%
Measuring Reliability and Validity of Operator - Mining Machine System’s Characteristics
No full textMining is widely recognized as a high-risk industry with elevated accident rates, yet the ergonomics and safety issues of machinery in open-pit mining operations remain underexplored in previous research. Therefore, this paper aims to examine the reliability and validity of the characteristics of operator-mining machine systems, based on a questionnaire survey conducted among operators in several Serbian open-pit mining companies. Descriptive statistics were first applied to analyse operators’ and machines’ characteristics. Reliability analysis using Cronbach's Alpha identified and eliminated three questions that did not meet acceptable thresholds. Factor analysis was performed to assess construct validity, and after analysis, one questionnaire item has been removed. The final set of questions was grouped into four groups, each containing one or two components, establishing the instrument’s reliability and validity. This research contributes to the understanding of ergonomic characteristics of operator-mining machine systems and shows that factors such as seat adjustability characteristics, armrests adjustability, vibrations in the cabin, and hand- and foot-operated controls are significant in providing a foundation for improving workplace conditions in open-pit mining environments. These results lay the groundwork for future research, such as regression analysis and/or confirmatory factor analysis, or further studies with larger samples
Organizational Resilience Assessment as the Indicator of the Sustainable and Human-centric Industrial Organizations Transformation
No full textIndustry 4.0 brought digitalization to every aspect of the industrial manufacturing processes. Based on the rapid development, besides being accepted as major promoter of the industrial development, Industry 4.0 evoked many controversies, mainly expressed through strong opposition to the related digitalization of the processes, based on the employees’ fear and lack of adequate organizational communication. Based on those circumstances, contemporary manufacturing operations are being transformed from a digital to a post-digital era, in the frame of Industry 5.0 concept. In this concept, post-digital processes are equally concerned with digitalization and with employees’ opinion on their workplace’s conditions and overall business success. In this research, the main focus is placed on the organizational resilience index (RI) assessment in the mining industry organizations, evaluated through the assessment of the employee’s opinion on the most important influencing factors, belonging to the: technical, human, organizational and sustainability, groups. In the assessment, the employees of all organizational levels, including: machinery operators, support workers, operational, middle and top-level managers were included. Methodology for RI calculation included application of MCDA techniques, supplemented by the Fuzzy Logic and additionally boosted by artificial intelligence – through Artificial Neural Networks implementation. Obtained models enable accurate calculation of the organizational RI, and possibility to its prediction, based on the measured influential factors.Plenarni ra
ADITIVNE TEHNOLOGIJE KAO ALAT ZA UNAPREĐENJE PROCESA INJEKCIONOG PRESOVANJA
No full textU današnjem industrijskom okruženju, zahtevi za poboljšanjem kvaliteta proizvoda, većom efikasnošću procesa i potrebom za malim serijama uz smanje troškova, postavljaju izazove proizvođačima plastičnih proizvoda. Aditivne tehnologije, nude rešenja koja omogućavaju bržu izradu prototipa, prilagođavanje dizajna, a u poslednjih nekoliko godina i direktnu izradu alata. U početku ove tehnologije su bile limitirane samo na mali broj pretežno polimernih materijala pravljenih posebno za svrhu izrade prototpiova, međutim danas je spektar materijala značajno proširen i naročiti akcenat se stavlja na metalne materijale i temperaturno otporne polimere. U ovom radu biće analizirana mogućnost upotrebe aditivnih tehnologija za optimizaciju alata za injekciono presovanje na primerima upotrebe konformnih kanala za hlađenje kod metalnih alata, kao i fabrikaciju polimernih umetaka za izradu malih serija
UTICAJ PROMENE PARAMETARA NA MEHANIČKA SVOJSTVA PROIZVODA DOBIJENIH ADITIVNIM TEHNOLOGIJAMA
No full textSa razvojem tehnologije, aditivne metode proizvodnje nalaze sve veću primenu u izradi delova složene geometrije. Izbor materijala mora biti usklađen specifičnoj primeni i potrebnim mehaničkim svojstvima. Ova studija prikazuje rezultate eksperimentalnog testiranja 3D štampanih uzoraka, s ciljem evaluacije mehaničkih svojstava materijala koji imaju najširu primenu u 3D štampanju FDM tehnologijom, fokusirajući se na svojstvo elastičnosti i zateznu čvrstoću. Među materijalima istakao se PLA, demonstrirajući najviše vrednosti elastičnosti i zatezne čvrstoće. Imajući to u vidu, odabran je za dalja istraživanja uticaja temperature mlaznice i broja zidova na njegovo mehaničko ponašanj
Mechanical Properties Variation Due To Building Orientation of ABS Resin Material
No full textConsidering that additive manufacturing technology, has evolved significantly over the past few decades, understanding of materials mechanical properties became important part of researches with the goal of further improvement of production Among the seven different AM technologies, in this research is used digital light processing (DLP) 3D printing process with LCD projector. The thermoplastic polymer material acrylonitrile butadiene styrene (ABS) is a widely used material for 3D plastics printing, and in this study, it is chosen in the resin form. So far, this type of material has not been sufficiently studied, and the aim of this study was to determine the mechanical properties for two different specimens’ building orientations (45° and 90°). Specimen’s geometry is chosen according to the respective standards for mechanical testing’s. Because of the difficulties and warping which occur when printing the flat, thin and long specimens, orientation ‘on edge’, i.e., 90° is chosen, as well as the 45° orientation, for comparison. Tensile, three point bending and compression mechanical tests were performed and Matlab is used to create stress-strain curves. Additionally, microscopy is performed for more comprehensive insight of the behaviour of the ABS resin printed via DLP-LCD technology. Comparison of mechanical properties for two orientations leads to the overview of printing parameters which result in better mechanical properties regard to specific application. Better behaviour and compression mechanical properties are noticed in 90° orientation printed ABS resin specimens, compared to 45° ones, while flexure behaviour of ABS is the same regardless to building orientation
Artificial Intelligence Methods On Sustainable Path In The Function of Energy Efficiency Increase
No full textArtificial intelligence (AI) methods have emerged as pivotal tools in the quest to
enhance energy efficiency across diverse sectors. This research presents the
multifaceted applications of AI methods and models and their transformative
impact on optimizing energy consumption, reducing energy consumption and
fostering sustainability. One of the primary applications of AI in energy efficiency
lies in predictive analytics. Machine learning algorithms analyse vast datasets,
including historical energy consumption patterns, weather data, and operational
parameters, to forecast future energy demand accurately. These predictive
models enable proactive decision-making, allowing stakeholders to anticipate
fluctuations in energy usage and adjust operations accordingly, thereby
minimizing waste and optimizing resource allocation. Furthermore, AI-driven
optimization models play a crucial role in maximizing energy efficiency. By
formulating complex optimization problems and considering various constraints
and objectives, such as cost minimization, demand satisfaction, and emission
reduction, these models identify optimal solutions for energy-intensive processes.
Whether it's scheduling energy-intensive tasks, optimizing energy distribution in
smart grids, or designing energy-efficient building systems, AI optimization
methods and models offer unprecedented opportunities to enhance efficiency and
sustainability
Analiza loma ortotropnog rotirajućeg hiperboličkog diska sa krutim štapom
No full textThe main objective of the problem is to evaluate the stresses and displacement in an orthotropic hyperbolic spinning disc equipped with a stiff rod that has a changeable density parameter. The methodology of transition theory developed by B.R. Seth is applied to simplify the governing differential equation of the considered physical problem. This theory has the advantage of taking the material's nonlinear character into account. Based on the stress analysis of rotating discs composed of various orthotropic materials, the following conclusions are reached: the angular velocity is maximal in the convergent disc made of topaz material (orthotropic) in elastic state, but in the plastic state angular velocity is maximal for divergent disc of steel. When compared to other materials under consideration, the diverging disc constructed of barite has the largest stresses in the elastic state and compressive fully plastic stresses are the highest in the diverging disc of topaz at the outer surface. Based on all numerical calculations and graphs it is observed that the convergent disc of topaz is a better option for the designing purpose compared to the other materials.Osnovna svrha zadatog problema sastoji se u proračunu napona i pomeranja ortotropnog hiperboličkog rotirajućeg diska sa krutim štapom, promenljivog parametra gustine. Primenjena je metodologija prelaznih napona, koju je razvio B.R. Seth, radi pojednostavljenja date polazne diferencijalne jednačine zadatog fizičkog problema. Prednost ove teorije je uzimanje u razmatranje nelinearnih karakteristika materijala. Na osnovu naponske analize rotirajućiih diskova sačinjenih od raznih ortotropnih materijala, dolazi se do sledećih zaključaka: ugaona brzina je maksimalna u konvergentnom disku od materijala topaza (ortotropan) u elastičnom stanju, dok je ugaona brzina u plastičnom stanju maksimalna kod divergentnog diska od čelika. Poređenjem ostalih razmatranih materijala, kod divergentnog diska od barita se javljaju najveći naponi u elastičnom stanju, a pritisni potpuno plastični naponi su najveći kod divergentnog diska od topaza na spoljnoj površini. Na osnovu svih numeričkih proračuna i grafičkih prikaza uočava se da je konvergentni disk od topaza pogodnija opcija u projektovanju u odnosu na ostale materijale.Naveden je glavni i odgovorni urednik časopisa "Integritet i vek konstrukcija" (Structural Integrity and Life