Machinery - Repository of the Faculty of Mechanical Engineering, University of Belgrade
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Additive Technologies in the Service of Advanced Robotics and Vice Versa
No full textFor decades, since the introduction of the first industrial robot, Unimate, achieving a harmonious balance between performance and feasible robotic design has been essential. Manufacturing limitations, material availability, and sensor and actuator systems have significantly influenced robotic system design. However, since their commercial debut in 1986, additive manufacturing (AM) technologies have been revolutionizing how once-unimaginable ideas are designed, presented, and ultimately produced. This paper explores the achievements in additive manufacturing with a special focus on its application in advanced robotics. A detailed classification of existing additive technologies is presented, along with a comprehensive review of their advantages in specific robotic applications. The growing role of additive technologies in expanding robotics across industries is also discussed. Furthermore, the increasing presence of advanced robotics in households, alongside AM, is largely driven by the exponential advancement of artificial intelligence (AI). AI contributes not only to the development of control models but also to the structural design of robotic systems. As a result, robotics itself plays a crucial role in the ongoing evolution of additive technologies, a key focus of this paper. One critical aspect explored is the development of models for active vibration damping, addressing vibrations as an undesirable phenomenon in production processes. Additionally, the integration of additive technologies with robotics enhances sustainability by reducing material waste, improving energy efficiency, and enabling the use of eco-friendly materials. These innovations are already reshaping industries such as aerospace, medical robotics, and construction, where additive manufacturing enables the creation of lightweight, customized, and highly functional robotic components. Future advancements in hybrid manufacturing, multi-material printing, and AI-driven process optimization will further enhance the synergy between additive technologies and robotics, paving the way for more autonomous, efficient, and adaptable robotic systems
LBFNN algorithm for studying response of shape memory alloy oscillator under Gaussian colored noise and periodic excitation
No full textSolving the Fokker-Planck-Kolmogorov (FPK) equation is a key problem for obtaining the transient response of stochastic dynamical systems. For shape memory alloy (SMA) oscillator systems, factors such as temperature and damping coefficients can affect the safety and normal operation of the system. Therefore, this paper studies the nonlinear dynamic response of SMA oscillator under periodic and Gaussian colored noise excitation. First, the stochastic Itô differential equations and the FPK equation for stochastic SMA system under non-resonant and resonant conditions are derived using the stochastic averaging method. Subsequently, Logistic Basis Function Neural Network (LBFNN) is proposed to solve the FPK equation. In the LBFNN algorithm, a three-layer neural network is used to approximate the solution of the FPK equation. The characteristic of this method lies in transforming the process of solving the FPK equation into solving a system of algebraic equations. The stationary and transient probability density functions of the SMA oscillator under periodic and Gaussian colored noise excitation are obtained. The influence of different parameter values on the SMA oscillator is analyzed, and the correctness of the approximate analytical solutions calculated by the LBFNN is verified using the Radial Basis Function Neural Network(RBFNN). The consistency of the comparison results demonstrates the effectiveness and superiority of the LBFNN algorithm in studying SMA oscillator. The study finds that temperature, damping coefficient and noise intensity can affect the performance of SMA oscillator. This paper shows that using neural networks to study the practical application of SMA materials has good potential.(No. 451-03-137/2025-03/200105
ILC-MPC CONTROLLER FOR ROBOTIC MANIPULATORS BASED ON THE ULTRA-LOCAL MODEL
No full textThis research explores the possibility of simplifying model predictive control strategy for robotic manipulators and improving the control system’s performance with data-driven learning controllers. The main goal is to synthesize a controller that will be feasible for embedded hardware. Simplifying the robot dynamics is done using the ultra-local model method, and then new equations of motion are used to solve a nonlinear optimization problem in model predictive control. An iterative learning controller with a serial structure is added for increased performance when the given task is repetitive. Test simulation is carried out in Matlab to verify the feasibility of the proposed control system. Results of the simulation show that the proposed controller indeed manages to attenuate external disturbances and improve performance through the learning processNo. 451-03-137/2025-03/200105 from 04.02.2025;
No. 451-03-136/2025-03/20006
Recycling or Sustainability: The Road of Electric Vehicles Toward Sustainable Economy via Blockchain
No full textThis semi-systematic review paper discusses four research questions based on findings from the last 10 years: What are the crucial issues in the ongoing debate on the development of the electric vehicle (EV) concept? Where are the major conflicting points and focuses between sustainable economy and EVs? How does the mining of metals and minerals follow current zero-waste sustainability trends, and how does the prediction of the magnitude of the future demand for EV batteries guide strategic decision-making in policies throughout the globe? As it is not easy to currently predict how metals necessary for EV productions will be produced, this article suggests a strategy that is diverse regarding its approaches to shaping the sustainable mining and further development of EVs, along with the involvement of urban planning. Using broad literature and a published pool of prediction scenarios, we provide a comprehensive assessment of future EV battery raw materials development under a range of scenarios, accounting for factors such as developments in battery technology, variations in the EV fleet composition, sustainability aspects of development of second use and recycling technologies. Additionally, this paper demonstrates how blockchain technology is likely to force mineral and metal supply chains to become significantly more traceable and transparent.Project no. 451-03-136/2025-03/2000
Structural response of Autoclave due to vibrations and optimisation of its supports by spring elements
No full textThis paper will present a novel approach to supporting a piece of process equipment subjected to long-term exploitation conditions, with the main goal of improving its reliability and safety. Optimising the supports of the process equipment (in this particular case, 16 autoclaves used for coal drying) began by measuring the load at the support points. It was followed by an analysis based on good engineering practice to develop a new technical solution. The old support solution represented a rigid connection between the autoclave envelope and the supporting structure. Meanwhile, the new approach introduced spring supports, thus providing flexible connections between the Autoclave and the structure. This flexibility ensures that the load on the vessel's shell is reduced significantly and that stress distribution at the support points is uniform. Simultaneously, the load distribution in the structure's support zone is significantly more favourable. The economic benefit of such an approach and a reflection on sustainability are also discussed
Experimental and Numerical Research of 3D DLP-Printed Solid and Voronoi PLA Resin Specimens Under Tensile and Bending Loads
No full textAdditive manufacturing (AM), especially vat photopolymerization processes
such as digital light processing (DLP), enables the production of highly detailed and complex
geometries with precise material structure control. In this study, the influence of
internal structure on the mechanical properties of PLA resin specimens produced using a
DLP 3D printer is investigated. Two designs were analyzed: a fully solid structure and a
shell with a Voronoi pattern. Tensile and bending tests revealed that solid specimens exhibited
higher strength, while Voronoi structures performed better under bending loading
despite lower load-bearing capacity due to their porosity ratio. The developed numerical
model, analyzed through different numerical simulations using the Ansys 2025R01 Software
package and validated by experimental results, showed a strong correlation between
experimental and numerical results that confirmed the reliability of the developed models
for preliminary design verification. These models hold significant potential for the design
of mechanical and biomedical components, including orthopedic immobilization devices.
Microscopic analysis revealed brittle fracture in solid specimens with striations and bubbleshaped
irregularities, while Voronoi specimens exhibited fragmented surfaces with clean,
brittle failure along structural voids. Based on the results obtained, this research demonstrates
how additive manufacturing enables the optimization of mechanical properties and
material efficiency through precise control of internal structures. In the future, validated
numerical models can be used to check the preliminary designs of different components,
which will significantly reduce development costs.contract No. 451-03-136/2025-03/200105; 451-03-137/2025-03/20010
Research of flexible plum-shaped guided wave transducer circular array for damage detection of plate metal
No full textUltrasonic guided wave transducers have become a key technology in the field of structural health monitoring due to their broad detection range and high sensitivity. However, traditional rigid sensors, which are mounted on the surfaces of complex structures, face challenges relating to mechanical integration and limited electrical and design flexibility. In order to address these issues, an innovative annular flexible omnidirectional plum-shaped interdigital guided wave (IGW) transducer array was developed and integrated into an experimental setup to assess its feasibility. The plum-shaped IGW transducer is fabricated using electric field-assisted jet deposition micro–nano three-dimensional printing technology. By designing the interdigital transducer structure on a piezoelectric substrate, the transducer array exhibits both wideband characteristics and the ability to detect waves from all directions. Experimental results confirm the array’s excitation and reception capabilities, demonstrating its wideband response. The excitation bandwidth and receiving bandwidth of the transducer are 610 and 510 kHz, respectively. Moreover, build an experimental platform to test the damage location ability of the transducer array. The calculated damage coordinate has an error of 2.89 mm from the actual damage coordinate, which does not exceed the radius of the magnet (≤3 mm). The effectiveness of the IGW transducer array for damage detection in plate structures is validated through time-domain delay superposition and multiplication techniques
Mehanizmi oštećenja cevi izlaznog međupregrejača pare nastali nakon 200.000 časova eksploatacije
No full textToplotnopostojani čelik klase 12H1MF već dugo godina se koristi u našim postrojenjima za izradu
elemenata termoenergetskog sistema. Čelik 12H1MF se koristi za izradu posuda pod pritiskom, koje su izložene istovremenom dejstvu povišene temperature, kao i unutrašnjem i spoljašnjem pritisku. U ovom radu je izvršeno eksperimentalno ispitivanje koje se odnosi na vizuelnu i dimenzionu kontrolu, merenje tvrdoće, hemijsku analizu, kao i mikrostrukturnu karakterizaciju cevnog luka izrađenog od čelika 12H1MF. Cevni luk je dobijen hladnim savijanjem cevi izlaznog međupregrejača pare nakon 200.000 časova eksploatacije na temperaturi od 540°C i maksimalnom radnom pritisku od 4,6 MPa. Na osnovu dobijenih eksperimentalnih rezultata može se potvrditi da je cevni luk oštećenjen usled dejstva gasne korozije, kao i da je došlo po pojave razugljeničenja površinskog sloja materijala na spoljašnjoj površini cevi izloženoj dejstvu dimnih gasova, dok do degradacije materijala nije došlo i pored dugotrajne eksploatacije. Ispitivanjem je utvrđeno da nije došlo do pojave puzanja materijala što potvrđuje da nije narušen integritet ove cevi
Real working process of a supercharged direct-injection spark-ignition engine with multiple injection: method for calculating the effective mixture composition in the angular domain
No full textTo evaluate the effective mixture composition in a direct-injection spark-ignition (DISI) engine, a numerical simulation was developed incorporating models for fuel injection, primary and secondary liquid fuel breakup and evaporation. The primary objective is to assess the fuel evaporation state prior to combustion - a critical factor influencing heat release and pollutant formation. The Wave-Breakup Model was employed for simulating the primary breakup of liquid fuel into droplets, providing input to the Arcoumanis model for secondary breakup. A chi-squared distribution was applied to model the distribution of Sauter Mean Diameters (SMD) of the resulting atomized droplets, while breakup time parameters were derived directly from the breakup models. These parameters were then used to solve a linearly implicit system of ordinary differential equations governing the evaporation process. Initially, a single injection event was simulated as a baseline, followed by simulations of dual injection strategies. Comparative analysis was conducted on the impact of fuel split ratios, with one set of cases maintaining fixed start of injection (SOI) crank angles and another set maintaining fixed end of injection (EOI) timings
Excavator Operators’ Working Conditions and Its’ Failure Rates Prediction by Artificial Neural Network Modelling
No full textPrior studies have demonstrated the importance of maintenance in rais- AQ1
ing mining equipment performance levels together with pollution prevention and
cleaner production. However, operators’ working conditions have not been studied enough in the previous research. In that aim, in this paper, firstly, operators’ AQ2
working conditions in 10 excavators working in Serbia have been analyzed. Later
on, the study uses artificial neural networks (ANN) for developing a quantitative
model for estimating the failure rate of excavators. In order to avoid potential indirect financial losses, which sometimes exceed 15,000 euros per hour, the duration
times of 590 excavator downtimes, measured over 198 days at the Serbian mining
sites, were used as an input to the ANN. This enables the classification of failures
lasting more than an hour based on the preceding 14 days. The most common
type of downtime was found to be technological, according to a Pareto analysis
of the observed data. The findings demonstrate that the non-linear link between
excavation operations and excavator failure rates could be mapped using ANN
modeling. The results also showed that operators’ working conditions very often
have exceeded the boundaries prescribed by regulation, and the suggested ANN
model offers a precise estimate tool for predicting excavator failure rates during
the planning stage. The future research avenue is to continue monitoring working
conditions and failures and to predict in real time precisely the length of time that
an excavator would be down and to find deeper interrelations between operators’
working conditions and an excavator’s downtime