Electropolishing at high current densities without agitation of the electrolyte results in a pitting phenomenon that produces dimple-like surface features. Although pitting is unfavorable in the electropolishing process, its effect on surface modification, such as surface texturing, has not been thoroughly investigated. Surface topography and chemical composition analyses of electropolished steel revealed surface pits and an oxide surface layer, indicating the presence of surface texture and coating. The resulting surface is characterized by negative skewness and high kurtosis values. The tribological behavior of the electropolished steel-bronze pair is investigated by evaluating coefficients of friction and bronze wear using sliding tests conducted in mixed and boundary lubrication regimes. The results are compared to those of the ground steel-bronze pair. In the mixed and upper range of the boundary lubrication regime, coefficients of friction reduction up to 30% and shorter running-in phases are observed for electropolished steel (electropolished steel μ_avg = 0.019 vs. ground steel μ_avg = 0.028). In contrast, the coefficient of friction increased in the lower range of boundary lubrication regime by 50% (electropolished steel μ_avg = 0.098 vs. ground steel μ_avg = 0.065). Electropolishing, as a cost- and time-effective method applicable to complex geometries, presents an alternative method for achieving surface modifications aimed at friction reduction and improved tribological behavior for non-conformal contacts in the boundary and mixed lubrication regimes.

Electropolishing using a high-current density results in a pitting phenomenon, producing a surface texture distinguished by many pits. Apart from the change in surface topography, electropolishing forms an oxide surface layer characterized by beneficial tribological properties. This paper introduces surface texturing in worm gear pairs by electropolishing a 16MnCr5 steel worm surface. Electropolishing produces surface pits 1 μm to 5 μm deep and 20 to 100 μm in diameter. The material characterization of 16MnCr5 steel is compared against the electropolished 16MnCr5 steel based on microstructure, hardness, surface topography and chemical composition. Experimental tests with worm pairs employing electropolished worms are conducted, and the results are compared to conventional worm pairs with ground steel worms. Electropolished worms show up to 5.2% higher efficiency ratings than ground ones and contribute to better running-in of worm gear pairs. Moreover, electropolished worms can reliably support full contact patterns and prevent scuffing due to improved lubrication conditions resulting from the produced surface texture and oxide surface layer. Based on the obtained results, electropolishing presents a promising method for surface texturing and modification in machine elements characterized by highly loaded non-conformal contacts and complex geometry.

In this study, a multi-objective optimization procedure with embedded topology optimization was presented. The procedure simultaneously optimizes the spatial arrangement and topology of bodies in a multi-body system. The multi-objective algorithm determines the locations of supports, joints, active loads, reactions, and load magnitudes, which serve as inputs for the topology optimization of each body. The multi-objective algorithm dynamically adjusts domain size, support locations, and load magnitudes during optimization. Due to repeated topology optimization calls within the genetic algorithm, the computational cost is significant. To address this, two reduction strategies are proposed: (I) using a coarser mesh and (II) reducing the number of iterations during the initial generations. As optimization progresses, Strategy I gradually refines the mesh, while Strategy II increases the maximum allowable iteration count. The effectiveness of both strategies is evaluated against a baseline (Reference) without reductions. By the 25th generation, all approaches achieve similar hypervolume values (Reference: 2.181; I: 2.112; II: 2.133). The computation time is substantially reduced (Reference: 42,226 s; I: 16,814 s; II: 21,674 s), demonstrating that both strategies effectively accelerate optimization without compromising solution quality.

The idea of the project was to find a conceptual design of a multi-functional smart orthosis for wrist fixation. The application of additive technologies presents the potential in designing a customised orthosis for every patient individually. By using pre-generated 3d models of various hand shapes it is possible to prepare models for several shapes and sizes of forearms and hands. The conceptual design provides a possible solution for a two-part orthosis bound around the forearm and a modular extension to stabilize the wrist without additional compression. The multi-functionality occurs with the development of a small pre-defined electronic plate located in the bottom part of the orthosis. The temperature and heart rate are constantly monitored and displayed wirelessly on a smartphone. The target group are the patients active in sports or patients with minor injuries. Moreover, the orthosis can be used for body temperature and heart function monitoring during recovery period.

Gateway engineering courses often expose accumulated gaps in students’ foundational knowledge, affecting progression and retention. This study investigates early predictors of completion and performance in Machine Elements, an integrative second-year mechanical engineering course at the University of Zagreb. A retrospective cohort dataset of 2351 students enrolled between 2013 and 2021 was analysed using admission variables, first-year course grades, and exam-attempt indicators. Cohort differences were examined with descriptive statistics and non-parametric tests, while course completion was modelled using logistic regression, LASSO-based predictor selection, and temporal validation. Students who completed the course differed most consistently from non-completers in Strength of Materials performance and prerequisite exam attempts. A reduced five-predictor model retained most of the full model’s predictive ability, achieving ROC AUC = 0.749 in the pooled sample and 0.726 in temporal validation. Intervention-oriented evaluation showed that Top-K risk selection provided high precision but low sensitivity under limited support capacity.