1. Assembly transport optimization for a reconfigurable flow shop based on a discrete event simulationS. L. Yang, 2020, original scientific article Abstract: Reconfigurable Manufacturing Systems (RMSs) are widely used to produce small batches of customized products in the current manufacturing environment. We comprehensively optimized the assembly transport strategy, production process, and production configuration of a reconfigurable flow shop (RFS). Firstly, three assembly transfer strategies, one-to-one, one-to-many, and many-to-many, are proposed for an RFS, given the specific process limitations. In addition, a production simulation model of the RFS is established by the Plant Simulation software to verify and compare those three strategies with realistic production constraints considered. Moreover, the production processes are optimized, and the optimal buffer configuration and vehicle configuration are optimized by the design of experiment (DOE) method. After the optimization processes, the throughput and facility utilization under each strategy increases significantly. Additionally, the optimal buffer size and vehicle quantity under each strategy are determined and compared. The one-to-one strategy can maximize the production output, but it requires the most production resources. In addition, the many-to-many strategy is more efficient than the one-to-many strategy. Our study provides a variety of assembly transport strategies for an RFS and offers an efficient optimization method for production performance and production configuration.
Keywords: Reconfigurable Manufacturing Systems, discrete event simulation, assembly transport strategy, optimization, plant simulation, reconfigurable flow shop, production configuration, simulation modelling
Published in DKUM: 13.01.2026; Views: 0; Downloads: 0
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2. Zero waste initiatives in Slovenian municipalities : a material flow and life cycle assessment analysesKristijan Brglez, Rebeka Kovačič Lukman, Roman Gumzej, 2025, original scientific article Abstract: The European Union (EU) has implemented several strategies, including the zero-waste initiative, to minimize waste generation and enhance resource efficiency. Slovenia demonstrates this policy with the “Zero Waste Municipalities” project, which has shown notable success, but also highlights opportunities for further improvement. This study assesses the effectiveness of zero-waste initiatives and municipal solid waste management (MSWM) strategies across Slovenian municipalities using Material Flow Analysis (MFA) and Life Cycle Assessment (LCA). MFA results from eight municipalities indicate that biowaste (averaging 42.49 %) and paper (21.78 %) constitute the largest fractions of collected municipal waste. LCA results highlight that, on a per capita basis, environmental impacts in urban areas are generally lower than in rural areas for glass, wood, biowaste, and plastic waste streams, but higher for metal and paper. Scenario modelling for Ljubljana demonstrates that meeting the EU recycling targets for 2025 and 2030 would lead to substantial reductions in environmental impacts—especially in terms of Global Warming Potential (GWP) and Abiotic Depletion Potential (ADP). Specifically, achieving the 2030 targets could reduce CO 2 emissions from paper, plastic, and wood waste by 52 %, 25 %, and 77 %, respectively, compared to current baseline recycling ratios. The integration of MFA and LCA provides a comprehensive and quantitative assessment and insight into current waste management practices in Slovenian municipalities, accelerating a transition towards zero waste and circular municipalities. The findings offer valuable information for decision-makers, researchers and stakeholders aligning local waste management strategies with broader EU objectives.
Keywords: zero waste initiatives, material flow analysis, life cycle assessment, municipal solid waste management, environmental impacts, Slovenia
Published in DKUM: 19.12.2025; Views: 0; Downloads: 0
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3. Analysis of gas flow distribution in a fluidized bed using two-fluid model with kinetic theory of granular flow and coupled CFD-DEM: a numerical studyMatija Založnik, Matej Zadravec, 2025, original scientific article Abstract: Fluidized bed systems are widely used in chemical and process engineering due to their excellent heat and mass transfer properties. Numerical modeling plays a crucial role in understanding and optimizing these systems, with the two-fluid model enhanced by the kinetic theory of granular flow (TFM-KTGF) and the coupled computational fluid dynamics-discrete element method (CFD-DEM) emerging as leading techniques. This study employs both models to simulate gas-solid interactions and evaluates their performance using a benchmark single-spout fluidized bed case validated against experimental data. Subsequently, the influence of particle presence on gas flow distribution through a non-uniform distribution plate is analyzed. The results show that the common assumption of proportional flow distribution based on the opening area fraction is inaccurate, particularly in the presence of particles. Both numerical models capture this behavior, with TFM-KTGF showing trends comparable to the coupled CFD-DEM approach but at significantly reduced computational cost. The findings highlight the importance of accounting for particle dynamics in distribution plate design and promote the TFM-KTGF approach as a promising alternative for large-scale simulations.
Keywords: fluidized bed, distribution plate, two-fluid model with kinetic theory of granular flow, coupled CFD-DEM, flow distribution
Published in DKUM: 09.12.2025; Views: 0; Downloads: 7
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4. Temporal and statistical insights into multivariate time series forecasting of corn outlet moisture in industrial continuous-flow drying systemsMarko Simonič, Simon Klančnik, 2025, original scientific article Abstract: Corn drying is a critical post-harvest process to ensure product quality and compliance with moisture standards. Traditional optimization approaches often overlook dynamic interactions between operational parameters and environmental factors in industrial continuous flow drying systems. This study integrates statistical analysis and deep learning to predict outlet moisture content, leveraging a dataset of 3826 observations from an operational dryer. The effects of inlet moisture, target air temperature, and material discharge interval on thermal behavior of the system were evaluated through linear regression and t-test, which provided interpretable insights into process dependencies. Three neural network architectures (LSTM, GRU, and TCN) were benchmarked for multivariate time-series forecasting of outlet corn moisture, with hyperparameters optimized using grid search to ensure fair performance comparison. Results demonstrated GRU’s superior performance in the context of absolute deviations, achieving the lowest mean absolute error (MAE = 0.304%) and competitive mean squared error (MSE = 0.304%), compared to LSTM (MAE = 0.368%, MSE = 0.291%) and TCN (MAE = 0.397%, MSE = 0.315%). While GRU excelled in average prediction accuracy, LSTM’s lower MSE highlighted its robustness against extreme deviations. The hybrid methodology bridges statistical insights for interpretability with deep learning’s dynamic predictive capabilities, offering a scalable framework for real-time process optimization. By combining traditional analytical methods (e.g., regression and t-test) with deep learning-driven forecasting, this work advances intelligent monitoring and control of industrial drying systems, enhancing process stability, ensuring compliance with moisture standards, and indirectly supporting energy efficiency by reducing over drying and enabling more consistent operation.
Keywords: advanced drying technologies, continuous flow drying, time-series forecasting, LSTM, GRU, TCN, deep learning, statistical analysis, optimization of the drying process
Published in DKUM: 03.11.2025; Views: 0; Downloads: 4
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5. Research on the modelling and analysis of the penetration of renewable sources and storage into electrical networksEva Simonič, Sebastijan Seme, Klemen Sredenšek, 2025, original scientific article Abstract: To address the growing integration of renewable energy sources and storage systems into distribution networks, there is a need for effective tools that can assess the impact of these technologies on grid performance. This paper investigates the impact of integrating residential rooftop photovoltaic (PV) systems and battery energy storage systems (BESSs) into low-voltage (LV) distribution networks. A stochastic approach, using the Monte Carlo method, is applied to randomly place PV systems across the network, generating multiple scenarios for power flow simulations in MATLAB Simulink R2024b. The method incorporates real-world consumer load data and grid topology, representing a novel approach in simulating distribution network behaviour accurately. The novelty of this paper lies in its ability to combine stochastic PV placement with real-world load data, providing a more realistic representation of network conditions. The simulation results revealed that widespread PV deployment can lead to overvoltage issues, but the integration of BESSs alongside PV systems mitigates these problems significantly. The findings of this paper offer valuable insights for Distribution Network Operators, aiding in the development of strategies for optimal PV and BESS integration to enhance grid performance.
Keywords: photovoltaic system, battery energy storage system, low-voltage distribution network, Monte Carlo method, power flow
Published in DKUM: 03.11.2025; Views: 0; Downloads: 10
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6. Modular flow synthesis of citric acid-coated superparamagnetic iron oxide nanoparticles : preliminary resultsSabina Vohl, Andreja Nemet, Janja Stergar, 2025, original scientific article Abstract: Superparamagnetic iron oxide nanoparticles (SPIONs) with sizes below 10 nm are biocompatible and non-toxic, making them promising for biomedical applications. To prevent their agglomeration and enhance their functionality, the nanoparticles were coated with citric acid (CA), which modifies the surface charge, improves dispersion stability, and facilitates biomedical use. In this work, a modular flow-through microreactor system was employed to synthesize and coat the nanoparticles in a single, continuous two-step process. The system enables precise control over temperature and mixing, ensuring uniform reaction conditions and minimizing hot spots. The synthesized Fe3O4 nanoparticles exhibited an average crystallite size of ~5 nm (XRD) and particle sizes of 4–6 nm (TEM). FTIR analysis confirmed the successful surface functionalization with CA, while TGA indicated a coating mass fraction of approximately 4–20 wt%, increasing with higher CA concentration. Zeta potential measurements revealed strong colloidal stability, with values around −35 mV at pH 6.5. Among the tested CA concentrations, the sample with a molar ratio of Fe3O4:CA = 1:0.25 exhibited the most favorable properties, including narrow size distribution and improved dispersion stability. These findings demonstrate that the continuous modular flow approach enables the reproducible synthesis of highly stable, sub-10 nm CA-coated SPIONs, offering promising potential for biomedical applications, particularly as magnetic resonance imaging (MRI) contrast agents.
Keywords: superparamagnetic iron oxide nanoparticles, citric acid, modular flow microreactor system, continuous synthesis, zeta potential measurements
Published in DKUM: 03.11.2025; Views: 0; Downloads: 4
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7. Investigation of the influencing parameters of the ▫$H_2O_2-assisted$▫ photochemical treatment of waste liquid from the hydrothermal carbonization process in a microreactor flow systemAleksandra Petrovič, Tjaša Cenčič, Silvo Hribernik, Andreja Nemet, 2025, original scientific article Abstract: Due to its complex composition and toxicity, the waste liquid from hydrothermal carbonization (HTC) poses a serious environmental challenge that must be addressed before disposal. In this study, the photochemical treatment of HTC liquid in a microreactor flow system was investigated. The effects of wavelength, the presence of atmospheric oxygen, oxidizing agent (H2O2) and catalyst (FeSO4), residence time and pH on the efficiency of the photo-treatment were investigated. In addition, the influence of the addition of deep eutectic solvent (DES) on photo-treatment was studied. The results showed that the photochemical treatment was more efficient at 365 nm than at 420 nm, and that the acidic conditions gave better results than the basic ones. UV365 treatment in the presence of H2O2 (at a dosage of 1 vol%) resulted in removal efficiencies of 31.6% for COD, 17.6% for TOC, 16.9% for NH4-N and 17.2% for PO4-P. The addition of FeSO4 caused coagulation/flocculation effects, but improved phosphorus removal. The addition of DES resulted in slight discolouration of the liquid and proved unsuccessful in COD removal. The GC-MS analysis and 3D-EEM spectra showed significant changes in the fate of organics and in the fluorescence intensity of aromatic proteins and humic acid-like substances. Photochemical treatment in a microreactor flow system in the presence of H2O2 under the selected operating conditions reduced the content of organics and nutrients in the HTC liquid, but the process liquids still showed toxic effects on the organisms V. fischeri and Daphnia magna.
Keywords: hydrothermal treatment, waste process liquid, photochemical treatment, hydrogen peroxide, microreactor flow system
Published in DKUM: 25.09.2025; Views: 0; Downloads: 4
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8. Improvisation as the foundation of flow in music education : connections to attitudes, gender and genreKaja Korošec, Blaženka Bačlija Sušić, Katarina Habe, 2022, original scientific article Abstract: The aim of our study was to explore the connection between improvisation and flow. Data were collected from 252 tertiary music students from Slovenia and Croatia (121 male and 131 female musicians), who filled in The Questionnaire on Attitudes to Music Improvisation, The Inventory on Feelings associated with Music Improvisation, and the Work-related Flow Inventory. The results show that the female students have significantly more negative feelings and attitudes toward improvisation, and they experience less flow while improvising. Differences were even more pronounced when comparing students who only played classical music with those who played other genres, as well. Regression analysis showed that we can explain 71% of the variance in flow with attitudes toward improvisation.
Keywords: attitudes, flow, higher music education, improvisation, music students
Published in DKUM: 25.07.2025; Views: 0; Downloads: 7
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9. Hybrid model for motorway EV fast-charging demand analysis based on traffic volumeBojan Rupnik, Yuhong Wang, Tomaž Kramberger, 2025, original scientific article Abstract: The expected growth of electric vehicle (EV) usage will not only increase the energy demand but also bring the requirement to provide the necessary electrical infrastructure to handle the load. While charging infrastructure is becoming increasingly present in urban areas, special attention is required for transit traffic, not just for passengers but also for freight transport. Differences in the nature of battery charging compared to that of classical refueling require careful planning in order to provide a resilient electrical infrastructure that will supply enough energy at critical locations during peak hours. This paper presents a hybrid simulation model for analyzing fast-charging demand based on traffic flow, projected EV adoption, battery characteristics, and environmental conditions. The model integrates a probabilistic model for evaluating the charging requirements based on traffic flows with a discrete-event simulation (DES) framework to analyze charger utilization, waiting queues, and energy demand. The presented case of traffic flow on Slovenian motorways explored the expected power demands at various seasonal traffic intensities. The findings provide valuable insight for planning the charging infrastructure, the electrical grid, and also the layout by anticipating the number of vehicles seeking charging services. The modular design of the model allowed replacing key parameters with different traffic projections, supporting a robust scenario analysis and adaptive infrastructure planning. Replacing the parameters with real-time data opens the path for integration into a digital twin framework of individual EV charging hubs, providing the basis for development of an EV charging hub network digital twin.
Keywords: electric vehicles, EV charging, traffic flow, EV charging hub
Published in DKUM: 11.04.2025; Views: 0; Downloads: 2
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10. Wear simulation of the conveyor belt transfer chute using the DEMTone Lerher, Žan Grum, Marko Motaln, Matej Zadravec, 2024, original scientific article Abstract: This paper presents a wear simulation-based performance evaluation of the conveyor belt transfer chute using the DEM (Discrete Element Method). Compared to known analytical and empirical wear models, DEM simulation can significantly increase the performance of wear analysis by enabling the analysis and optimization of highly complex geometries of material handling systems such as conveyor belt transfer chutes. Only the correct design of the conveyor belt transfer chute has the potential to significantly extend its service life, resulting in considerable cost savings. Based on the parametric analysis of different angles and radius in the upper head and lower section of the transfer chute, a new geometry of the transfer chute was proposed. The wear depth of the new conveyor belt transfer chute is compared with the wear resistant and low-carbon steel of the transfer chute along with the moderate and relatively high values of the solid granules mass flow. The results show that the wear depth of the transfer chute can be significantly reduced by using the wear-resistant steel compared to the low-carbon steel, which is significantly evident in high throughput rates of the solid granules mass flow.
Keywords: bulk material flow, Discrete Element Method (DEM), transfer chute wear simulation, archard and relative wear, performance analysis
Published in DKUM: 10.03.2025; Views: 0; Downloads: 18
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