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1.
Exploring digital twins in the transport and energy fields : a bibliometrics and literature review approach
Milena Kajba, Borut Jereb, Tina Cvahte Ojsteršek, 2023, review article

Abstract: Logistics and transport are major sources of energy consumption that still rely heavily on fossil fuels. Especially in the freight sector, finding means to optimise fuel consumption and energy efficiency are increasingly important. Digital twins’ adaptation in logistics and transport is not as frequent as in production, but their implementation potential is immense. This technology can replicate real environments, allowing verification of various scenarios without real-life application, leading to optimal implementation outcome faster and more efficiently. This paper aims to research digital twins’ use in logistics and transport, focusing on digital twins’ potential and effects to optimise energy consumption. Firstly, previous research on digital twins in specified fields was identified, followed by a quantitative literature review. The latter focused on codifying the selected publications based on criteria such as modality, specific environment, energy consumption, etc. Furthermore, a qualitative overview of 57 relevant publications on digital twins’ use in logistics and transport was made. The main contribution of this paper is the systematic overview of digital twins from the viewpoint of energy optimisation in one of the most energy-dependent sectors. This gives researchers a good starting point for further research and digital twins’ practical implementation cases.
Keywords: logistics, transport, digital twin, energy consumption, optimisation, literature review, bibliometrics
Published in DKUM: 22.04.2024; Views: 45; Downloads: 5
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2.
Reduction of surface defects by optimization of casting speed using genetic programming : an industrial case study
Miha Kovačič, Uroš Župerl, Leo Gusel, Miran Brezočnik, 2023, original scientific article

Abstract: Štore Steel Ltd. produces more than 200 different types of steel with a continuous caster installed in 2016. Several defects, mostly related to thermomechanical behaviour in the mould, originate from the continuous casting process. The same casting speed of 1.6 m/min was used for all steel grades. In May 2023, a project was launched to adjust the casting speed according to the casting temperature. This adjustment included the steel grades with the highest number of surface defects and different carbon content: 16MnCrS5, C22, 30MnVS5, and 46MnVS5. For every 10 °C deviation from the prescribed casting temperature, the speed was changed by 0.02 m/min. During the 2-month period, the ratio of rolled bars with detected surface defects (inspected by an automatic control line) decreased for the mentioned steel grades. The decreases were from 11.27 % to 7.93 %, from 12.73 % to 4.11 %, from 16.28 % to 13.40 %, and from 25.52 % to 16.99 % for 16MnCrS5, C22, 30MnVS5, and 46MnVS5, respectively. Based on the collected chemical composition and casting parameters from these two months, models were obtained using linear regression and genetic programming. These models predict the ratio of rolled bars with detected surface defects and the length of detected surface defects. According to the modelling results, the ratio of rolled bars with detected surface defects and the length of detected surface defects could be minimally reduced by 14 % and 189 %, respectively, using casting speed adjustments. A similar result was achieved from July to November 2023 by adjusting the casting speed for the other 27 types of steel. The same was predicted with the already obtained models. Genetic programming outperformed linear regression.
Keywords: continuous casting of steel, surface defects, automatic control, machine learning, modelling, optimisation, prediction, linear regression, genetic programming
Published in DKUM: 25.03.2024; Views: 150; Downloads: 9
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3.
Optimizing smart manufacturing systems using digital twin
Robert Ojsteršek, Aljaž Javernik, Borut Buchmeister, 2023, original scientific article

Abstract: Presented paper investigates the application of digital twins for the optimisation of intelligent manufacturing systems and focuses on the comparison between simulation modelling results and real-world production conditions. A digital twin was created in the Simio software environment using a data-driven simulation model derived from a real-world production system. Running the digital twin in real time, which was displayed graphically, facilitated the analysis of key parameters, including the number of finished products, average flow time, workstation utilization and product quality. The discrepancies were attributed to the use of random distributions of input data in the dynamic digital twin, as opposed to the long-term measurements and averages in the real-world system. Despite the limitations in the case study, the results underline the financial justification and predictive capabilities of digital twins for optimising production systems. Real-time operation enables continuous evaluation and tracking of parameters and offers high benefits for intelligent production systems. The study emphasises the importance of accurate selection of input data and warns that even small deviations can lead to inaccurate results. Finally, the paper high-lights the role of digital twins in optimising production systems and argues for careful consideration of input data. It highlights the importance of analysing real-world production systems and creating efficient simulation models as a basis for digital twin solutions. The results encourage extending the research to different types of production, from job shop to mass production, in order to obtain a comprehensive optimisation perspective.
Keywords: smart manufacturing, digital twin, optimisation, simulation modelling, Simio, case study
Published in DKUM: 25.03.2024; Views: 134; Downloads: 7
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4.
Transient circuit simulation of arc-free current breaking by resistance rise
Dareer Bin Khalid, Michael Rock, Luigi Piegari, 2021, original scientific article

Abstract: There has been intensive research and development in the field of Circuit breakers, whether DC and AC, or low voltage and high voltage. The result of this has led to the production of highly reliable circuit breakers that accompany a built-in arc extinguishing system. However, the purpose of this study is to give the basics for arc-free current breaking with fast interruption of fault currents, e.g., in surge protective devices (SPD) for AC and DC systems, by means of a time-dependent resistor with fast rising resistance. This investigation shall illustrate how the current can be driven almost to zero with a steadily time increasing resistance, and interrupted completely without an electric arc. The basic aim of the conducted transient circuit simulations is to determine suitable time functions for the current or resistance and necessary initial and final resistances. This paper will discuss the "optimisation conditions", a switching time as short as possible, small switch-off overvoltage, and possibly an energy conversion in the resistor as low as possible is set using ATP-EMTP and analytical calculations.
Keywords: current breaking, ATP-EMTP, time-dependent resistance, optimisation, concave functions, convex functions
Published in DKUM: 13.11.2023; Views: 329; Downloads: 3
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5.
The use of differential evolution to determine maximum generation and load values in the distribution network
Eva Tratnik, Janez Ribič, Matej Pintarič, Miran Rošer, Gorazd Štumberger, Miloš Beković, 2022, original scientific article

Abstract: By integrating renewable energy sources into the existing distribution network, the characteristics and local stability of the network is highly impacted. The network, which was built with the goal of a directed energy flow from large conventional sources connected to the transmission network via the distribution network to consumers, can change the direction of the energy flow. The adoption of environmental commitments and directives encourages the integration of local dispersed energy sources, which can worsen voltage conditions in the distribution network. To avoid excessive local production, distribution network operators must limit the installation of new generati on units, as it is necessary to take into account the quality of power supply by monitoring its network parameters, such as the appropriate voltage profi le and the rati o between acti ve and reacti ve power. On the other hand, excessive loads due to the mass transiti on of household heati ng and transport towards electricity can also pose a problem for high-quality electricity supply due to the excessive voltage drop. The arti cle presents an algorithm for determining the maximum size of unit producti on and the maximum load at a node in the distributi on network. Also demonstrated is the use of variable tap transformer technology, which adjusts the tap of the transformer to provide an appropriate voltage profi le in the network. The enti re analysis was performed on a model of a real medium-voltage network, in which solar and hydropower plants are already included. The model was verifi ed by comparing its calculated values with actual measurements. The goal was to determine the size of the unit’s maximum producti on, as well as the size of the maximum load, by using the diff erenti al evoluti on algorithm, while keeping voltage profi les within the permissible limits. The results of the analysis are presented in the article.
Keywords: distribution network, renewable energy sources, optimisation method, voltage profile
Published in DKUM: 30.10.2023; Views: 306; Downloads: 11
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7.
Energy consumption and grid interaction analysis of electric vehicles based on particle swarm optimisation method
Klemen Deželak, Klemen Sredenšek, Sebastijan Seme, 2023, original scientific article

Abstract: The widespread adoption of electric vehicles poses certain challenges to the distribution grid, which refers to the network of power lines, transformers, and other infrastructure that delivers electricity from power plants to consumers. This higher demand can strain the distribution grid, particularly in areas with a high concentration of electric vehicles. Grid operators need to ensure that the grid infrastructure can handle this additional load and prevent overloading and consequences in terms of additional losses. As part of the task, a methodology was developed for the assessment of the electricity consumption of battery electric vehicles in Slovenia. The approach used for the calculation includes the number of electric cars, average consumption, distance travelled and efficiency of the system. Additionally, the results of the modelling approach for an integrated distribution grid model in terms of steady-state simulations are presented. The regular situation of the power losses within the distribution grid is managed together with an optimal result. In this sense, an application of the particle swarm optimisation-based strategy is suggested to minimise reliance on grid systems.
Keywords: electric vehicles, distribution grid, optimisation, power losses
Published in DKUM: 10.10.2023; Views: 276; Downloads: 17
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8.
Editorial: combined water and heat integration in the process industries
Elvis Ahmetović, Ignacio E. Grossmann, Zdravko Kravanja, François Marechal, Jiri Klemeš, Luciana E. Savulescu, Dong Hongguang, 2022, preface, editorial, afterword

Abstract: Water and energy are resources that are used in large quantities in different sectors (domestic, agricultural, and industrial). Based on data on global water and energy consumption in the world over the recent past, as well as forecasts for the coming years, a continuous trend of increasing water and energy consumption can be observed. ...
Keywords: water integration, heat integration, systematic methods, pinch analysis, mathematical programming, heat-integrated water networks, optimisation, process industry
Published in DKUM: 18.08.2023; Views: 312; Downloads: 20
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9.
Simulated global empty containers repositioning using agent-based modelling
Alaa Abdelshafie, Bojan Rupnik, Tomaž Kramberger, 2023, original scientific article

Abstract: Due to an ever-increasing movement of containers across the globe in line with the economic boom, the trade imbalance and issues related to empty containers have become inevitable. Empty containers accumulated at specific ports cannot only generate profit but also increase the environmental footprint. This research proposes a Maritime Empty Container Reposition Modelling Framework by integrating the agent-based modelling (ABM) paradigm to model the global movements of empty containers. An agent-based maritime logistic empty container redistribution model was developed to help minimize the total relevant costs for empty container movement in the planning horizon. In the system, ports, shipping companies, customers, and empty containers were identified as critical agents. Using simulated annealing (SA), shipping line agents were able to optimise empty container repositioning to determine the best sequence for moving containers. The model was applied to the Asia–Middle East region to simulate global empty containers repositioning in the region. The results comparison shows that the proposed optimised empty container repositioning framework can significantly reduce the shipping line’s costs and make full use of empty containers
Keywords: maritime industry, empty containers, repositioning, agent-based modelling, simulation, optimisation
Published in DKUM: 02.08.2023; Views: 281; Downloads: 23
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10.
Considering IT trends for modelling investments in supply chains by prioritising digital twins
Milena Kajba, Borut Jereb, Matevž Obrecht, 2023, original scientific article

Abstract: Supply chain disruptions and challenges have and will always exist, but preparing in advance and improving resilience for the upcoming consequences should be the utmost important goal. This paper explores trends that affect innovation in the technological sphere of supply chain systems. More precisely, the research is focused on Digital Twin technology applicability through other logistics IT trends and aims to research the pressing issue of ensuring the visibility and resilience of future supply chain systems. The paper’s objective is to produce a conceptual model enabling the investment assessment of the necessary IT resources. Initially, a theoretical confirmation of logistics IT trends’ relevance to supply chain systems was established. After, propositions of Digital Twin technology applications to other logistics IT trends were made, which were divided into corresponding constant multitudes of supply chain systems. Lastly, the conceptual model for the investment assessment of the necessary IT resources was derived in the form of a matrix. It considers 16 parameters for investment assessment and applicability to all companies, regardless of their specifics. It also supports the notion of digital IT competencies’ fundamental importance to the continuous operation of supply chain systems.
Keywords: supply chain management, logistics, process optimisation, visibility, resilience, Digital Twin
Published in DKUM: 03.04.2023; Views: 458; Downloads: 56
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