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37th Bled eConference - Resilience Through Digital Innovation: Enabling the Twin Transition : June 9 – 12, 2024, Bled, Slovenia, Conference Proceedin
2024, proceedings

Abstract: The Bled eConference, organised by the University of Maribor, Faculty of Organizational Sciences, has been shaping electronic interactions since 1988. The theme of the 37th conference is "Resilience through digital innovation: enabling the twin transition". The theme addresses the critical convergence of digital transformation and sustainability, in line with the European Commission’s top priorities and policy initiatives. At the conference, we aim to highlight the opportunities of digital technologies that can contribute to building organisational and societal resilience, with a focus on social and environmental goals. The papers in this conference proceedings explore a range of topics including the opportunities and challenges of the twin transition, emerging technologies, artificial intelligence and data science, decision analytics for business and societal changes, digital innovation and business models, restructured work and the future workplace, digital health, digital ethics, digital education, smart sustainable cities, digital consumers, and the digital transformation of the public sector.
Keywords: resilience, digital transformation, innovation, twin transition, sustainability, digital transition, green transition
Published in DKUM: 28.05.2024; Views: 214; Downloads: 19
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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: 74; Downloads: 10
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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: 171; Downloads: 9
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The impact of changing collaborative workplace parameters on assembly operation efficiency
Klemen Kovič, Aljaž Javernik, Robert Ojsteršek, Iztok Palčič, 2024, original scientific article

Abstract: Human–robot collaborative systems bring several benefits in using human and robot capabilities simultaneously. One of the critical questions is the impact of these systems on production process efficiency. The search for high-level efficiency is severely dependent on collaborative robot characteristics and motion parameters, and the ability of humans to adjust to changing circumstances. Therefore, our research analyzes the effect of the changing collaborative robot motion parameters, acoustic parameters and visual factors in a specific assembly operation, where efficiency is measured through operation times. To conduct our study, we designed a digital twin-based model and a laboratory environment experiment in the form of a collaborative workplace. The results show that changing the motion, acoustic and visual parameters of the collaborative workplace impact the assembly process efficiency significantly.
Keywords: collaborative robot, collaborative workplace, digital twin, assembly operation, efficiency
Published in DKUM: 26.02.2024; Views: 218; Downloads: 5
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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: 478; Downloads: 58
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Data-driven supply chain operations : the pilot case of postal logistics and the cross-border optimization potential
Tanja Zdolšek Draksler, Miha Cimperman, Matevž Obrecht, 2023, original scientific article

Abstract: According to the defined challenge of cross-border delivery, a pilot experiment based on the integration of new digital technologies to assess process optimization potential in the postal sector was designed. The specifics were investigated with events processing based on digital representation. Different events were simulated with scenario analysis with the integration of the Cognitive Advisor and supported by the monitoring of KPIs. The business environment is forcing logistics companies to optimize their delivery processes, integrate new technologies, improve their performance metrics, and move towards Logistics 4.0. Their main goals are to simultaneously reduce costs, environmental impact, delivery times, and route length, as well as to increase customer satisfaction. This pilot experiment demonstrates the integration of new digital technologies for process optimization in real time to manage intraday changes. Postal operators can increase flexibility, introduce new services, improve utilization by up to 50%, and reduce costs and route length by 12.21%. The Cognitive Advisor has shown great potential for the future of logistics by enabling a dynamic approach to managing supply chain disruptions using sophisticated data analytics for process optimization based on the existing delivery infrastructure and improving business processes. Research originality is identified with a novel approach of real-time simulation based on the integration of the Cognitive Advisor in postal delivery.
Keywords: cognitive logistics, machine learning, social IoT, last mile, digital twin, supply chain digitization
Published in DKUM: 24.02.2023; Views: 625; Downloads: 58
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Industry 4.0 and the new simulation modelling paradigm
Blaž Rodič, 2017, original scientific article

Abstract: Background and Purpose: The aim of this paper is to present the influence of Industry 4.0 on the development of the new simulation modelling paradigm, embodied by the Digital Twin concept, and examine the adoption of the new paradigm via a multiple case study involving real-life R&D cases involving academia and industry. Design: We introduce the Industry 4.0 paradigm, presents its background, current state of development and its influence on the development of the simulation modelling paradigm. Further, we present the multiple case study methodology and examine several research and development projects involving automated industrial process modelling, presented in recent scientific publications and conclude with lessons learned. Results: We present the research problems and main results from five individual cases of adoption of the new simulation modelling paradigm. Main lesson learned is that while the new simulation modelling paradigm is being adopted by big companies and SMEs, there are significant differences depending on company size in problems that they face, and the methodologies and technologies they use to overcome the issues. Conclusion: While the examined cases indicate the acceptance of the new simulation modelling paradigm in the industrial and scientific communities, its adoption in academic environment requires close cooperation with industry partners and diversification of knowledge of researchers in order to build integrated, multi-level models of cyber-physical systems. As shown by the presented cases, lack of tools is not a problem, as the current generation of general purpose simulation modelling tools offers adequate integration options.
Keywords: simulation, modelling, automated modelling, Industry 4.0, Digital Twin, SME, multiple-case study
Published in DKUM: 30.11.2017; Views: 1488; Downloads: 478
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