Digital twin-driven management strategies for logistics transportation systems

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 9, 2025

With the development of Industry 5.0, logistics industry, serving as a bridge between production and consumption, is undergoing profound changes. However, this transformation faces challenges such data fragmentation, difficult system integration, insufficient real-time monitoring capabilities. Consequently, modern demands higher standards for prediction management transportation behavior. To address these challenges, paper introduces Digital Twin (DT) technology proposes research methodology DT-driven strategies. DT constructs virtual models physical objects to enable analysis unmanned vehicle states, effectively resolving identified issues. Specifically, proposed method leverages integrate multi-source heterogeneous establishes digital model vehicles. Furthermore, it combines LSTM neural network algorithm design predictive time-series forecasting behaviors. The dynamically adjusted based on results, further optimizing strategy. Finally, effectiveness validated through case study Experimental results demonstrate that DT-based strategy significantly improves accuracy predicting behaviors exhibits superior performance in decision aid fault tolerance. Additionally, simulation tests confirm reliability efficiency improved practical applications, providing an important reference intelligent systems.

Language: Английский

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Exploring digital twins for transport planning: a review

European Transport Research Review, Journal Year: 2025, Volume and Issue: 17(1)

Published: March 13, 2025

Language: Английский

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Using Big Data for Predictive Maintenance in Transportation Systems

IGI Global eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 297 - 314

Published: April 4, 2025

The economic and social health of contemporary urban centers is greatly dependent on the transportation industry. Transportation infrastructure must be dependable efficient because any disruptions can have a domino effect mobility as whole. Predictive maintenance, facilitated by analysis big data, gives chance to proactively address maintenance needs minimize service interruptions. use data analytics for predictive in systems examined this chapter. It starts going over special sources that are available industry, such sensor from infrastructure, cars, traffic control systems. explores essential phases procedure, encompassing gathering, analysis, modeling, production practical insights. application data-driven various contexts—such public fleets, road rail networks—is demonstrated through several case studies.

Language: Английский

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Integration of Pavement Finite Element simulation with Digital Twin: Current Practices, Emerging Trends, and Future Enablers

Journal of Information Technology in Construction, Journal Year: 2025, Volume and Issue: 30, P. 544 - 569

Published: April 19, 2025

In the transition towards Construction 5.0, intelligent systems, such as predictive Digital Twins (DTs), have emerged a critical solution in infrastructure assets management. This is by leveraging advanced simulations and analytical methods for accurate asset condition prediction. However, while are essential enabling DTs, existing literature often overlooks role of pavement simulation within developed DTs. paper systematically leverages on Finite Element (FE) modelling performance prediction to assess current state practice simulations, identifies trends integration, proposes advancements enhance incorporation FE models an architecture integration. Finally, study concludes with call future research directions address gaps, aiming advance DTs sustainable

Language: Английский

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Digital Twin Technology in Logistics: A Narrative Review of Implementation, Impact, and Challenges

Sinergi International Journal of Logistics, Journal Year: 2024, Volume and Issue: 2(4), P. 225 - 238

Published: Nov. 30, 2024

The adoption of digital twin technology in logistics has gained significant traction as organizations seek to enhance supply chain transparency, operational efficiency, and predictive accuracy. This review explores how technologies improve performance, identifying what enables success challenges persist. Literature was collected through comprehensive searches Scopus Google Scholar using keyword-based Boolean strategies, with inclusion criteria focusing on peer-reviewed studies from the last decade that explicitly address applications systems. Findings reveal twins enable smarter decision-making real-time tracking tools, especially urban maritime logistics. Empirical evidence highlights substantial gains contexts. However, systemic barriers persist, including integrating legacy systems, high implementation costs, cybersecurity risks, shortages skilled professionals. Comparative insights a divide between developed developing economies, driven by disparities infrastructure institutional support. To accelerate adoption, stakeholders—especially policymakers managers—must prioritize infrastructure, workforce readiness, inclusive innovation policies. Future should cross-regional comparisons develop standardized evaluation models. Overall, holds strong promise for transforming global if supported cohesive governance, innovation, strategic investment.

Language: Английский

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