Digital twin driven intelligent manufacturing for FPCB etching production line

Computers & Industrial Engineering, Год журнала: 2023, Номер 186, С. 109763 - 109763

Опубликована: Ноя. 18, 2023

Язык: Английский

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Development of the Concept of Digital Twin of Temperature Control System of Electric Vehicles Category L

Опубликована: Янв. 1, 2025

Язык: Английский

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Review of Digital Twin in the Automotive Industry on Products, Processes and Systems

International Journal of Automotive Manufacturing and Materials, Год журнала: 2025, Номер unknown, С. 6 - 6

Опубликована: Март 24, 2025

Review of Digital Twin in the Automotive Industry on Products, Processes and Systems Heli Liu 1,2, Benjamin Zhang 1, Vincent Wu Xiao Yang Liliang Wang 1,2,* 1 Department Mechanical Engineering, Imperial College London, London SW7 2AZ, UK 2 Smart Forming Research Base, * Correspondence: [email protected] Received: 17 February 2025; Revised: 10 March Accepted: 20 Published: 24 2025 Abstract: In era digital manufacturing, technologies are rapidly revolutionising automotive industry. Among these, twin, an enabling industry 4.0 technology first introduced two decades ago, is characterised by seamless integration physical cyber realms. The twin undergoing extensive investigations within sector, covering various perspectives including design, application. By leveraging big manufacturing data captured spatially distributed sensing networks, shows capacity to create high-fidelity models actual practices, thereby significantly improving precision efficiency production processes. Integrated with other such as analytics (BDA) Internet Things (IoT), mirrors components world into virtual environment facilitates exchange real-time information achieve fully converged cyber-physical spaces. This turn minimises costs improves overall product quality, flexibility processes, system integration. work reviewed recent advancements applications focusing products, systems. Insights were provided future digitally enhanced towards developing passports (DPPs) for circular economy (CE).

Язык: Английский

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AI Enabled Digital Twin of the Traction Motor of an Electric Vehicle

SAE technical papers on CD-ROM/SAE technical paper series, Год журнала: 2025, Номер 1

Опубликована: Апрель 1, 2025

<div class="section abstract"><div class="htmlview paragraph">Electric motors are critical components in Electric Vehicle (EV) &amp; industrial applications. In case of EVs electric motor has a direct impact on the functionality, range and general user experience. Traditional maintenance procedures have several major limitations such as, leaving no choice but to use expensive warranty claims, restricted predictive maintenance, unavailability useful data, reducing resale value, ultimately poor customer satisfaction. The process building virtual duplicate an actual that can replicate physical system real time is known as Digital Twin (DT) technology. Here, DT technology-based monitoring initiated permanent magnet synchronous (PMSM) used traction, thus helping overcome drawbacks traditional system. To provide holistic approach monitoring, management, ensuring enhanced reliability, efficiency, capabilities, solution includes intuitive real-time interface, digital models based mathematics artificial intelligence (AI), anomaly detection, GenAI-based failure identification. developed improves reduce cost other related also serve future scope data repository “DT Service”.</div></div>

Язык: Английский

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Digital twin for smart manufacturing equipment: modeling and applications

The International Journal of Advanced Manufacturing Technology, Год журнала: 2025, Номер unknown

Опубликована: Март 31, 2025

Язык: Английский

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The Future of Digital Twin Research and Development

Journal of Computing and Information Science in Engineering, Год журнала: 2025, Номер 25(8)

Опубликована: Апрель 16, 2025

Abstract While digital twin (DT) has made significant strides in recent years, much work remains to be done the research community and industry fully realize benefits of DT. A group 25 professionals, US federal government researchers, academics came together from 11 different institutions organizations identify 14 key thrusts 3 cross-cutting areas for further DT development (R&D). This article presents our vision future R&D, provides historical context DT’s birth growth as a field, examples DTs use lab, discusses current state research. We hope that this serves nucleation point R&D efforts with shared trajectory collectively advance so society can more rapidly see

Язык: Английский

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Revolutionizing Railway Systems: A Systematic Review of Digital Twin Technologies

High-speed Railway, Год журнала: 2025, Номер unknown

Опубликована: Май 1, 2025

Язык: Английский

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Digital Twin technology advancing Industry 4.0 and Industry 5.0 across Sectors

Results in Engineering, Год журнала: 2025, Номер unknown, С. 105583 - 105583

Опубликована: Июнь 1, 2025

Язык: Английский

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Digital Twins in Operation and Maintenance(O&P)

Опубликована: Дек. 5, 2023

This chapter of "Digital Twin Technologies in Transportation Infrastructure Management" focuses on the role Digital Twins operation and maintenance transportation infrastructure. The starts with an introduction to O&M emphasizes importance data models for O&M. It then delves into concepts technologies predictive maintenance, such as machine learning AI, their Twins. also covers various applications infrastructure O&M, including pavement management, bridge railway system management. Overall, Chapter 6 provides a comprehensive overview how can be utilized enhance By leveraging data-driven approaches, enable reduce downtime, increase efficiency concludes summary key takeaways potential future developments this field.

Язык: Английский

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Enhancing the maintenance strategy and cost in systems with surrogate assisted multiobjective evolutionary algorithms

Developments in the Built Environment, Год журнала: 2024, Номер 19, С. 100478 - 100478

Опубликована: Июнь 6, 2024

Digital twins need efficient methodologies to design maintenance strategies for decision-making purposes. Recently, a methodology coupling computational simulation and multiobjective evolutionary algorithms has been proposed developing consisting in assigning times preventive activities designing the layout of components system, minimizing unavailability system strategy cost. Here, surrogate assisted (SAEAs) enhance optimization improve drawback cost assessment based on discrete simulation. Several Kriging surrogates were tested. Two industrial test cases are handled experimental section, where succeed obtaining nondominated designs improving previous benchmarks, enhancing state-of-the-art optimizers, with up an order magnitude terms number fitness function evaluations. Results show that using SAEAs development optimal could foster digital operations.

Язык: Английский

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