A real-time adaptive dynamic scheduling method for manufacturing workshops based on digital twin DOI
Wenbin Gu, L. Duan, Siqi Liu

et al.

Flexible Services and Manufacturing Journal, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 23, 2024

Language: Английский

Cloud-edge-end collaborative multi-process dynamic optimization for energy-efficient aluminum casting DOI
Weipeng Liu, Hao Wang, Pai Zheng

et al.

Journal of Manufacturing Systems, Journal Year: 2025, Volume and Issue: 79, P. 217 - 233

Published: Jan. 27, 2025

Language: Английский

Citations

1

A human-centric methodology for the co-evolution of operators’ skills, digital tools and user interfaces to support the Operator 4.0 DOI Creative Commons
Fabio Grandi,

Contini Giuditta,

Margherita Peruzzini

et al.

Robotics and Computer-Integrated Manufacturing, Journal Year: 2024, Volume and Issue: 91, P. 102854 - 102854

Published: Aug. 15, 2024

The concept of Operator 4.0 has been recently defined to evolve the modern industrial scenarios by defining a knowledge sharing process from/to operators and systems, creating personalized skills, introducing digital tools towards socially sustainable factories. In this context, dynamic adaptive user interfaces can make humans part intelligent factory system, supporting human work contextually providing specific contents when needed, preserving wellbeing. This paper defines human-centric methodology for symbiotic co-evolution operators' assistive interfaces, developed within Horizon Europe project titled "DaCapo - Digital assets Circular value chains manufacturing products". focuses on new set services industry capable boosting application circular economy (CE) throughout chains. proposed link needs an case definition most proper functionalities drive design adaptive, proactive 4.0. method applied validated one use cases, involving company operating in warehousing logistics.

Language: Английский

Citations

6

On Digital Twins for Cloud Continuum Applications DOI
Luiz F. Bittencourt, Kelly Rosa Braghetto, Daniel Cordeiro

et al.

Lecture notes in computer science, Journal Year: 2025, Volume and Issue: unknown, P. 286 - 293

Published: Jan. 1, 2025

Language: Английский

Citations

0

A novel dynamic spatio-temporal graph based condition monitoring framework for consistency retention of digital twin DOI
Xiaofeng Wang, Jihong Yan, Xun Xu

et al.

Journal of Manufacturing Systems, Journal Year: 2025, Volume and Issue: 79, P. 455 - 465

Published: Feb. 11, 2025

Language: Английский

Citations

0

Towards Industry 5.0: digital twin-enhanced approach for dynamic supply chain rescheduling with real-time order arrival and acceptance DOI
Xing Zhu, Baoyu Liao,

Yexing Shen

et al.

International Journal of Production Research, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 23

Published: March 24, 2025

Language: Английский

Citations

0

Enhancing Production Efficiency Through Digital Twin Simulation Scheduling DOI Creative Commons
Patrik Grznár,

Ladislav Papánek,

Milan Marčan

et al.

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(7), P. 3637 - 3637

Published: March 26, 2025

Flexible custom manufacturing is becoming increasingly important, and, in the near future, it will serve as a key method to counter growing competition and meet market demands across most industrial sectors. This situation necessitates substantial reorganization of companies’ material information flows, traditional planning approaches focused on serial production longer time horizons are gradually losing their effectiveness. An integrated digital twin system that unifies logistics emerging promising solution. The proposed approach entails implementing directly within manufacturing, enabling continuous monitoring real-time adjustment plans based instant data from sensors systems. architecture designed around multiple modules responsible for collection processing, scheduling, simulation, statistical analysis, effective communication between its users. By leveraging these components, solution can flexibly adapt any deviations or changes they occur. Within scope this research, attention devoted not only handling dynamic random but also prioritization individual orders. Equally emphasized role intelligent tools, which promptly inform us about shifts process allow rapid plan modifications ensure highest possible levels efficiency reliability.

Language: Английский

Citations

0

Metrology and Manufacturing-Integrated Digital Twin (MM-DT) for Advanced Manufacturing: Insights from Coordinate Measuring Machine (CMM) and FARO Arm Measurements DOI

Hamidreza Samadi,

Md Manjurul Ahsan, Shivakumar Raman

et al.

Next research., Journal Year: 2025, Volume and Issue: unknown, P. 100299 - 100299

Published: April 1, 2025

Language: Английский

Citations

0

No-wait lines optimisation: a procedure based on scheduling enhanced by digital twin DOI Creative Commons
Mario Caterino, Roberto Macchiaroli, Stefano de Miranda

et al.

Flexible Services and Manufacturing Journal, Journal Year: 2025, Volume and Issue: unknown

Published: April 22, 2025

Abstract The no-wait scheduling problem involves planning the sequence of tasks in a job without any delay. This constraint is crucial industries where production interruptions may create significant inefficiencies or quality issues. paper addresses this by proposing new methodology to design and verify work-cycle related layout, focusing on both job-shop flow-shop environments finally proving its efficiency thanks use digital twin validate process. goal optimisation makespan minimisation it achieved through application timetabling heuristic method. iterative nature proposed model allows for continuous improvement scheduling, queue reduction verified twin. procedure tested real galvanic line primary aerospace international company; results show that guarantees respect times, which concur increase demand satisfaction company.

Language: Английский

Citations

0

Dynamic production scheduling and maintenance planning under opportunistic grouping DOI

Nada Ouahabi,

Ahmed Chebak,

Oulaïd Kamach

et al.

Computers & Industrial Engineering, Journal Year: 2024, Volume and Issue: unknown, P. 110646 - 110646

Published: Oct. 1, 2024

Language: Английский

Citations

3

Milling surface roughness monitoring using real-time tool wear data DOI
Runqiong Wang, Qinghua Song,

Yezhen Peng

et al.

International Journal of Mechanical Sciences, Journal Year: 2024, Volume and Issue: 285, P. 109821 - 109821

Published: Nov. 15, 2024

Language: Английский

Citations

3