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

Enhancing production system resilience with digital twin-driven management DOI
Marisa Analía Sánchez, Daniel Alejandro Rossit, Fernando Tohmé

et al.

International Journal of Computer Integrated Manufacturing, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 20

Published: Nov. 21, 2024

Language: Английский

Citations

2
Artificial Intelligence Manufacturing Execution System (MES) Unit Control in Automation Application Fusion Industry and Education Platform Design Innovation Exploration DOI Creative Commons
Qiang Peng,

Hui Shi,

Cong Wang

et al.

Applied Mathematics and Nonlinear Sciences, Journal Year: 2024, Volume and Issue: 9(1)

Published: Jan. 1, 2024

Abstract MES, as an important part of the automation application fusion production and education platform, influences teaching majors plays role in students’ professional practice. The article designs builds industry-education platform based on MES unit control by developing key technology i.e., Kubernetes container cluster functional modules, then researches dynamic scheduling model N-MES system, proposes structure. finally applies proposed this paper to specific learning effect test productivity finds that after using paper, overall students has been improved, with 65% believing they have basically mastered knowledge points section, average score pre-test experimental class risen from 86.88 94.58 points. In practical training operation, Product A was beat line body reduced 248 seconds per piece, pass rate increased 90.32%.

Language: Английский

Citations

1
Gemelos Digitales en la Industria 5.0 – una Revisión Sistemática de Literatura DOI Creative Commons
Lauren Genith Isaza Domínguez

European Public & Social Innovation Review, Journal Year: 2024, Volume and Issue: 9, P. 1 - 21

Published: Aug. 30, 2024

Introducción: La Industria 5.0 integra tecnologías avanzadas con enfoques centrados en el ser humano para mejorar la seguridad fabricación, colaboración humano-robot y eficiencia. Los gemelos digitales, réplicas virtuales de sistemas físicos, son centrales esta iniciativa laboral eficiencia operativa. Metodología: Esta SLR utilizó una estrategia búsqueda exhaustiva cinco bibliotecas digitales: IEEE Explore, Scopus, Taylor & Francis Online, ACM Digital Library Web of Science. Resultados: hallazgos destacan las contribuciones los digitales a trabajadores mediante monitoreo tiempo real, detección inteligente gestión proactiva riesgos. se logra través integración datos real. también mejoran fabricación al permitir producción más inteligentes adaptativos. Discusión: A pesar su potencial, deben abordar desafíos como calidad datos, complejidad computacional, ciberseguridad, factores humanos impactos socioeconómicos. Conclusiones: subraya papel avance 5.0, promoviendo entornos industriales seguros, eficientes humano.

Citations

1
The Genesis DOI

Rajagopal,

Ananya Rajagopal

Published: Jan. 1, 2024

Citations

0
Reinforcement learning and digital twin-driven optimization of production scheduling with the digital model playground DOI Creative Commons

Arne Seipolt,

Ralf Buschermöhle,

Volker Haag

et al.

Discover Internet of Things, Journal Year: 2024, Volume and Issue: 4(1)

Published: Dec. 23, 2024

Language: Английский

Citations

0
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

Citations

0