πŸ“–
Towards a Maturity Model for Intelligent Digital Twins in Manufacturing
Luis Felipe Villegas, Marco Macchi, Adalberto Polenghi

Towards a Maturity Model for Intelligent Digital Twins in Manufacturing

Science & Mathematics Published 2024 Verification Pending

Overview & Synopsis

The adoption of Digital Twins (DTs) in manufacturing is promising as they hold the potential to bring key changes in the way industrial systems are managed and optimized. As enabling technologies continue to emerge, their integration into these complex systems enhances the granularity of intelligence and functionalities available within the Cyber-physical Systems. Such granularity accentuates the need to clarify the distinctive features of this emerging class of DTs, where the transition from Conventional DTs to Intelligent DTs marks a shift towards increasingly proactive, autonomous, and cognitive systems. This paper particularly explores the evolution of Intelligent DTs, focusing on formalizing the enhanced intelligence in correspondent maturity levels that express the progression on DT systems. The maturity levels of Intelligent DTs are categorized into predictive, prescriptive, and autonomous stages, to then identify both the associated capabilities and technologies across different application domains related to manufacturing. On its whole, the outcome of this paper can be seen both as a current map on the maturity of Intelligent DTs implementation, and as a research agenda to explore capabilities and technologies from different domains in manufacturing.

Advertisement
SPONSOR CONTENT
Indexed from repository: HAL Open Science (hal.science)
Loading document from verified source...
Keyboard Shortcuts: ← / → for pages • + / - for zoom • 0 to fit width Powered by Mozilla PDF.js v3.11

Document Information

Document Title Towards a Maturity Model for Intelligent Digital Twins in Manufacturing
Author / Organization Luis Felipe Villegas, Marco Macchi, Adalberto Polenghi
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2024
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-7695
Original Source Link Visit Source Page on hal.science »