The results demonstrate the feasibility of the proposed architecture for disembodied manufacturing work and provide a reusable cyber-physical framework for future human-AI-controlled digital factories.
Abstract
Digital Twins (DTs), Artificial Intelligence (AI), and Industrial Internet of Things (IIoT) technologies have significantly advanced manufacturing digitalization. However, these technologies are typically applied to individual manufacturing processes rather than integrated into a unified cyber-physical manufacturing environment. This paper proposes a cyber-physical digital factory architecture that enables disembodied work, where manufacturing systems can be supervised and operated remotely through eXtended Reality (XR) user interfaces in collaboration between AI-based control and human operators. The architecture integrates synchronized DTs, hierarchical cloud-edge AI, IIoT, and XR teleoperation interfaces into a cyber-physical manufacturing environment. The proposed approach is validated through representative manufacturing operations, including CNC machining, robotic-assisted abrasive finishing, and robotized disassembly. The results demonstrate the feasibility of the proposed architecture for disembodied manufacturing work and provide a reusable cyber-physical framework for future human-AI-controlled digital factories.
A cyber-physical architecture based on the IoT, which uses machine intelligence to monitor, analyze, and control manufacturing systems in real-time, which can be both scaled and powerful to serve next-generation intelligent manufacturing systems.
P. Mudholkar· Materials Research Proceedin...· 0 citations
Smart manufacturing represents the confluence of digital transformation and
industrial evolution, redefining manufacturing paradigms through seamless integration,
artificial intelligence (AI)-driven intelligence, and continuous innovation. This paper
explores the future development of smart manufacturing, highlighting...
Vidosav Majstorović· SMART MANUFACTURING ON THE H...· 0 citations
Industrial digital twins integrate physical objects, dynamic models, control systems, data analysis tools, 2D and 3D visualization, and existing software systems. Much research has focused on the functional composition of the digital twin, modeling, and application scenarios, while the organization of the digital twin...
E. Koltsova, Maksim Pysin, A. Lobanov et al.· Information· 0 citations
A comprehensive cloud-enabled Digital Twin architecture for IRs that enables remote task allocation, autonomous ROS-based execution, near real-time monitoring, and synchronized operation with physical manufacturing assets through a unified Cloud–Edge framework is presented.
Deep Singh, Arunachalam Narayanaperumal, Rashmi Swamy et al.· Proceedings of the Instituti...· 0 citations
Research and development of advanced technologies underpinning the
implementation of Industry 4.0 are driving the transformation of traditional
manufacturing systems into flexible production systems whose high level of integration
and intelligence is based on digital technologies. Mobile and collaborative robotics,
sup...
I. Karabegović, E. Husak, M. Mahmić et al.· SMART MANUFACTURING ON THE H...· 0 citations
This study examines the impact of Industry 4.0 technologies on manufacturing operations at Qualcomm India Private Limited by analyzing employee awareness, technology adoption, production efficiency, automation, product quality, operational performance, and employee satisfaction.
P. Dhanalakshmi, V. Kumar, Srilekha Rageru· 0 citations
Related blog posts
MIT News · Artificial Intelligence· news.mit.eduOct 7, 2026
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduSep 30, 2026
Able to defeat top-ranked human players and more efficient than other models, the new system could help decision-makers in military maneuvers or business negotiations.