Towards AI-based Sustainable and XR-based human-centric manufacturing: Implementation of ISO 23247 for digital twins of production systems
August 20, 2025 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Huizhong Cao, Henrik SΓΆderlund, Qi Fang, Siyuan Chen, Lejla Erdal, Ammar Gubartalla, Paulo Victor Lopes, Guodong Shao, Per Lonnehed, Henri Putto, Abbe Ahmed, Sven Ekered, BjΓΆrn Johansson
arXiv ID
2508.14580
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Since the introduction of Industry 4.0, digital twin technology has significantly evolved, laying the groundwork for a transition toward Industry 5.0 principles centered on human-centricity, sustainability, and resilience. Through digital twins, real-time connected production systems are anticipated to be more efficient, resilient, and sustainable, facilitating communication and connectivity between digital and physical systems. However, environmental performance and integration with virtual reality (VR) and artificial intelligence (AI) of such systems remain challenging. Further exploration of digital twin technologies is needed to validate the real-world impact and benefits. This paper investigates these challenges by implementing a real-time digital twin based on the ISO 23247 standard, connecting the physical factory and simulation software with VR capabilities. This digital twin system provides cognitive assistance and a user-friendly interface for operators, thereby improving cognitive ergonomics. The connection of the Internet of Things (IoT) platform allows the digital twin to have real-time bidirectional communication, collaboration, monitoring, and assistance. A lab-scale drone factory was used as the digital twin application to test and evaluate the ISO 23247 standard and its potential benefits. Additionally, AI integration and environmental performance Key Performance Indicators (KPIs) have been considered as the next stages in improving VR-integrated digital twins. With a solid theoretical foundation and a demonstration of the VR-integrated digital twins, this paper addresses integration issues between various technologies and advances the framework of digital twins based on ISO 23247.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted