Towards Sustainable Personalized Assembly Through Human-Centric Digital Twins
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View abstract on PubMed
Summary
This summary is machine-generated.Industry 5.0 integrates human-centricity, resilience, and sustainability to meet demands for personalized and green production. This research presents a human-centric digital twin prototype to optimize assembly systems for sustainable, individualized manufacturing.
Area Of Science
- Manufacturing Engineering
- Industrial Systems
- Sustainability Science
Background
- Industry trends shift towards green, sustainable, and personalized production, posing challenges for integration.
- Industry 4.0 focuses on digitalization, while Industry 5.0 complements it with human-centricity, resilience, and sustainability.
- A multidisciplinary approach is essential to address the complexities of modern manufacturing paradigms.
Purpose Of The Study
- To present an advanced concept of organizational sustainability.
- To demonstrate the application of digital twin technologies aligned with human-centric approaches.
- To introduce a novel human-centric digital twin prototype for optimizing assembly systems.
Main Methods
- Utilizing research from the Erasmus+ ExCurS project, focusing on digital twin applications and training.
- Developing a multidisciplinary approach incorporating human-centricity, resilience, and sustainability.
- Creating a digital twin prototype with an algorithm for optimization and humanoid decision-making.
Main Results
- An advanced concept for organizational sustainability was developed.
- The concept is realized through digital twin technologies integrated with human-centric principles.
- A prototype digital twin was created, optimizing an assembly system for personalized products.
Conclusions
- The human-centric digital twin offers a viable solution for achieving organizational sustainability in personalized manufacturing.
- This approach enhances workforce engagement and well-being while improving system adaptability and environmental performance.
- The presented case study validates the effectiveness of the human-centric digital twin in industrial applications.
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