| Title |
Exploring the synergies between collaborative robotics, digital twins, augmentation, and industry 5.0 for smart manufacturing: a state-of-the-art review / |
| Authors |
Zafar, Muhammad Hamza ; Langås, Even Falkenberg ; Sanfilippo, Filippo |
| DOI |
10.1016/j.rcim.2024.102769 |
| Full Text |
|
| Is Part of |
Robotics and computer-integrated manufacturing.. Kidlington : Elsevier. 2024, vol. 89, art. no. 102769, p. 1-29.. ISSN 0736-5845. eISSN 1879-2537 |
| Keywords [eng] |
augmentation ; deep learning ; digital twins ; HRC ; Industry 5.0 |
| Abstract [eng] |
Industry 5.0 aims at establishing an inclusive, smart and sustainable production process that encourages human creativity and expertise by leveraging enhanced automation and machine intelligence. Collaborative robotics, or “cobotics”,is a major enabling technology of Industry 5.0, which aspires at improving human dexterity by elevating robots to extensions of human capabilities and, ultimately, even as team members. A pivotal element that has the potential to operate as an interface for the teaming aspiration of Industry 5.0 is the adoption of novel technologies such as virtual reality (VR), augmented reality (AR), mixed reality (MR) and haptics, together known as “augmentation”. Industry 5.0 also benefit from Digital Twins (DTs), which are digital representations of a physical assets that serves as their counterpart — or twins. Another essential component of Industry 5.0 is artificial intelligence (AI), which has the potential to create a more intelligent and efficient manufacturing process. In this study, a systematic review of the state of the art is presented to explore the synergies between cobots, DTs, augmentation, and Industry 5.0 for smart manufacturing. To the best of the author's knowledge, this is the first attempt in the literature to provide a comprehensive review of the synergies between the various components of Industry 5.0. This work aims at increasing the global efforts to realize the large variety of application possibilities offered by Industry 5.0 and to provide an up-to-date reference as a stepping-stone for new research and development within this field. |
| Published |
Kidlington : Elsevier |
| Type |
Journal article |
| Language |
English |
| Publication date |
2024 |
| CC license |
|
