Table 3 Identified impacts with the state-of-the-art.
Impact categories | Specification | Authors |
|---|---|---|
VR and AI in the design, production, and evaluation | Use of mixed reality tools for interactive virtual prototyping to enable user participation. High-fidelity simulation environments in evaluating industrial automation. It highlights the potential of VR and AI in addressing communication in manufacturing processes. Advanced simulation and visualization techniques to optimize processes Innovation through the integration like AI, VR, and IoT | Arrighi and Mougenot (2016)12 Zhang et al. (2022)25 Lnu and Talwar (2023)7 Mourtzis (2023)37 Chu et al. (2023)38 |
Machinery maintenance, and inventory management | This paper presents a genetic algorithm-based approach to optimize preventive maintenance scheduling. Methodology for designing and implementing data-driven predictive maintenance models in manufacturing, guided by domain knowledge. Skills related to maintenance in advanced manufacturing processes. | Javanmard and Koraeizadeh (2016)59 Serradilla et al. (2022)32 Rodzalan et al. (2022)3 |
Personalized training | It emphasizes the use of VR and AI in enhancing skills and providing innovative solutions in the manufacturing sector. AI in enhancing training and skill development through interactive scenarios. Use of VR and NLP for training through interactive, conversationa scenarios | Jurczuk and Florea (2022)4 Joypriyanka and Surendran (2023)8 Lnu and Talwar (2023)7 |
Incorporation of user preferences | It emphasizes the use of VR and AI in enhancing skills and providing innovative solutions in the manufacturing sector. User experience in VR evaluations, indicating the significant influence of VR on user perception and workload. | Arrighi and Mougenot (2016)12 Hinricher et al. (2023)52 |
Global collaboration | Enhances productivity through the digital technologies | Chu et al. (2023)38 |
Sustainability and circular approach | It highlight the benefits of implementing reconfigurable and intelligent systems in production processes for sustainable manufacturing, using digital technologies. | Todescato et al. (2023)15 |
