Disruptive data visualization towards zero-defects diagnostics
| Autor: | Maria Leonilde Rocha Varela, Nuno Lopes, Zlata Putnik, Luís Carlos de Souza Ferreira, Goran D. Putnik, Vaibhav Shah, João Martinho Moura, Cátia Alves, Wiley Garcia, Hélio Castro, Maria Manuela Cruz-Cunha |
|---|---|
| Přispěvatelé: | Universidade do Minho |
| Rok vydání: | 2018 |
| Předmět: |
IoT
0209 industrial biotechnology Ubiquitous computing Industry 4.0 Computer science Dashboard (business) Cloud computing 02 engineering and technology 020901 industrial engineering & automation Data visualization Application domain 0202 electrical engineering electronic engineering information engineering industry 4.0 Manufacturing systems General Environmental Science Science & Technology 9. Industry and infrastructure business.industry Zero-defects diagnostics Data science Visualization General Earth and Planetary Sciences Disruptive data visualization 020201 artificial intelligence & image processing Augmented reality business |
| Zdroj: | Procedia CIRP. 67:374-379 |
| ISSN: | 2212-8271 |
| DOI: | 10.1016/j.procir.2017.12.270 |
| Popis: | Innovative processes become available due to the high processing capacity of emergent infrastructures, such as cloud and ubiquitous computing and organizational infrastructures and applications. However, these intense computation processes are difficult to follow, where co-decision is required, for which the existence of disruptive visualization and collaboration tools that offer a visual tracing capacity with integrated decision supporting tools, are critical for its sustainable success. This project proposes: a) a set of immersive and disruptive visualization tools, supported by virtual and augmented reality, that enables a global perspective of any production agents; b) a data analytics tool to complement and assist the decision making; c) a resource federated network that allows the brokering and interaction between all existing resources; and d) a dynamic context-aware dashboard, to improve the overall productive process and contribute to intelligent manufacturing systems. The application domain addressed is Zero-Defects Diagnostics in manufacturing as well as in Industry 4.0 in general. Fundação para a Ciência e a Tecnologia (UID/CEC/00319/2013) |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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