Please use this identifier to cite or link to this item: https://hdl.handle.net/1822/62958

TitleDisruptive data visualization towards zero-defects diagnostics
Author(s)Ferreira, Luís
Putnik, Goran D.
Lopes, Nuno
Garcia, Wiley
Cruz-Cunha, Maria M.
Castro, Hélio
Varela, M.L.R.
Moura, João Martinho
Shah, Vaibhav
Alves, Cátia
Putnik, Zlata
KeywordsDisruptive data visualization
industry 4.0
IoT
Manufacturing systems
Zero-defects diagnostics
Issue date2018
PublisherElsevier B.V.
JournalProcedia CIRP
Abstract(s)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.
TypeConference paper
URIhttps://hdl.handle.net/1822/62958
DOI10.1016/j.procir.2017.12.270
ISSN2212-8271
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings

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