TY - JOUR
T1 - Disruptive data visualization towards zero-defects diagnostics
AU - Ferreira, Luís
AU - Putnik, Goran D.
AU - Lopes, Nuno
AU - Garcia, Wiley
AU - Cruz-Cunha, Maria M.
AU - Castro, Hélio
AU - Varela, Maria L.R.
AU - Moura, João M.
AU - Shah, Vaibhav
AU - Alves, Cátia
AU - Putnik, Zlata
N1 - Funding Information:
This work has been supported by (1) COMPETE: POCI-01-0145-FEDER-007043 (2) FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013, (3) Ph.D. Scholarship Grant reference SFRH/BD/85672/2012, and (4) Ph.D. Scholarship Grant reference SFRH/BD/62313/2009.
Publisher Copyright:
© 2017 The Authors.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
KW - Disruptive data visualization
KW - industry 4.0
KW - IoT
KW - Manufacturing systems
KW - Zero-defects diagnostics
UR - http://www.scopus.com/inward/record.url?scp=85044636918&partnerID=8YFLogxK
U2 - 10.1016/j.procir.2017.12.270
DO - 10.1016/j.procir.2017.12.270
M3 - Conference article
AN - SCOPUS:85044636918
SN - 2212-8271
VL - 67
SP - 374
EP - 379
JO - Procedia CIRP
JF - Procedia CIRP
T2 - 11th CIRP International Conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME 2017
Y2 - 19 July 2017 through 21 July 2017
ER -
