In this section
@inproceedings{Romero:2014:10.1016/B978-0-444-63456-6.50136-8,
author = {Romero, DD and Graven, T-G and Thornhill, NF},
doi = {10.1016/B978-0-444-63456-6.50136-8},
pages = {811--816},
title = {Investigations on information-rich visualizations to explore process connectivity and causality},
url = {http://dx.doi.org/10.1016/B978-0-444-63456-6.50136-8},
year = {2014}
}
TY - CPAPER
AB - Complexity in large-scale chemical processes poses a challenge to engineers who need to understand causality and interconnectivity. Previous work has already taken advantage of the use of visualization for alarm correlation and plant-wide oscillation detection for small scale example processes, but the resulting correlation maps are limited in the number of variables that can be easily managed. This paper proposes a new approach to the visualization of connectivity information, which is capable of representing a large number of connections between process variables and units, as well as process-specific information and alarm history. The novel visualization is based on the Circos framework which is widely used for analysis of connectivity and causality in the field of genomics. The benefit of adapting information-rich visualizations for the field of process systems engineering will be discussed based on an academic use-case. © 2014 Elsevier B.V.
AU - Romero,DD
AU - Graven,T-G
AU - Thornhill,NF
DO - 10.1016/B978-0-444-63456-6.50136-8
EP - 816
PY - 2014///
SN - 1570-7946
SP - 811
TI - Investigations on information-rich visualizations to explore process connectivity and causality
UR - http://dx.doi.org/10.1016/B978-0-444-63456-6.50136-8
ER -
Nina Thornhill, ABB/RAEng Professor of Process Automation
Centre for Process Systems Engineering
Department of Chemical Engineering
Imperial College London
South Kensington Campus, London SW7 2AZ
Tel: +44 (0)20 7594 6622
Email: n.thornhill@imperial.ac.uk