Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.784247
Title: Integration and visualisation of plant connectivity in process operations
Author: Dorantes Romero, David
ISNI:       0000 0004 7969 8017
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2017
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Abstract:
Tight coupling and complexity in modern process plants make it difficult to obtain a clear and accurate assessment of the state of the process, especially when disturbances occur. Highly interconnected plants are challenging to analyse as disturbances propagate plant-wide over the process. Tasks such as troubleshooting, maintenance planning and diagnosis of abnormalities become more diffcult in the presence of unobserved dependencies between plant components. In order to support engineers to better understand the connectivity among plant items, new methods are required for modelling and visualising plant connectivity information. The methods proposed in this thesis address physical connectivity (piping and instrumentation), and also include the signals, the electrical sub-system that powers the plant and the logical connections (cause-and-effect). The reason is that electrical and utility systems are important propagation routes for the effects of process disturbances. The research reported in this thesis includes the review of technologies for data mapping and analysis, methods for modelling and integrating connectivity, and novel algorithms for parsing, linking and visualising plant connectivity models. The thesis presents the software prototype Topoviz, designed to achieve the research objectives of this project. The development of Topoviz was driven by requirements generated from site-visits and interviews with subject matter experts in the eld of plant operations. Novel contributions to the research eld include the proposal of a graph database using the property-graph model. Several algorithms were developed and tested, including novel algorithms for creating plant connectivity networks from engineering documents. These networks can be analysed to gain insights about how the di erent sub-systems in the plant could a ect each other in case of disturbances. For the rst time, the integration of connectivity information coming from the process and electrical systems was achieved. The research in this thesis shows successful results and visible advantages compared to previous methods for analysing plant connectivity information.
Supervisor: Thornhill, Nina F. Sponsor: European Union
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.784247  DOI:
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