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Exploring visual asset management collaboration: learning from the oil and gas sector.

Leon, Marianthi; Ahiaga-Dagbui, Dominic; Fleming, Claire; Laing, Richard

Authors

Marianthi Leon

Dominic Ahiaga-Dagbui

Claire Fleming

Richard Laing



Contributors

P.W. Chan
Editor

C.J. Neilson
Editor

Abstract

Visual Asset Management (VAM) is defined as a visual, collaborative and cloud-based database application for project sharing, viewing, delivery, operation and maintenance. VAM provides a platform that contains multiple visual data sources of an infrastructure project, including Building Information Models, associated asset documentation and 360° photographic images of the asset. This research presents three cases of the use of VAM in major oil and gas platforms in the North Sea, identifying the challenges resolved using VAM, the benefits realised as well as the opportunities for learning and transfer of VAM to the construction industry. The findings demonstrate that VAM can be used effectively to support decision making process during infrastructure project planning and development. The case studies further demonstrated that VAM will be particularly beneficial in facilities management and built asset operation, thereby, ensuring the accuracy and reliability of information for operations and maintenance. Due to the increasingly complex nature of projects in terms of size, information technology and security, realizing these benefits would require a learning process for all stakeholders involved in procuring and managing assets. This research proposes stepped change and learning opportunity for built assets value maximization and delivery, management and operation efficiency using VAM.

Citation

LEON, M., AHIAGA-DAGBUI, D., FLEMING, C. and LAING, R. 2017. Exploring visual asset management collaboration: learning from the oil and gas sector. In Chan, P.W. and Neilson, C.J. (eds.) Proceedings of the 33rd Association of Researchers in Construction Management (ARCOM) annual conference, 4-6 September 2017, Cambridge, UK. Manchester: ARCOM [online], pages 765-774. Available from: http://www.arcom.ac.uk/-docs/proceedings/5f524baa70ec1d0c7cdfafec96acc7e9.pdf

Conference Name 33rd Association of Researchers in Construction Management (ARCOM) annual conference
Conference Location Cambridge, UK
Start Date Sep 4, 2017
End Date Sep 6, 2017
Acceptance Date Feb 20, 2017
Online Publication Date Sep 4, 2017
Publication Date Sep 6, 2017
Deposit Date Oct 9, 2017
Publicly Available Date Oct 9, 2017
Publisher ARCOM Association of Researchers in Construction Management
Pages 765-774
Keywords Collaboration; Building information modelling; Visual asset management
Public URL http://hdl.handle.net/10059/2541
Publisher URL http://www.arcom.ac.uk/-docs/proceedings/5f524baa70ec1d0c7cdfafec96acc7e9.pdf

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