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Leveraging engineering asset data : strategic priorities, data types and informational outcomes

Murphy, Glen D., Chang, Artemis, & Barlow, M. (2008) Leveraging engineering asset data : strategic priorities, data types and informational outcomes. In Jinji, Goa, Lee, Jay, Ni, Jun, Ma, Lin, & Mathew, Joseph (Eds.) 3rd World Congress on Engineering Asset Management and Intelligent Maintenance Systems Conference (WCEAM-IMS 2008): Engineering Asset Management – A Foundation for Sustainable Development, 27–30 October 2008, Beijing, China.

Abstract

A common complaint heard within the engineering asset community is that while the capacity for data storage increases, the quality of ever increasing amounts of data remains poor. We propose a new model of engineering asset data management that helps explain why data collected by organizations frequently fails to assist in effective engineering asset management. The model situates a four component typology of engineering data between institutional drivers (e.g. organizational culture; organizational strategy; organizational life-cycle; consequence of asset failure) and asset management outcomes. We argue these outcomes (regulatory compliance; time-based maintenance; condition-based asset management; capacity development) are functions not only of the data collected by an organization, but its capacity to leverage that data. We develop a model suggesting that institutional drivers dictate the data requirements of engineering asset intensive firms, typically at the cost of data requirements for different phases in the asset's life-cycle. This paper will assist practitioners to re-conceptualize the manner in which they view their data, the manner in which it is utilized, and provide a better understanding of data and its intended outcomes. This will allow a better prioritization of data collection activities and offer an improved insight into ways in which engineering data may be better transformed into informational and knowledge outcomes.

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ID Code: 15611
Item Type: Conference Paper
Additional URLs:
Keywords: Data Quality, Organisational Lifecycle, Data Typology
ISBN: 9781848822160
Subjects: Australian and New Zealand Standard Research Classification > COMMERCE MANAGEMENT TOURISM AND SERVICES (150000) > BUSINESS AND MANAGEMENT (150300) > Organisational Planning and Management (150312)
Australian and New Zealand Standard Research Classification > COMMERCE MANAGEMENT TOURISM AND SERVICES (150000) > BUSINESS AND MANAGEMENT (150300) > Innovation and Technology Management (150307)
Divisions: Current > Research Centres > Australian Centre for Business Research
Current > QUT Faculties and Divisions > QUT Business School
Current > Research Centres > CRC Integrated Engineering Asset Management (CIEAM)
Copyright Owner: Copyright 2008 Springer
Copyright Statement: This is the author-version of the work. Conference proceedings published, by Springer Verlag, will be available via SpringerLink. http://www.springerlink.com SpringerLink
Deposited On: 13 Nov 2008
Last Modified: 29 Feb 2012 23:43

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