Alnaggar, Ahmed Mohamed Mohamed Moustafa; (2022) Digital Transformation in Asset Management Organisations: Towards a Data Driven Approach for Life Cycle Asset Management. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Digital transformation has a significant potential to help Asset Management (AM) industry overcome its inherent problems such as lack of productivity and inefficiency. However, the required data driven approach to achieve that, is not sufficiently mature in research and practise. To bridge this gap, this research aims to investigate the technical and social aspects associated with this data driven approach for lifecycle asset management using two digital technologies namely Building Information Modelling (BIM) and the Internet of Things (IoT). The research has three main objectives: First, identify the current problems of asset data management using BIM open standards, and develop a process model for asset data flow that can be used to avoid the identified problems during design and construction phases of building lifecycle. Second, investigate the role of IoT to integrate with BIM data forming a digital twin of the built asset to support the automation of AM in the operation phase of building lifecycle. Third, outline the social change required to enable this data driven approach for AM organisations. This research took place in collaboration with a Tier 1 construction main contractor and an AM service provider. The first stage of this research used a design science methodology to identify the problems of asset data management and develop a process model for asset data flow using BIM open standards during the design and construction phases of the building lifecycle. The second stage used case study research to investigate the use of IoT in asset management automation and its role in enabling a connected digital twin during the operation phase of the lifecycle. Finally, using a qualitive research method, a sociotechnical systems (STS) analysis and discussion is then used to investigate the social change associated with digital transformation in AM organisations. The findings of this research outlined several problems of asset data management and showed how process re-engineering could tackle these problems. Furthermore, the research showed that IoT based automation is technically feasible, provides business value to AM industry and it developed a roadmap to use IoT for a lifecycle/connected digital twin. The STS study showed that a redesign of the AM work system including its strategy, policy, processes, legal and people related aspects is required to support a successful digital transformation journey. The significance of this study is that it took a holistic view of digital transformation for AM industry across the asset lifecycle. This holistic view used empirical data from live projects to improve our theoretical understanding and provide practical insights on asset information exchange processes, the use of digital technology for AM automation and the social aspects associated with digital transformation.

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