Alex Mbabu A.M.Mbabu@edu.salford.ac.uk
Alex Mbabu A.M.Mbabu@edu.salford.ac.uk
Prof Jason Underwood J.Underwood@salford.ac.uk
Professor
Dr Mustapha Munir M.Y.Munir1@salford.ac.uk
Lecturer
Digital twins are increasingly popular in the built environment for addressing unique challenges through tailored use cases. One such application is in decision support and management for strategic facility management. Employing design science research strategy, this research proposes a digital twin framework for Lean strategic facility management, which explores the integration of Building Information Modelling (BIM) process maturity. The findings present a structured approach that enables organisations to achieve enhanced decision support, efficient decision management, and combined Lean management. By leveraging the proposed framework, organisations can improve their performance through effective strategic facility management. This paper offers practical guidance for organisations seeking to adopt Lean management in strategic facility management, by providing a BIM maturity process for a Lean strategic facility management digital twin. Embracing this approach enables organisations to fully harness the potential of digital twins, driving customer value improvements.
Presentation Conference Type | Conference Paper (published) |
---|---|
Conference Name | 2023 European Conference of Computing in Construction (2023 ECĀ³) |
Start Date | Jul 10, 2023 |
End Date | Jul 12, 2023 |
Acceptance Date | Mar 17, 2023 |
Publication Date | Jul 10, 2023 |
Deposit Date | Nov 24, 2023 |
DOI | https://doi.org/10.35490/EC3.2023.325 |
Publisher URL | https://ec-3.org/publications/conference/ |
Building-as-a-Service: Theoretical Foundations and Conceptual Framework
(2022)
Journal Article
A lean strategic FM service model based on the digital twin
(2022)
Presentation / Conference Contribution
A Proposed Digital Twin Framework to Enable Lean Strategic Facility Management
(2022)
Presentation / Conference Contribution
About USIR
Administrator e-mail: library-research@salford.ac.uk
This application uses the following open-source libraries:
Apache License Version 2.0 (http://www.apache.org/licenses/)
Apache License Version 2.0 (http://www.apache.org/licenses/)
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search