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Drivers for energy analysis towards a BIM-enabled information flow

Lookup NU author(s): Professor Mohamad Kassem


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© 2022, Emerald Publishing Limited. Purpose: Energy analysis (EA) within a building information modelling (BIM) enables consistent data integration in central repositories and eases information exchange, reducing rework. However, data loss during information exchange from different BIM uses or disciplines is frequent. Therefore, a holistic approach for different BIM uses enables a coherent life cycle information flow. The life cycle information flow drives the reduction of data loss and model rework and enhances the seamless reuse of information. The latter requires a specification of the EA key performance indicators (KPIs) and integrating those in the process. Design/methodology/approach: The paper presents a set of KPIs extracted from the developed EA process maps and interviews with expert stakeholders. These KPIs stem from the literature review and link to the benefits of EA through industry expert review. The study includes (1) development and validation of EA process maps adjusted to requirements from different stakeholders. (2) KPIs aligned with the EA process map, (3) identification of the drivers that can facilitate life cycle information exchange and (4) opportunities and obstacles for EA within BIM-enabled projects. Findings: This paper depicts a viable alternative for EA process maps and KPIs in a BIM-enabled AEC design industry. The findings of this paper showcase the need for an EA within BIM with these KPIs integrated for a more effective process conforming to the current Open BIM Alliance guidance and contributing towards sustainable life cycle information flow. Research limitations/implications: The limitation of the research is the challenge of generalising the developed EA process maps; however, it can be adjusted to fit defined organisational use. The findings deduced from the developed EA process map only show KPIs to have the ability to facilitate adequate information flow during EA. Practical implications: The AEC industry will benefit from the findings of this primary research as the industry will be able to contrast its process maps and KPIs to those developed in the paper. Social implications: This paper benefits the societal values in EA for the built environment in the design stages. The subsequent life cycle information flow will help achieve a consistent information set and decarbonised built environment. Originality/value: The paper offers a practical overview of process maps and KPIs to embed EA into BIM, reducing the information loss and rework needed in the practice of this integration. The applicability of the solution is contrasted by consultation with experts and literature.

Publication metadata

Author(s): Mohammad Ahmad A, Rodriguez Trejo S, Hafeez MA, Dawood N, Kassem M, Naji KK

Publication type: Article

Publication status: Published

Journal: Smart and Sustainable Built Environment

Year: 2022

Volume: 12

Issue: 3

Pages: 507-533

Online publication date: 20/04/2022

Acceptance date: 02/04/2018

ISSN (print): 2046-6099

ISSN (electronic): 2046-6102

Publisher: Emerald Publishing Limited


DOI: 10.1108/SASBE-07-2021-0129


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