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Publication date: 27 January 2022

Soheila Bahrami and Davood Zeinali

This paper explores the quality and flow of facade product information and the capabilities for avoiding the risk of facade fires early in the design process.

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Abstract

Purpose

This paper explores the quality and flow of facade product information and the capabilities for avoiding the risk of facade fires early in the design process.

Design/methodology/approach

A qualitative case study using the process tracing method is conducted in two stages. First, a thematic analysis of reports and literature identified two categories for the problems that caused fast fire spread across the Grenfell Tower facade. This enabled classifying the identified problems into four stages of a facade life cycle: product design and manufacturing, procurement, facade design and construction. Second, the capabilities for avoiding the problems were explored by conducting in-depth interviews with 18 experts in nine countries, analyzing design processes and designers' expertise and examining the usability of three digital interfaces in providing required information for designing fire-safe facades.

Findings

The results show fundamental flaws in the quality of facade product information and usability of digital interfaces concerning fire safety. These flaws, fragmented design processes and overreliance on other specialists increase the risk of design defects that cause fast fire spread across facades.

Practical implications

The findings have implications for standardization of building product information, digitalization in industrialized construction and facade design management.

Originality/value

This research adds to the body of knowledge on sustainability in the built environment. It is the first study to highlight the fundamental problem of facade product information, which requires urgent attention in the rapid transition toward digital and industrialized construction.

Details

Smart and Sustainable Built Environment, vol. 12 no. 3
Type: Research Article
ISSN: 2046-6099

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Last 12 months (1)

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