Design for Disassembly in Residential Buildings: A Systematic Review of Current Practices and Emerging Digital Technologies

Cem Cetin; Nils Jaeger

doi:10.65582/rrs.2026.012

Authors

Cem Cetin Department of Architecture and Built Environment, University of Nottingham, University Park, Nottingham, NG7 2RD, United Kingdom. https://orcid.org/0000-0001-6885-6735
Nils Jaeger Department of Architecture and Built Environment, University of Nottingham, University Park, Nottingham, NG7 2RD, United Kingdom. https://orcid.org/0000-0002-4686-2568

DOI:

https://doi.org/10.65582/rrs.2026.012

Keywords:

Artificial Intelligence, Circular Economy, Sustainable Housing

Abstract

This systematic review critically examines the state of Design for Disassembly (DfD) in residential construction, synthesising evidence from 95 peer-reviewed studies and 71 case studies published between 2010 and 2025. The study asks: To what extent do current DfD strategies align with residential realities, and what integrated approaches are needed to bridge gaps in validation and assessment? Despite rapid growth in circular economy (CE) research, findings reveal a fundamental misalignment between the technical development of DfD strategies and the socio-spatial realities of housing. Firstly, while DfD offers critical capabilities for portability and rapid response to housing shortages and emergency contexts, current scholarship predominantly prioritises uncertain, scenario-based end-of-life waste recovery over these immediate functional benefits. Secondly, empirical research mainly focuses on low-rise dwellings, leaving mid- and high-rise buildings largely theoretical despite their significant material intensity. Thirdly, the economic frameworks and social dimensions of housing remain largely unexamined. To address these gaps, emerging digital technologies offer substantial potential. Specifically, machine learning can replace uncertain life cycle predictions with predictive circularity modelling, computer vision enables the digitisation of existing housing stock to quantify residual material values for alternative mortgage models, and large language models can address the social dimensions to increase the adoption of DfD and CE strategies among non-expert homeowners and self-builders. The review concludes that advancing residential DfD requires integrated research across all building scales, bridging technical, environmental, and socio-economic domains to achieve a scalable circular transition.

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