Skip to main content

Research Repository

Advanced Search

Disassembly and deconstruction analytics system (D-DAS) for construction in a circular economy

Akanbi, Lukman A.; Oyedele, Lukumon O.; Omoteso, Kamil; Bilal, Muhammad; Akinade, Olugbenga O.; Ajayi, Anuoluwapo O.; Davila Delgado, Juan Manuel; Owolabi, Hakeem A.

Disassembly and deconstruction analytics system (D-DAS) for construction in a circular economy Thumbnail


Authors

Dr Lukman Akanbi Lukman.Akanbi@uwe.ac.uk
Associate Professor - Big Data Application Developer

Lukumon Oyedele L.Oyedele@uwe.ac.uk
Professor in Enterprise & Project Management

Kamil Omoteso

Muhammad Bilal Muhammad.Bilal@uwe.ac.uk
Associate Professor - Big Data Application

Olugbenga Akinade Olugbenga.Akinade@uwe.ac.uk
Associate Professor - AR/VR Development with Artificial Intelligence

Anuoluwapo Ajayi Anuoluwapo.Ajayi@uwe.ac.uk
Associate Professor - Big Data Application

Manuel Davila Delgado Manuel.Daviladelgado@uwe.ac.uk
Associate Professor - AR/VR Development with Artificial Intelligence

Hakeem Owolabi Hakeem.Owolabi@uwe.ac.uk
Associate Professor - Project Analytics and Digital Enterprise



Abstract

© 2019 Despite the relevance of building information modelling for simulating building performance at various life cycle stages, Its use for assessing the end-of-life impacts is not a common practice. Even though the global sustainability and circular economy agendas require that buildings must have minimal impact on the environment across the entire lifecycle. In this study therefore, a disassembly and deconstruction analytics system is developed to provide buildings’ end-of-life performance assessment from the design stage. The system architecture builds on the existing building information modelling capabilities in managing building design and construction process. The architecture is made up of four different layers namely (i) Data storage layer, (ii) Semantic layer, (iii) Analytics and functional models layer and (iv) Application layer. The four layers are logically connected to function as a single system. Three key functionalities of the disassembly and deconstruction analytics system namely (i) Building Whole Life Performance Analytics (ii) Building Element Deconstruction Analytics and (iii) Design for Deconstruction Advisor are implemented as plug-in in Revit 2017. Three scenarios of a case study building design were used to test and evaluate the performance of the system. The results show that building information modelling software capabilities can be extended to provide a platform for assessing the performance of building designs in respect of the circular economy principle of keeping the embodied energy of materials perpetually in an economy. The disassembly and deconstruction analytics system would ensure that buildings are designed with design for disassembly and deconstruction principles that guarantee efficient materials recovery in mind. The disassembly and deconstruction analytics tool could also serve as a decision support platform that government and planners can use to evaluate the level of compliance of building designs to circular economy and sustainability requirements.

Citation

Akanbi, L. A., Oyedele, L. O., Omoteso, K., Bilal, M., Akinade, O. O., Ajayi, A. O., …Owolabi, H. A. (2019). Disassembly and deconstruction analytics system (D-DAS) for construction in a circular economy. Journal of Cleaner Production, 223, 386-396. https://doi.org/10.1016/j.jclepro.2019.03.172

Journal Article Type Article
Acceptance Date Mar 14, 2019
Online Publication Date Mar 15, 2019
Publication Date Jun 20, 2019
Deposit Date Mar 21, 2019
Publicly Available Date Jan 17, 2020
Journal Journal of Cleaner Production
Print ISSN 0959-6526
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 223
Pages 386-396
DOI https://doi.org/10.1016/j.jclepro.2019.03.172
Keywords Disassembly and Deconstruction Analytics (D-DAS), Building Information Modelling (BIM), end-of-life, circular economy, design for deconstruction, design for disassembly
Public URL https://uwe-repository.worktribe.com/output/846100
Publisher URL https://doi.org/10.1016/j.jclepro.2019.03.172
Additional Information Additional Information : This is the author's accepted manuscript. the final published version is available here: https://doi.org/10.1016/j.jclepro.2019.03.172.

Files







You might also like



Downloadable Citations