TY  - CONF
TI  - On-Site Waste Management: A Use Case of Lean Construction and Artificial Intelligence Synergy
C1  - Lille, France
C3  - Proceedings of the 31st Annual Conference of the International Group for Lean Construction (IGLC31)
SP  - 462
EP  - 473
PY  - 2023
DO  - 10.24928/2023/0153
AU  - Berroir, Fabrice
AU  - Guernaccini, Pierre
AU  - Sottet, Jean-Sébastien
AD  - R&D Engineer, Luxembourg Institute of Science and Technology (LIST), Esch-sur-Alzette, Luxembourg,  fabrice.berroir@list.lu, orcid.org/0000-0002-0392-1011
AD  - R&D Engineer, Luxembourg Institute of Science and Technology (LIST), Esch-sur-Alzette, Luxembourg,  pierre.guernaccini@list.lu, orcid.org/0000-0002-5395-9042
AD  - Senior Researcher, Luxembourg Institute of Science and Technology (LIST), Esch-sur-Alzette, Luxembourg,  jean-sebastien.sottet@list.lu, orcid.org/0000-0002-3071-6371  
AB  - The construction industry generates more waste than any other industry. Waste management is getting more and more attention as the policies and mentalities evolve to face the challenges ahead: climate change, materials shortage, circular economy. Most of the waste management activities consist in waste sorting and is carried out downstream of the construction execution, resulting in lower material recovery performance. This paper proposes a method to segregate waste (separate waste based on how it is created) to enhance the reuse, recovery, and recycling of construction waste. Therefore, it investigates the applicability of Lean Construction methods and Artificial Intelligence (AI) tools and their potential synergy. Directly applying classical waste management AI tools (as used in recycling centers) was tested based on real case data. It required an excessive need for data and training. Alternatively, a Lean Construction framework based on a combination of the 5S method, and the Takt Time Planning method was proposed. It enables the streamlining of flows in order to mitigate the impact of on-site constraints on AI training. We instrumented this Lean Construction approach with an AI tool that checks the quality of the construction waste segregation process by detecting mixed materials in dumpsters
KW  - Lean Construction
KW  - process
KW  - sustainability
KW  - Artificial Intelligence
KW  - waste segregation.
PB  - 
T2  - Proceedings of the 31st Annual Conference of the International Group for Lean Construction (IGLC31)
DA  - 2023/06/26
CY  - Lille, France
L1  - http://iglc.net/Papers/Details/2092/pdf
L2  - http://iglc.net/Papers/Details/2092
N1  - Export Date: 24 April 2025
DB  - IGLC.net
DP  - IGLC
LA  - English
ER  -