BIM-based automated construction waste estimation algorithms: The case of concrete and drywall waste streams
•BIM-based quantity takeoff reliability validated using cloud-based software.•Method relying on linear equations, BIM quantity takeoff and purchasing records.•Method demonstration through algorithms to estimate concrete and drywall waste.•Waste estimations validated with real-world project data and...
Gespeichert in:
Veröffentlicht in: | Waste management (Elmsford) 2019-03, Vol.87, p.825-832 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 832 |
---|---|
container_issue | |
container_start_page | 825 |
container_title | Waste management (Elmsford) |
container_volume | 87 |
creator | Guerra, Beatriz C. Bakchan, Amal Leite, Fernanda Faust, Kasey M. |
description | •BIM-based quantity takeoff reliability validated using cloud-based software.•Method relying on linear equations, BIM quantity takeoff and purchasing records.•Method demonstration through algorithms to estimate concrete and drywall waste.•Waste estimations validated with real-world project data and data from literature.
Globally, the growth of construction activities over the past years has resulted in large quantities of waste generation. Much of this waste is not reused or recycled and is subsequently redirected to landfills. The environmental impact of construction waste (CW) generation and the shortage of land resources for the creation of new landfills have reinforced the need to adopt more innovative CW management practices. Estimation of CW is a necessary step for the adoption of CW management practices. In this study, Building Information Modeling (BIM) is used to automate CW quantification. In this context, CW generation is estimated as the materials purchased but not incorporated into the actual building structure. Algorithms developed to quantify concrete and drywall waste streams are presented to demonstrate the proposed CW estimation method. The proposed concrete algorithm is validated by comparing estimated waste to actual waste data reported in the waste hauling tickets of a real-world project. Furthermore, CW generation quantities reported in the literature are used to validate estimates of both concrete and drywall waste streams. By leveraging material quantities directly from BIM—as opposed to manual estimations—CW estimation can be streamlined, enabling decision makers to implement more efficient construction waste management practices in the field. |
doi_str_mv | 10.1016/j.wasman.2019.03.010 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2232095425</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0956053X1930131X</els_id><sourcerecordid>2232095425</sourcerecordid><originalsourceid>FETCH-LOGICAL-c399t-68018a66cf5ab9ce92194531afda913abe29bb5c1bb60f731f0bbb162612d6303</originalsourceid><addsrcrecordid>eNp9kEFP3DAQhS1UVBboP0BVjr0knbETb8yhUkFAkah6Aak3y3YmJaskBtsB8e_r1W575GTL8948v4-xM4QKAeXXTfVq4mTmigOqCkQFCAdshe1albxu5Ae2AtXIEhrx-4gdx7gBwLpF-MiOBGKetesVGy9uf5bWROoKsyQ_mZRvzs8xhcWlwc9FTklUUExDHm4fzPjHhyE9TvG8uH-kwmV34futywXKWjN3RRfeXs047t15G5kpnrLD3oyRPu3PE_ZwfXV_-aO8-3Vze_n9rnRCqVTKFrA1Urq-MVY5UhxV3Qg0fWcUCmOJK2sbh9ZK6NcCe7DWouQSeScFiBP2Zbf3KfjnJX9dT0N0NI5mJr9EzbnguX_Nmyytd1IXfIyBev0UctHwphH0lrPe6B1nveWsQejMOds-7xMWO1H33_QPbBZ82wko93wZKOjoBpoddUMgl3Tnh_cT_gLi-5JB</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2232095425</pqid></control><display><type>article</type><title>BIM-based automated construction waste estimation algorithms: The case of concrete and drywall waste streams</title><source>MEDLINE</source><source>ScienceDirect Journals (5 years ago - present)</source><creator>Guerra, Beatriz C. ; Bakchan, Amal ; Leite, Fernanda ; Faust, Kasey M.</creator><creatorcontrib>Guerra, Beatriz C. ; Bakchan, Amal ; Leite, Fernanda ; Faust, Kasey M.</creatorcontrib><description>•BIM-based quantity takeoff reliability validated using cloud-based software.•Method relying on linear equations, BIM quantity takeoff and purchasing records.•Method demonstration through algorithms to estimate concrete and drywall waste.•Waste estimations validated with real-world project data and data from literature.
Globally, the growth of construction activities over the past years has resulted in large quantities of waste generation. Much of this waste is not reused or recycled and is subsequently redirected to landfills. The environmental impact of construction waste (CW) generation and the shortage of land resources for the creation of new landfills have reinforced the need to adopt more innovative CW management practices. Estimation of CW is a necessary step for the adoption of CW management practices. In this study, Building Information Modeling (BIM) is used to automate CW quantification. In this context, CW generation is estimated as the materials purchased but not incorporated into the actual building structure. Algorithms developed to quantify concrete and drywall waste streams are presented to demonstrate the proposed CW estimation method. The proposed concrete algorithm is validated by comparing estimated waste to actual waste data reported in the waste hauling tickets of a real-world project. Furthermore, CW generation quantities reported in the literature are used to validate estimates of both concrete and drywall waste streams. By leveraging material quantities directly from BIM—as opposed to manual estimations—CW estimation can be streamlined, enabling decision makers to implement more efficient construction waste management practices in the field.</description><identifier>ISSN: 0956-053X</identifier><identifier>EISSN: 1879-2456</identifier><identifier>DOI: 10.1016/j.wasman.2019.03.010</identifier><identifier>PMID: 31109587</identifier><language>eng</language><publisher>United States: Elsevier Ltd</publisher><subject>Algorithms ; Automated estimation ; Building Information Modeling (BIM) ; Concrete ; Construction Materials ; Construction waste ; Drywall ; Industrial Waste ; Recycling ; Waste Disposal Facilities ; Waste Management</subject><ispartof>Waste management (Elmsford), 2019-03, Vol.87, p.825-832</ispartof><rights>2019 Elsevier Ltd</rights><rights>Copyright © 2019 Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c399t-68018a66cf5ab9ce92194531afda913abe29bb5c1bb60f731f0bbb162612d6303</citedby><cites>FETCH-LOGICAL-c399t-68018a66cf5ab9ce92194531afda913abe29bb5c1bb60f731f0bbb162612d6303</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.wasman.2019.03.010$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3548,27922,27923,45993</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31109587$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Guerra, Beatriz C.</creatorcontrib><creatorcontrib>Bakchan, Amal</creatorcontrib><creatorcontrib>Leite, Fernanda</creatorcontrib><creatorcontrib>Faust, Kasey M.</creatorcontrib><title>BIM-based automated construction waste estimation algorithms: The case of concrete and drywall waste streams</title><title>Waste management (Elmsford)</title><addtitle>Waste Manag</addtitle><description>•BIM-based quantity takeoff reliability validated using cloud-based software.•Method relying on linear equations, BIM quantity takeoff and purchasing records.•Method demonstration through algorithms to estimate concrete and drywall waste.•Waste estimations validated with real-world project data and data from literature.
Globally, the growth of construction activities over the past years has resulted in large quantities of waste generation. Much of this waste is not reused or recycled and is subsequently redirected to landfills. The environmental impact of construction waste (CW) generation and the shortage of land resources for the creation of new landfills have reinforced the need to adopt more innovative CW management practices. Estimation of CW is a necessary step for the adoption of CW management practices. In this study, Building Information Modeling (BIM) is used to automate CW quantification. In this context, CW generation is estimated as the materials purchased but not incorporated into the actual building structure. Algorithms developed to quantify concrete and drywall waste streams are presented to demonstrate the proposed CW estimation method. The proposed concrete algorithm is validated by comparing estimated waste to actual waste data reported in the waste hauling tickets of a real-world project. Furthermore, CW generation quantities reported in the literature are used to validate estimates of both concrete and drywall waste streams. By leveraging material quantities directly from BIM—as opposed to manual estimations—CW estimation can be streamlined, enabling decision makers to implement more efficient construction waste management practices in the field.</description><subject>Algorithms</subject><subject>Automated estimation</subject><subject>Building Information Modeling (BIM)</subject><subject>Concrete</subject><subject>Construction Materials</subject><subject>Construction waste</subject><subject>Drywall</subject><subject>Industrial Waste</subject><subject>Recycling</subject><subject>Waste Disposal Facilities</subject><subject>Waste Management</subject><issn>0956-053X</issn><issn>1879-2456</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kEFP3DAQhS1UVBboP0BVjr0knbETb8yhUkFAkah6Aak3y3YmJaskBtsB8e_r1W575GTL8948v4-xM4QKAeXXTfVq4mTmigOqCkQFCAdshe1albxu5Ae2AtXIEhrx-4gdx7gBwLpF-MiOBGKetesVGy9uf5bWROoKsyQ_mZRvzs8xhcWlwc9FTklUUExDHm4fzPjHhyE9TvG8uH-kwmV34futywXKWjN3RRfeXs047t15G5kpnrLD3oyRPu3PE_ZwfXV_-aO8-3Vze_n9rnRCqVTKFrA1Urq-MVY5UhxV3Qg0fWcUCmOJK2sbh9ZK6NcCe7DWouQSeScFiBP2Zbf3KfjnJX9dT0N0NI5mJr9EzbnguX_Nmyytd1IXfIyBev0UctHwphH0lrPe6B1nveWsQejMOds-7xMWO1H33_QPbBZ82wko93wZKOjoBpoddUMgl3Tnh_cT_gLi-5JB</recordid><startdate>20190315</startdate><enddate>20190315</enddate><creator>Guerra, Beatriz C.</creator><creator>Bakchan, Amal</creator><creator>Leite, Fernanda</creator><creator>Faust, Kasey M.</creator><general>Elsevier Ltd</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20190315</creationdate><title>BIM-based automated construction waste estimation algorithms: The case of concrete and drywall waste streams</title><author>Guerra, Beatriz C. ; Bakchan, Amal ; Leite, Fernanda ; Faust, Kasey M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c399t-68018a66cf5ab9ce92194531afda913abe29bb5c1bb60f731f0bbb162612d6303</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Algorithms</topic><topic>Automated estimation</topic><topic>Building Information Modeling (BIM)</topic><topic>Concrete</topic><topic>Construction Materials</topic><topic>Construction waste</topic><topic>Drywall</topic><topic>Industrial Waste</topic><topic>Recycling</topic><topic>Waste Disposal Facilities</topic><topic>Waste Management</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Guerra, Beatriz C.</creatorcontrib><creatorcontrib>Bakchan, Amal</creatorcontrib><creatorcontrib>Leite, Fernanda</creatorcontrib><creatorcontrib>Faust, Kasey M.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Waste management (Elmsford)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Guerra, Beatriz C.</au><au>Bakchan, Amal</au><au>Leite, Fernanda</au><au>Faust, Kasey M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>BIM-based automated construction waste estimation algorithms: The case of concrete and drywall waste streams</atitle><jtitle>Waste management (Elmsford)</jtitle><addtitle>Waste Manag</addtitle><date>2019-03-15</date><risdate>2019</risdate><volume>87</volume><spage>825</spage><epage>832</epage><pages>825-832</pages><issn>0956-053X</issn><eissn>1879-2456</eissn><abstract>•BIM-based quantity takeoff reliability validated using cloud-based software.•Method relying on linear equations, BIM quantity takeoff and purchasing records.•Method demonstration through algorithms to estimate concrete and drywall waste.•Waste estimations validated with real-world project data and data from literature.
Globally, the growth of construction activities over the past years has resulted in large quantities of waste generation. Much of this waste is not reused or recycled and is subsequently redirected to landfills. The environmental impact of construction waste (CW) generation and the shortage of land resources for the creation of new landfills have reinforced the need to adopt more innovative CW management practices. Estimation of CW is a necessary step for the adoption of CW management practices. In this study, Building Information Modeling (BIM) is used to automate CW quantification. In this context, CW generation is estimated as the materials purchased but not incorporated into the actual building structure. Algorithms developed to quantify concrete and drywall waste streams are presented to demonstrate the proposed CW estimation method. The proposed concrete algorithm is validated by comparing estimated waste to actual waste data reported in the waste hauling tickets of a real-world project. Furthermore, CW generation quantities reported in the literature are used to validate estimates of both concrete and drywall waste streams. By leveraging material quantities directly from BIM—as opposed to manual estimations—CW estimation can be streamlined, enabling decision makers to implement more efficient construction waste management practices in the field.</abstract><cop>United States</cop><pub>Elsevier Ltd</pub><pmid>31109587</pmid><doi>10.1016/j.wasman.2019.03.010</doi><tpages>8</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0956-053X |
ispartof | Waste management (Elmsford), 2019-03, Vol.87, p.825-832 |
issn | 0956-053X 1879-2456 |
language | eng |
recordid | cdi_proquest_miscellaneous_2232095425 |
source | MEDLINE; ScienceDirect Journals (5 years ago - present) |
subjects | Algorithms Automated estimation Building Information Modeling (BIM) Concrete Construction Materials Construction waste Drywall Industrial Waste Recycling Waste Disposal Facilities Waste Management |
title | BIM-based automated construction waste estimation algorithms: The case of concrete and drywall waste streams |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-09T23%3A31%3A35IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=BIM-based%20automated%20construction%20waste%20estimation%20algorithms:%20The%20case%20of%20concrete%20and%20drywall%20waste%20streams&rft.jtitle=Waste%20management%20(Elmsford)&rft.au=Guerra,%20Beatriz%20C.&rft.date=2019-03-15&rft.volume=87&rft.spage=825&rft.epage=832&rft.pages=825-832&rft.issn=0956-053X&rft.eissn=1879-2456&rft_id=info:doi/10.1016/j.wasman.2019.03.010&rft_dat=%3Cproquest_cross%3E2232095425%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2232095425&rft_id=info:pmid/31109587&rft_els_id=S0956053X1930131X&rfr_iscdi=true |