Mathematical modeling to optimize pine lumber yield

Mathematical modeling to optimize pine lumber yield

In Brazil, only 4% of the 7.84 million hectares of planted forests is devoted to the production of lumber wood, being in Santa Catarina state most of the wood used for this purpose is of the Pinus genus. This work aims to estimate the maximum utilization of logs due to the production of wood boards...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Advances in Forestry Science 2020-04, Vol.7 (1), p.877
Hauptverfasser: Bonfatti Júnior, Eraldo Antonio, Lengowski, Elaine Cristina, De Almeida Sfeir, Tamires, Gruber Nisponginski, Bruno, Fanes, Kaio, Cunha Dickow, Kauana Melissa
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue 1
container_start_page 877
container_title Advances in Forestry Science
container_volume 7
creator Bonfatti Júnior, Eraldo Antonio
Lengowski, Elaine Cristina
De Almeida Sfeir, Tamires
Gruber Nisponginski, Bruno
Fanes, Kaio
Cunha Dickow, Kauana Melissa
description In Brazil, only 4% of the 7.84 million hectares of planted forests is devoted to the production of lumber wood, being in Santa Catarina state most of the wood used for this purpose is of the Pinus genus. This work aims to estimate the maximum utilization of logs due to the production of wood boards in the city of Canoinhas, Santa Catarina. For that, a sawmill of the region were consulted and the dimensions of the pieces produced were verified. The dimensions and classes of logs commonly traded in the region were also raised. As a result, 82 models were created in Maxitora software in diagram format. With the cutting models the sawmill had its performance optimized with the use of techniques of operational research in a cutting problem. The whole linear programming technique was used for an estimated demand for the quantity of each of the pieces produced. The results showed that only five models are required to meet such demand, so the yield is 43.18%.
doi_str_mv 10.34062/afs.v7i1.9767
format Article
fullrecord <record><control><sourceid>crossref</sourceid><recordid>TN_cdi_crossref_primary_10_34062_afs_v7i1_9767</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>10_34062_afs_v7i1_9767</sourcerecordid><originalsourceid>FETCH-crossref_primary_10_34062_afs_v7i1_97673</originalsourceid><addsrcrecordid>eNqVzrEOgjAUheHGaCJRVue-ANhSoXQ2Ghc396ZA0Zu0QNpqgk-vEF_A6fzLST6EdpSk7ECKbK9an7440FTwgi9QlLGcJyUt6XJukRQ5J2sUew8VyZjIhMiLCLGrCg9tVYBaGWz7Rhvo7jj0uB8CWHhrPECnsXnaSjs8gjbNFq1aZbyOf7tB6fl0O16S2vXeO93KwYFVbpSUyFknvzo56eSkY38fPpsPQ6M</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Mathematical modeling to optimize pine lumber yield</title><source>DOAJ Directory of Open Access Journals</source><creator>Bonfatti Júnior, Eraldo Antonio ; Lengowski, Elaine Cristina ; De Almeida Sfeir, Tamires ; Gruber Nisponginski, Bruno ; Fanes, Kaio ; Cunha Dickow, Kauana Melissa</creator><creatorcontrib>Bonfatti Júnior, Eraldo Antonio ; Lengowski, Elaine Cristina ; De Almeida Sfeir, Tamires ; Gruber Nisponginski, Bruno ; Fanes, Kaio ; Cunha Dickow, Kauana Melissa</creatorcontrib><description>In Brazil, only 4% of the 7.84 million hectares of planted forests is devoted to the production of lumber wood, being in Santa Catarina state most of the wood used for this purpose is of the Pinus genus. This work aims to estimate the maximum utilization of logs due to the production of wood boards in the city of Canoinhas, Santa Catarina. For that, a sawmill of the region were consulted and the dimensions of the pieces produced were verified. The dimensions and classes of logs commonly traded in the region were also raised. As a result, 82 models were created in Maxitora software in diagram format. With the cutting models the sawmill had its performance optimized with the use of techniques of operational research in a cutting problem. The whole linear programming technique was used for an estimated demand for the quantity of each of the pieces produced. The results showed that only five models are required to meet such demand, so the yield is 43.18%.</description><identifier>ISSN: 2359-6570</identifier><identifier>EISSN: 2357-8181</identifier><identifier>DOI: 10.34062/afs.v7i1.9767</identifier><language>eng</language><ispartof>Advances in Forestry Science, 2020-04, Vol.7 (1), p.877</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0002-3475-4711 ; 0000-0002-2730-7681 ; 0000-0002-7336-7626 ; 0000-0002-5330-6703 ; 0000-0002-3228-383X ; 0000-0003-0813-9368</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,864,27924,27925</link.rule.ids></links><search><creatorcontrib>Bonfatti Júnior, Eraldo Antonio</creatorcontrib><creatorcontrib>Lengowski, Elaine Cristina</creatorcontrib><creatorcontrib>De Almeida Sfeir, Tamires</creatorcontrib><creatorcontrib>Gruber Nisponginski, Bruno</creatorcontrib><creatorcontrib>Fanes, Kaio</creatorcontrib><creatorcontrib>Cunha Dickow, Kauana Melissa</creatorcontrib><title>Mathematical modeling to optimize pine lumber yield</title><title>Advances in Forestry Science</title><description>In Brazil, only 4% of the 7.84 million hectares of planted forests is devoted to the production of lumber wood, being in Santa Catarina state most of the wood used for this purpose is of the Pinus genus. This work aims to estimate the maximum utilization of logs due to the production of wood boards in the city of Canoinhas, Santa Catarina. For that, a sawmill of the region were consulted and the dimensions of the pieces produced were verified. The dimensions and classes of logs commonly traded in the region were also raised. As a result, 82 models were created in Maxitora software in diagram format. With the cutting models the sawmill had its performance optimized with the use of techniques of operational research in a cutting problem. The whole linear programming technique was used for an estimated demand for the quantity of each of the pieces produced. The results showed that only five models are required to meet such demand, so the yield is 43.18%.</description><issn>2359-6570</issn><issn>2357-8181</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNqVzrEOgjAUheHGaCJRVue-ANhSoXQ2Ghc396ZA0Zu0QNpqgk-vEF_A6fzLST6EdpSk7ECKbK9an7440FTwgi9QlLGcJyUt6XJukRQ5J2sUew8VyZjIhMiLCLGrCg9tVYBaGWz7Rhvo7jj0uB8CWHhrPECnsXnaSjs8gjbNFq1aZbyOf7tB6fl0O16S2vXeO93KwYFVbpSUyFknvzo56eSkY38fPpsPQ6M</recordid><startdate>20200403</startdate><enddate>20200403</enddate><creator>Bonfatti Júnior, Eraldo Antonio</creator><creator>Lengowski, Elaine Cristina</creator><creator>De Almeida Sfeir, Tamires</creator><creator>Gruber Nisponginski, Bruno</creator><creator>Fanes, Kaio</creator><creator>Cunha Dickow, Kauana Melissa</creator><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0002-3475-4711</orcidid><orcidid>https://orcid.org/0000-0002-2730-7681</orcidid><orcidid>https://orcid.org/0000-0002-7336-7626</orcidid><orcidid>https://orcid.org/0000-0002-5330-6703</orcidid><orcidid>https://orcid.org/0000-0002-3228-383X</orcidid><orcidid>https://orcid.org/0000-0003-0813-9368</orcidid></search><sort><creationdate>20200403</creationdate><title>Mathematical modeling to optimize pine lumber yield</title><author>Bonfatti Júnior, Eraldo Antonio ; Lengowski, Elaine Cristina ; De Almeida Sfeir, Tamires ; Gruber Nisponginski, Bruno ; Fanes, Kaio ; Cunha Dickow, Kauana Melissa</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-crossref_primary_10_34062_afs_v7i1_97673</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><toplevel>online_resources</toplevel><creatorcontrib>Bonfatti Júnior, Eraldo Antonio</creatorcontrib><creatorcontrib>Lengowski, Elaine Cristina</creatorcontrib><creatorcontrib>De Almeida Sfeir, Tamires</creatorcontrib><creatorcontrib>Gruber Nisponginski, Bruno</creatorcontrib><creatorcontrib>Fanes, Kaio</creatorcontrib><creatorcontrib>Cunha Dickow, Kauana Melissa</creatorcontrib><collection>CrossRef</collection><jtitle>Advances in Forestry Science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bonfatti Júnior, Eraldo Antonio</au><au>Lengowski, Elaine Cristina</au><au>De Almeida Sfeir, Tamires</au><au>Gruber Nisponginski, Bruno</au><au>Fanes, Kaio</au><au>Cunha Dickow, Kauana Melissa</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Mathematical modeling to optimize pine lumber yield</atitle><jtitle>Advances in Forestry Science</jtitle><date>2020-04-03</date><risdate>2020</risdate><volume>7</volume><issue>1</issue><spage>877</spage><pages>877-</pages><issn>2359-6570</issn><eissn>2357-8181</eissn><abstract>In Brazil, only 4% of the 7.84 million hectares of planted forests is devoted to the production of lumber wood, being in Santa Catarina state most of the wood used for this purpose is of the Pinus genus. This work aims to estimate the maximum utilization of logs due to the production of wood boards in the city of Canoinhas, Santa Catarina. For that, a sawmill of the region were consulted and the dimensions of the pieces produced were verified. The dimensions and classes of logs commonly traded in the region were also raised. As a result, 82 models were created in Maxitora software in diagram format. With the cutting models the sawmill had its performance optimized with the use of techniques of operational research in a cutting problem. The whole linear programming technique was used for an estimated demand for the quantity of each of the pieces produced. The results showed that only five models are required to meet such demand, so the yield is 43.18%.</abstract><doi>10.34062/afs.v7i1.9767</doi><orcidid>https://orcid.org/0000-0002-3475-4711</orcidid><orcidid>https://orcid.org/0000-0002-2730-7681</orcidid><orcidid>https://orcid.org/0000-0002-7336-7626</orcidid><orcidid>https://orcid.org/0000-0002-5330-6703</orcidid><orcidid>https://orcid.org/0000-0002-3228-383X</orcidid><orcidid>https://orcid.org/0000-0003-0813-9368</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 2359-6570
ispartof Advances in Forestry Science, 2020-04, Vol.7 (1), p.877
issn 2359-6570
2357-8181
language eng
recordid cdi_crossref_primary_10_34062_afs_v7i1_9767
source DOAJ Directory of Open Access Journals
title Mathematical modeling to optimize pine lumber yield
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-22T20%3A41%3A46IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-crossref&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Mathematical%20modeling%20to%20optimize%20pine%20lumber%20yield&rft.jtitle=Advances%20in%20Forestry%20Science&rft.au=Bonfatti%20J%C3%BAnior,%20Eraldo%20Antonio&rft.date=2020-04-03&rft.volume=7&rft.issue=1&rft.spage=877&rft.pages=877-&rft.issn=2359-6570&rft.eissn=2357-8181&rft_id=info:doi/10.34062/afs.v7i1.9767&rft_dat=%3Ccrossref%3E10_34062_afs_v7i1_9767%3C/crossref%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true