Management of mechanized harvesting through operational modeling

Bibliographic Details
Main Author: Ferraz Dias Neto, Américo
Publication Date: 2022
Other Authors: Albiero, Daniel, Rossetto, Raffaella, Domingos Biagi, João
Format: Article
Language: eng
Source: Revista ciência agronômica (Online)
Download full: http://periodicos.ufc.br/revistacienciaagronomica/article/view/84997
Summary: The activity of agricultural experimentation may require high budget and long periods of time for obtaining data. Due to production features, decision-making processes within agro-industrial mills that use sugarcane as raw material must be optimized. In this scenario, modeling operating systems that use embedded technology as agricultural automation enables the optimization of decision-making and influences operational performance and costs. This article presents a model for receiving and processing sugarcane based on its harvesting capacity, considering the harvestability index and the nominal capacity of the harvester. Sensitivity analysis enables the assessment of potential offenders and the reallocation of assets, thus optimizing resources and ensuring plant operation. This analysis also enables new possibilities, such as harvesting under different row spacings and harvesting simultaneously different rows.
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spelling Management of mechanized harvesting through operational modelingSugarcane harvest and loading. Modeling. Agricultural automation.The activity of agricultural experimentation may require high budget and long periods of time for obtaining data. Due to production features, decision-making processes within agro-industrial mills that use sugarcane as raw material must be optimized. In this scenario, modeling operating systems that use embedded technology as agricultural automation enables the optimization of decision-making and influences operational performance and costs. This article presents a model for receiving and processing sugarcane based on its harvesting capacity, considering the harvestability index and the nominal capacity of the harvester. Sensitivity analysis enables the assessment of potential offenders and the reallocation of assets, thus optimizing resources and ensuring plant operation. This analysis also enables new possibilities, such as harvesting under different row spacings and harvesting simultaneously different rows.Revista Ciência Agronômica2022-11-29info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://periodicos.ufc.br/revistacienciaagronomica/article/view/84997Revista Ciência Agronômica; v. 54 (2023)1806-66900045-6888reponame:Revista ciência agronômica (Online)instname:Universidade Federal do Ceará (UFC)instacron:UFCenghttp://periodicos.ufc.br/revistacienciaagronomica/article/view/84997/229149Copyright (c) 2022 Revista Ciência Agronômicainfo:eu-repo/semantics/openAccessFerraz Dias Neto, AméricoAlbiero, DanielRossetto, RaffaellaDomingos Biagi, João2023-07-06T10:49:18Zoai:periodicos.ufc:article/84997Revistahttps://periodicos.ufc.br/revistacienciaagronomicaPUBhttps://periodicos.ufc.br/revistacienciaagronomica/oai||alekdutra@ufc.br|| ccarev@ufc.br1806-66900045-6888opendoar:2023-07-06T10:49:18Revista ciência agronômica (Online) - Universidade Federal do Ceará (UFC)false
dc.title.none.fl_str_mv Management of mechanized harvesting through operational modeling
title Management of mechanized harvesting through operational modeling
spellingShingle Management of mechanized harvesting through operational modeling
Ferraz Dias Neto, Américo
Sugarcane harvest and loading. Modeling. Agricultural automation.
title_short Management of mechanized harvesting through operational modeling
title_full Management of mechanized harvesting through operational modeling
title_fullStr Management of mechanized harvesting through operational modeling
title_full_unstemmed Management of mechanized harvesting through operational modeling
title_sort Management of mechanized harvesting through operational modeling
author Ferraz Dias Neto, Américo
author_facet Ferraz Dias Neto, Américo
Albiero, Daniel
Rossetto, Raffaella
Domingos Biagi, João
author_role author
author2 Albiero, Daniel
Rossetto, Raffaella
Domingos Biagi, João
author2_role author
author
author
dc.contributor.author.fl_str_mv Ferraz Dias Neto, Américo
Albiero, Daniel
Rossetto, Raffaella
Domingos Biagi, João
dc.subject.por.fl_str_mv Sugarcane harvest and loading. Modeling. Agricultural automation.
topic Sugarcane harvest and loading. Modeling. Agricultural automation.
description The activity of agricultural experimentation may require high budget and long periods of time for obtaining data. Due to production features, decision-making processes within agro-industrial mills that use sugarcane as raw material must be optimized. In this scenario, modeling operating systems that use embedded technology as agricultural automation enables the optimization of decision-making and influences operational performance and costs. This article presents a model for receiving and processing sugarcane based on its harvesting capacity, considering the harvestability index and the nominal capacity of the harvester. Sensitivity analysis enables the assessment of potential offenders and the reallocation of assets, thus optimizing resources and ensuring plant operation. This analysis also enables new possibilities, such as harvesting under different row spacings and harvesting simultaneously different rows.
publishDate 2022
dc.date.none.fl_str_mv 2022-11-29
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://periodicos.ufc.br/revistacienciaagronomica/article/view/84997
url http://periodicos.ufc.br/revistacienciaagronomica/article/view/84997
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv http://periodicos.ufc.br/revistacienciaagronomica/article/view/84997/229149
dc.rights.driver.fl_str_mv Copyright (c) 2022 Revista Ciência Agronômica
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2022 Revista Ciência Agronômica
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Revista Ciência Agronômica
publisher.none.fl_str_mv Revista Ciência Agronômica
dc.source.none.fl_str_mv Revista Ciência Agronômica; v. 54 (2023)
1806-6690
0045-6888
reponame:Revista ciência agronômica (Online)
instname:Universidade Federal do Ceará (UFC)
instacron:UFC
instname_str Universidade Federal do Ceará (UFC)
instacron_str UFC
institution UFC
reponame_str Revista ciência agronômica (Online)
collection Revista ciência agronômica (Online)
repository.name.fl_str_mv Revista ciência agronômica (Online) - Universidade Federal do Ceará (UFC)
repository.mail.fl_str_mv ||alekdutra@ufc.br|| ccarev@ufc.br
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