Management of mechanized harvesting through operational modeling
Main Author: | |
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Publication Date: | 2022 |
Other Authors: | , , |
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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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 |
_version_ |
1826232467074318336 |