Monitoring performance indicators of mechanized agricultural operations through a systemic method
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Scientia Agrícola (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162023000100101 |
Resumo: | ABSTRACT: Key performance indicators (KPI) are essential to decision-making in an organization, but the approach to analysis and composition used in the formulation of the KPIs can lead to errors. Analysis based only on averages does not allow for discriminating between variations that are natural to the process or special cases which require investigation. The use of control charts can identify this differentiation. However, when several charts are presented encompassing different measurement units and scales, systemic interpretation can be impaired. To assist in this interpretation, this research study aimed at proposing a method to facilitate the analysis of control charts when multiple indicators are employed in the monitoring of agricultural operations. Based on the data obtained over 26 weeks from a mechanized sugarcane (Saccharum officinarum L.) harvesting front, six indicators were defined and analyzed through individual control charts and, systemically, through a standardized group control chart. Results show that the points identified as being outside the control zone (special causes of variation) according to the standardized group control chart were the same as those identified by the six individual charts, which demonstrates the potential of this method to summarize the information with no loss of quality of analysis. |
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Scientia Agrícola (Online) |
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|
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Monitoring performance indicators of mechanized agricultural operations through a systemic methodKPImanagementcontrol chartagricultural mechanizationsugarcane harvestABSTRACT: Key performance indicators (KPI) are essential to decision-making in an organization, but the approach to analysis and composition used in the formulation of the KPIs can lead to errors. Analysis based only on averages does not allow for discriminating between variations that are natural to the process or special cases which require investigation. The use of control charts can identify this differentiation. However, when several charts are presented encompassing different measurement units and scales, systemic interpretation can be impaired. To assist in this interpretation, this research study aimed at proposing a method to facilitate the analysis of control charts when multiple indicators are employed in the monitoring of agricultural operations. Based on the data obtained over 26 weeks from a mechanized sugarcane (Saccharum officinarum L.) harvesting front, six indicators were defined and analyzed through individual control charts and, systemically, through a standardized group control chart. Results show that the points identified as being outside the control zone (special causes of variation) according to the standardized group control chart were the same as those identified by the six individual charts, which demonstrates the potential of this method to summarize the information with no loss of quality of analysis.Escola Superior de Agricultura "Luiz de Queiroz"2023-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162023000100101Scientia Agricola v.80 2023reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USP10.1590/1678-992x-2021-0143info:eu-repo/semantics/openAccessPeloia,Paulo RodriguesMilan,MarcosRomanelli,Thiago LibórioGimenez,Leandro Mariaeng2022-02-21T00:00:00Zoai:scielo:S0103-90162023000100101Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2022-02-21T00:00Scientia Agrícola (Online) - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Monitoring performance indicators of mechanized agricultural operations through a systemic method |
title |
Monitoring performance indicators of mechanized agricultural operations through a systemic method |
spellingShingle |
Monitoring performance indicators of mechanized agricultural operations through a systemic method Peloia,Paulo Rodrigues KPI management control chart agricultural mechanization sugarcane harvest |
title_short |
Monitoring performance indicators of mechanized agricultural operations through a systemic method |
title_full |
Monitoring performance indicators of mechanized agricultural operations through a systemic method |
title_fullStr |
Monitoring performance indicators of mechanized agricultural operations through a systemic method |
title_full_unstemmed |
Monitoring performance indicators of mechanized agricultural operations through a systemic method |
title_sort |
Monitoring performance indicators of mechanized agricultural operations through a systemic method |
author |
Peloia,Paulo Rodrigues |
author_facet |
Peloia,Paulo Rodrigues Milan,Marcos Romanelli,Thiago Libório Gimenez,Leandro Maria |
author_role |
author |
author2 |
Milan,Marcos Romanelli,Thiago Libório Gimenez,Leandro Maria |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Peloia,Paulo Rodrigues Milan,Marcos Romanelli,Thiago Libório Gimenez,Leandro Maria |
dc.subject.por.fl_str_mv |
KPI management control chart agricultural mechanization sugarcane harvest |
topic |
KPI management control chart agricultural mechanization sugarcane harvest |
description |
ABSTRACT: Key performance indicators (KPI) are essential to decision-making in an organization, but the approach to analysis and composition used in the formulation of the KPIs can lead to errors. Analysis based only on averages does not allow for discriminating between variations that are natural to the process or special cases which require investigation. The use of control charts can identify this differentiation. However, when several charts are presented encompassing different measurement units and scales, systemic interpretation can be impaired. To assist in this interpretation, this research study aimed at proposing a method to facilitate the analysis of control charts when multiple indicators are employed in the monitoring of agricultural operations. Based on the data obtained over 26 weeks from a mechanized sugarcane (Saccharum officinarum L.) harvesting front, six indicators were defined and analyzed through individual control charts and, systemically, through a standardized group control chart. Results show that the points identified as being outside the control zone (special causes of variation) according to the standardized group control chart were the same as those identified by the six individual charts, which demonstrates the potential of this method to summarize the information with no loss of quality of analysis. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162023000100101 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162023000100101 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1678-992x-2021-0143 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Escola Superior de Agricultura "Luiz de Queiroz" |
publisher.none.fl_str_mv |
Escola Superior de Agricultura "Luiz de Queiroz" |
dc.source.none.fl_str_mv |
Scientia Agricola v.80 2023 reponame:Scientia Agrícola (Online) instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Scientia Agrícola (Online) |
collection |
Scientia Agrícola (Online) |
repository.name.fl_str_mv |
Scientia Agrícola (Online) - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
scientia@usp.br||alleoni@usp.br |
_version_ |
1748936466129485824 |