Monitoring performance indicators of mechanized agricultural operations through a systemic method

Detalhes bibliográficos
Autor(a) principal: Peloia,Paulo Rodrigues
Data de Publicação: 2023
Outros Autores: Milan,Marcos, Romanelli,Thiago Libório, Gimenez,Leandro Maria
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.
id USP-18_e067d5a061fb24452fdb7ba80fca46e6
oai_identifier_str oai:scielo:S0103-90162023000100101
network_acronym_str USP-18
network_name_str Scientia Agrícola (Online)
repository_id_str
spelling 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