MONITORING TRACTOR PERFORMANCE USING SHEWHART AND EXPONENTIALLY WEIGHTED MOVING AVERAGE CHARTS

Detalhes bibliográficos
Autor(a) principal: Voltarelli,Murilo A.
Data de Publicação: 2021
Outros Autores: Paixão,Carla S. S., Oliveira,Bruno R. de, Angelo,Eduardo P., Silva,Rouverson P. da
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Engenharia Agrícola
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162021000100062
Resumo: ABSTRACT Statistical process control has been widely used in agricultural operations for monitoring and improving process quality. This study aims to evaluate the Shewhart and exponentially weighted moving average (EWMA) control charts to monitor the performance of an agricultural tractor–planter set. The design is completely randomized based on the assumptions of statistical process control and comprises two treatments: day and night shift treatments. The data to assess the performance of the tractor–planter set are collected during the day and night shifts and used to evaluate the operating speed, motor rotation, engine oil pressure and water temperature, and hourly fuel consumption. The dataset comprised 40 samples compiled from the frontal monitor column inside a tractor cab. It is concluded that both Shewhart and MMEP/EWMA control charts can be used to evaluate engine performance based on the quality indicator parameters investigated, regardless of the normality assumption of the datasets.
id SBEA-1_8c4743b7e77e19547a6156967026b1ea
oai_identifier_str oai:scielo:S0100-69162021000100062
network_acronym_str SBEA-1
network_name_str Engenharia Agrícola
repository_id_str
spelling MONITORING TRACTOR PERFORMANCE USING SHEWHART AND EXPONENTIALLY WEIGHTED MOVING AVERAGE CHARTSstatistical process controlmanagement operationsagricultural mechanizationABSTRACT Statistical process control has been widely used in agricultural operations for monitoring and improving process quality. This study aims to evaluate the Shewhart and exponentially weighted moving average (EWMA) control charts to monitor the performance of an agricultural tractor–planter set. The design is completely randomized based on the assumptions of statistical process control and comprises two treatments: day and night shift treatments. The data to assess the performance of the tractor–planter set are collected during the day and night shifts and used to evaluate the operating speed, motor rotation, engine oil pressure and water temperature, and hourly fuel consumption. The dataset comprised 40 samples compiled from the frontal monitor column inside a tractor cab. It is concluded that both Shewhart and MMEP/EWMA control charts can be used to evaluate engine performance based on the quality indicator parameters investigated, regardless of the normality assumption of the datasets.Associação Brasileira de Engenharia Agrícola2021-02-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162021000100062Engenharia Agrícola v.41 n.1 2021reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/1809-4430-eng.agric.v41n1p62-69/2021info:eu-repo/semantics/openAccessVoltarelli,Murilo A.Paixão,Carla S. S.Oliveira,Bruno R. deAngelo,Eduardo P.Silva,Rouverson P. daeng2021-02-25T00:00:00Zoai:scielo:S0100-69162021000100062Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2021-02-25T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false
dc.title.none.fl_str_mv MONITORING TRACTOR PERFORMANCE USING SHEWHART AND EXPONENTIALLY WEIGHTED MOVING AVERAGE CHARTS
title MONITORING TRACTOR PERFORMANCE USING SHEWHART AND EXPONENTIALLY WEIGHTED MOVING AVERAGE CHARTS
spellingShingle MONITORING TRACTOR PERFORMANCE USING SHEWHART AND EXPONENTIALLY WEIGHTED MOVING AVERAGE CHARTS
Voltarelli,Murilo A.
statistical process control
management operations
agricultural mechanization
title_short MONITORING TRACTOR PERFORMANCE USING SHEWHART AND EXPONENTIALLY WEIGHTED MOVING AVERAGE CHARTS
title_full MONITORING TRACTOR PERFORMANCE USING SHEWHART AND EXPONENTIALLY WEIGHTED MOVING AVERAGE CHARTS
title_fullStr MONITORING TRACTOR PERFORMANCE USING SHEWHART AND EXPONENTIALLY WEIGHTED MOVING AVERAGE CHARTS
title_full_unstemmed MONITORING TRACTOR PERFORMANCE USING SHEWHART AND EXPONENTIALLY WEIGHTED MOVING AVERAGE CHARTS
title_sort MONITORING TRACTOR PERFORMANCE USING SHEWHART AND EXPONENTIALLY WEIGHTED MOVING AVERAGE CHARTS
author Voltarelli,Murilo A.
author_facet Voltarelli,Murilo A.
Paixão,Carla S. S.
Oliveira,Bruno R. de
Angelo,Eduardo P.
Silva,Rouverson P. da
author_role author
author2 Paixão,Carla S. S.
Oliveira,Bruno R. de
Angelo,Eduardo P.
Silva,Rouverson P. da
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Voltarelli,Murilo A.
Paixão,Carla S. S.
Oliveira,Bruno R. de
Angelo,Eduardo P.
Silva,Rouverson P. da
dc.subject.por.fl_str_mv statistical process control
management operations
agricultural mechanization
topic statistical process control
management operations
agricultural mechanization
description ABSTRACT Statistical process control has been widely used in agricultural operations for monitoring and improving process quality. This study aims to evaluate the Shewhart and exponentially weighted moving average (EWMA) control charts to monitor the performance of an agricultural tractor–planter set. The design is completely randomized based on the assumptions of statistical process control and comprises two treatments: day and night shift treatments. The data to assess the performance of the tractor–planter set are collected during the day and night shifts and used to evaluate the operating speed, motor rotation, engine oil pressure and water temperature, and hourly fuel consumption. The dataset comprised 40 samples compiled from the frontal monitor column inside a tractor cab. It is concluded that both Shewhart and MMEP/EWMA control charts can be used to evaluate engine performance based on the quality indicator parameters investigated, regardless of the normality assumption of the datasets.
publishDate 2021
dc.date.none.fl_str_mv 2021-02-01
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=S0100-69162021000100062
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162021000100062
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1809-4430-eng.agric.v41n1p62-69/2021
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 Associação Brasileira de Engenharia Agrícola
publisher.none.fl_str_mv Associação Brasileira de Engenharia Agrícola
dc.source.none.fl_str_mv Engenharia Agrícola v.41 n.1 2021
reponame:Engenharia Agrícola
instname:Associação Brasileira de Engenharia Agrícola (SBEA)
instacron:SBEA
instname_str Associação Brasileira de Engenharia Agrícola (SBEA)
instacron_str SBEA
institution SBEA
reponame_str Engenharia Agrícola
collection Engenharia Agrícola
repository.name.fl_str_mv Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)
repository.mail.fl_str_mv revistasbea@sbea.org.br||sbea@sbea.org.br
_version_ 1752126274928640000

Registros relacionados