StatSSCandlePlot : a new way of monitoring operational performance indicators

Detalhes bibliográficos
Autor(a) principal: Giaquinto, Cláudia Daniela Melo
Data de Publicação: 2019
Outros Autores: Trierweiler, Jorge Otávio, Teixeira, Herbert Campos Gonçalves, Trierweiler, Luciane Ferreira, Farenzena, Marcelo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRGS
Texto Completo: http://hdl.handle.net/10183/214313
Resumo: Operational KPIs play an extremely important role in the process industry, aiding in decision making. However, they need to be reliably calculated to be representative. The present work presents a schematic methodology for the calculation of these KPIs, including techniques of steady-state detection, denoising, error propagation and sensitivity analysis, presented, as far as it is known, in the form of a new graphical tool proposed by the authors named StatSSCandlePlot. The methodology was applied in a real case study of a gas fired boiler in which the indicator studied was its efficiency evaluated by the Stack Loss Method. From the StatSSCandlePlot it was possible to identify the trends of the indicator, the portion of each window in the steady-state, the values to be considered from the indicator and, in a complementary way, to identify the variable that most influences the variation of the indicator, through the sensitivity analysis.
id UFRGS-2_c35a29b17ead16d8e7887f178b2f87c8
oai_identifier_str oai:www.lume.ufrgs.br:10183/214313
network_acronym_str UFRGS-2
network_name_str Repositório Institucional da UFRGS
repository_id_str
spelling Giaquinto, Cláudia Daniela MeloTrierweiler, Jorge OtávioTeixeira, Herbert Campos GonçalvesTrierweiler, Luciane FerreiraFarenzena, Marcelo2020-10-22T04:06:39Z20190104-6632http://hdl.handle.net/10183/214313001118095Operational KPIs play an extremely important role in the process industry, aiding in decision making. However, they need to be reliably calculated to be representative. The present work presents a schematic methodology for the calculation of these KPIs, including techniques of steady-state detection, denoising, error propagation and sensitivity analysis, presented, as far as it is known, in the form of a new graphical tool proposed by the authors named StatSSCandlePlot. The methodology was applied in a real case study of a gas fired boiler in which the indicator studied was its efficiency evaluated by the Stack Loss Method. From the StatSSCandlePlot it was possible to identify the trends of the indicator, the portion of each window in the steady-state, the values to be considered from the indicator and, in a complementary way, to identify the variable that most influences the variation of the indicator, through the sensitivity analysis.application/pdfengBrazilian journal of chemical engineering [recurso eletrônico]. São Paulo. Vol. 36, no. 1 (Jan./Mar. 2019), p. 393-408Indicadores de desempenhoProcessos industriaisGráficosKey performance indicatorsCandlestick chartProcess assessmentStatSSCandlePlot : a new way of monitoring operational performance indicatorsinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/otherinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001118095.pdf.txt001118095.pdf.txtExtracted Texttext/plain60707http://www.lume.ufrgs.br/bitstream/10183/214313/2/001118095.pdf.txt2ef5d10ada917071e5c39d5a676f50b9MD52ORIGINAL001118095.pdfTexto completo (inglês)application/pdf827885http://www.lume.ufrgs.br/bitstream/10183/214313/1/001118095.pdff50ed86b5ad5a96dbc3ccc11ddc43db7MD5110183/2143132021-03-09 04:30:32.598603oai:www.lume.ufrgs.br:10183/214313Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2021-03-09T07:30:32Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false
dc.title.pt_BR.fl_str_mv StatSSCandlePlot : a new way of monitoring operational performance indicators
title StatSSCandlePlot : a new way of monitoring operational performance indicators
spellingShingle StatSSCandlePlot : a new way of monitoring operational performance indicators
Giaquinto, Cláudia Daniela Melo
Indicadores de desempenho
Processos industriais
Gráficos
Key performance indicators
Candlestick chart
Process assessment
title_short StatSSCandlePlot : a new way of monitoring operational performance indicators
title_full StatSSCandlePlot : a new way of monitoring operational performance indicators
title_fullStr StatSSCandlePlot : a new way of monitoring operational performance indicators
title_full_unstemmed StatSSCandlePlot : a new way of monitoring operational performance indicators
title_sort StatSSCandlePlot : a new way of monitoring operational performance indicators
author Giaquinto, Cláudia Daniela Melo
author_facet Giaquinto, Cláudia Daniela Melo
Trierweiler, Jorge Otávio
Teixeira, Herbert Campos Gonçalves
Trierweiler, Luciane Ferreira
Farenzena, Marcelo
author_role author
author2 Trierweiler, Jorge Otávio
Teixeira, Herbert Campos Gonçalves
Trierweiler, Luciane Ferreira
Farenzena, Marcelo
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Giaquinto, Cláudia Daniela Melo
Trierweiler, Jorge Otávio
Teixeira, Herbert Campos Gonçalves
Trierweiler, Luciane Ferreira
Farenzena, Marcelo
dc.subject.por.fl_str_mv Indicadores de desempenho
Processos industriais
Gráficos
topic Indicadores de desempenho
Processos industriais
Gráficos
Key performance indicators
Candlestick chart
Process assessment
dc.subject.eng.fl_str_mv Key performance indicators
Candlestick chart
Process assessment
description Operational KPIs play an extremely important role in the process industry, aiding in decision making. However, they need to be reliably calculated to be representative. The present work presents a schematic methodology for the calculation of these KPIs, including techniques of steady-state detection, denoising, error propagation and sensitivity analysis, presented, as far as it is known, in the form of a new graphical tool proposed by the authors named StatSSCandlePlot. The methodology was applied in a real case study of a gas fired boiler in which the indicator studied was its efficiency evaluated by the Stack Loss Method. From the StatSSCandlePlot it was possible to identify the trends of the indicator, the portion of each window in the steady-state, the values to be considered from the indicator and, in a complementary way, to identify the variable that most influences the variation of the indicator, through the sensitivity analysis.
publishDate 2019
dc.date.issued.fl_str_mv 2019
dc.date.accessioned.fl_str_mv 2020-10-22T04:06:39Z
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/other
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10183/214313
dc.identifier.issn.pt_BR.fl_str_mv 0104-6632
dc.identifier.nrb.pt_BR.fl_str_mv 001118095
identifier_str_mv 0104-6632
001118095
url http://hdl.handle.net/10183/214313
dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartof.pt_BR.fl_str_mv Brazilian journal of chemical engineering [recurso eletrônico]. São Paulo. Vol. 36, no. 1 (Jan./Mar. 2019), p. 393-408
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFRGS
instname:Universidade Federal do Rio Grande do Sul (UFRGS)
instacron:UFRGS
instname_str Universidade Federal do Rio Grande do Sul (UFRGS)
instacron_str UFRGS
institution UFRGS
reponame_str Repositório Institucional da UFRGS
collection Repositório Institucional da UFRGS
bitstream.url.fl_str_mv http://www.lume.ufrgs.br/bitstream/10183/214313/2/001118095.pdf.txt
http://www.lume.ufrgs.br/bitstream/10183/214313/1/001118095.pdf
bitstream.checksum.fl_str_mv 2ef5d10ada917071e5c39d5a676f50b9
f50ed86b5ad5a96dbc3ccc11ddc43db7
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
repository.name.fl_str_mv Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)
repository.mail.fl_str_mv
_version_ 1801224999981285376