Análise das taxas de mortalidade por acidente de trabalho na região sul do Brasil
Ano de defesa: | 2019 |
---|---|
Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | , |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal de Santa Maria
Centro de Tecnologia |
Programa de Pós-Graduação: |
Programa de Pós-Graduação em Engenharia de Produção
|
Departamento: |
Engenharia de Produção
|
País: |
Brasil
|
Palavras-chave em Português: | |
Palavras-chave em Inglês: | |
Área do conhecimento CNPq: | |
Link de acesso: | http://repositorio.ufsm.br/handle/1/20636 |
Resumo: | Fatal occupational accident rates are explored in order to measure workers' exposure to the risks inherent to the economic activity, making it possible to monitor the oscillations and the historical trend of work-related fatal accidents, as well as the impacts on organizations and society. Considering the relevance of the topic, this study intends to use the ARIMA and ��ARMA methodologies to model the series of data of fatal work accident rates, to compare the adjusted prediction models and to identify the best predictive model by state of the southern region of Brazil (Paraná (PR), Santa Catarina (SC) e Rio Grande do Sul (RS)). The labor-related fatality rates were obtained by the Department of Information Technology of SUS (DATASUS), by means of deaths recorded in the Mortality Information System (SIM), stratifying them by state of the southern region of Brazil. With this information a descriptive analysis was carried out, showing the vulnerability characteristics of the victims, comparing them among the three states. Also, three time series were modeled using the Box-Jenkins or ARIMA and ��ARMA methodologies, for the monthly period from 2000 to 2016. Finally, it was evident that there was an increase in female participation in the labor market, but the number of deaths from occupational accidents did not increase in the same proportion. The state of Paraná stood out having the highest mortality rate due to work accidents. A better performance in the adjustment of the ��ARMA model was observed in the 6-month time horizon using the MAE, MAPE and RMSE accuracy measurements, the residue analysis and the AIC and BIC penalty criteria to evaluate the quality of the models and select the most accurate forecast model |
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Biblioteca Digital de Teses e Dissertações do UFSM |
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2021-04-20T11:06:38Z2021-04-20T11:06:38Z2019-02-21http://repositorio.ufsm.br/handle/1/20636Fatal occupational accident rates are explored in order to measure workers' exposure to the risks inherent to the economic activity, making it possible to monitor the oscillations and the historical trend of work-related fatal accidents, as well as the impacts on organizations and society. Considering the relevance of the topic, this study intends to use the ARIMA and ��ARMA methodologies to model the series of data of fatal work accident rates, to compare the adjusted prediction models and to identify the best predictive model by state of the southern region of Brazil (Paraná (PR), Santa Catarina (SC) e Rio Grande do Sul (RS)). The labor-related fatality rates were obtained by the Department of Information Technology of SUS (DATASUS), by means of deaths recorded in the Mortality Information System (SIM), stratifying them by state of the southern region of Brazil. With this information a descriptive analysis was carried out, showing the vulnerability characteristics of the victims, comparing them among the three states. Also, three time series were modeled using the Box-Jenkins or ARIMA and ��ARMA methodologies, for the monthly period from 2000 to 2016. Finally, it was evident that there was an increase in female participation in the labor market, but the number of deaths from occupational accidents did not increase in the same proportion. The state of Paraná stood out having the highest mortality rate due to work accidents. A better performance in the adjustment of the ��ARMA model was observed in the 6-month time horizon using the MAE, MAPE and RMSE accuracy measurements, the residue analysis and the AIC and BIC penalty criteria to evaluate the quality of the models and select the most accurate forecast modelAs taxas de acidentes de trabalho fatais são exploradas a fim de mensurar a exposição dos operários aos riscos inerentes à atividade econômica, possibilitando acompanhar as oscilações e a tendência histórica dos acidentes fatais relacionados ao trabalho, bem como os impactos nas organizações e na sociedade. Considerando a relevância do tema, este estudo tem o propósito de utilizar a metodologia ARIMA e ARMA para modelar as séries de dados referentes às taxas de acidentes fatais relacionados ao trabalho, comparar os modelos de previsão ajustados e identificar o melhor modelo preditivo por estado da região Sul do Brasil (Paraná (PR), Santa Catarina (SC) e Rio Grande do Sul (RS)). As taxas dos acidentes fatais relacionados ao trabalho foram obtidas do Departamento de Informática do SUS (DATASUS), por meio dos óbitos registrados no Sistema de Informação sobre Mortalidade (SIM), estratificando-os por estado da região Sul do Brasil. De posse dessas informações foi realizada uma análise descritiva demonstrando as características de vulnerabilidade das vítimas, comparando-as entre os três estados. Ainda, foram modeladas três séries temporais utilizando as metodologias Box-Jenkins ou ARIMA e ARMA, considerando observações mensais no período de 2000 a 2016. Por fim, ficou evidente que houve um aumento da participação feminina no mercado de trabalho, mas o número de mortes por acidentes ocupacionais não aumentou na mesma proporção. Enquanto que, o estado do Paraná destacou-se por possuir o maior índice de mortalidade por acidente de trabalho. Observou-se um melhor desempenho no ajuste do modelo ARMA, no horizonte de tempo de 6 meses, utilizando as medidas de acurácia MAE, MAPE e RMSE, a análise dos resíduos e os critérios penalizadores AIC e BIC para avaliar a qualidade dos modelos e selecionar o modelo de previsão mais acurado.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESporUniversidade Federal de Santa MariaCentro de TecnologiaPrograma de Pós-Graduação em Engenharia de ProduçãoUFSMBrasilEngenharia de ProduçãoAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessTaxa de mortalidadeAcidente de trabalhoARIMAPrevisãoSéries temporaisβARMAMortality rateWork accidentBeta distributionPredictionTime seriesCNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAOAnálise das taxas de mortalidade por acidente de trabalho na região sul do BrasilAnalysis of mortality rates per work accidents in the southern region of Brazilinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisZanini, Roselaine Ruviarohttp://lattes.cnpq.br/4332331006565656Flôres, Maria Lucia PozzattiXXXXXXXXXXXXXXXSilva, Wesley Vieira daXXXXXXXXXXXXXXhttp://lattes.cnpq.br/5177489789995732Melchior, Cristiane300800000005600b5af5cd4-250e-4e42-8491-f0c3fd2656f56d3ed887-a4b5-483d-8517-238d5d623364e3b09512-6fde-4306-89ac-be7b677528f461b32d3e-38a3-4dda-a690-3389f012994freponame:Biblioteca Digital de Teses e Dissertações do UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMORIGINALDIS_PPGEP_2019_MELCHIOR_CRISTIANE.pdfDIS_PPGEP_2019_MELCHIOR_CRISTIANE.pdfDissertação de Mestradoapplication/pdf5539718http://repositorio.ufsm.br/bitstream/1/20636/1/DIS_PPGEP_2019_MELCHIOR_CRISTIANE.pdf729a0a433e00f7b2ff5a10c60efe6927MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; 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dc.title.por.fl_str_mv |
Análise das taxas de mortalidade por acidente de trabalho na região sul do Brasil |
dc.title.alternative.eng.fl_str_mv |
Analysis of mortality rates per work accidents in the southern region of Brazil |
title |
Análise das taxas de mortalidade por acidente de trabalho na região sul do Brasil |
spellingShingle |
Análise das taxas de mortalidade por acidente de trabalho na região sul do Brasil Melchior, Cristiane Taxa de mortalidade Acidente de trabalho ARIMA Previsão Séries temporais βARMA Mortality rate Work accident Beta distribution Prediction Time series CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO |
title_short |
Análise das taxas de mortalidade por acidente de trabalho na região sul do Brasil |
title_full |
Análise das taxas de mortalidade por acidente de trabalho na região sul do Brasil |
title_fullStr |
Análise das taxas de mortalidade por acidente de trabalho na região sul do Brasil |
title_full_unstemmed |
Análise das taxas de mortalidade por acidente de trabalho na região sul do Brasil |
title_sort |
Análise das taxas de mortalidade por acidente de trabalho na região sul do Brasil |
author |
Melchior, Cristiane |
author_facet |
Melchior, Cristiane |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Zanini, Roselaine Ruviaro |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/4332331006565656 |
dc.contributor.referee1.fl_str_mv |
Flôres, Maria Lucia Pozzatti |
dc.contributor.referee1Lattes.fl_str_mv |
XXXXXXXXXXXXXXX |
dc.contributor.referee2.fl_str_mv |
Silva, Wesley Vieira da |
dc.contributor.referee2Lattes.fl_str_mv |
XXXXXXXXXXXXXX |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/5177489789995732 |
dc.contributor.author.fl_str_mv |
Melchior, Cristiane |
contributor_str_mv |
Zanini, Roselaine Ruviaro Flôres, Maria Lucia Pozzatti Silva, Wesley Vieira da |
dc.subject.por.fl_str_mv |
Taxa de mortalidade Acidente de trabalho ARIMA Previsão Séries temporais βARMA |
topic |
Taxa de mortalidade Acidente de trabalho ARIMA Previsão Séries temporais βARMA Mortality rate Work accident Beta distribution Prediction Time series CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO |
dc.subject.eng.fl_str_mv |
Mortality rate Work accident Beta distribution Prediction Time series |
dc.subject.cnpq.fl_str_mv |
CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO |
description |
Fatal occupational accident rates are explored in order to measure workers' exposure to the risks inherent to the economic activity, making it possible to monitor the oscillations and the historical trend of work-related fatal accidents, as well as the impacts on organizations and society. Considering the relevance of the topic, this study intends to use the ARIMA and ��ARMA methodologies to model the series of data of fatal work accident rates, to compare the adjusted prediction models and to identify the best predictive model by state of the southern region of Brazil (Paraná (PR), Santa Catarina (SC) e Rio Grande do Sul (RS)). The labor-related fatality rates were obtained by the Department of Information Technology of SUS (DATASUS), by means of deaths recorded in the Mortality Information System (SIM), stratifying them by state of the southern region of Brazil. With this information a descriptive analysis was carried out, showing the vulnerability characteristics of the victims, comparing them among the three states. Also, three time series were modeled using the Box-Jenkins or ARIMA and ��ARMA methodologies, for the monthly period from 2000 to 2016. Finally, it was evident that there was an increase in female participation in the labor market, but the number of deaths from occupational accidents did not increase in the same proportion. The state of Paraná stood out having the highest mortality rate due to work accidents. A better performance in the adjustment of the ��ARMA model was observed in the 6-month time horizon using the MAE, MAPE and RMSE accuracy measurements, the residue analysis and the AIC and BIC penalty criteria to evaluate the quality of the models and select the most accurate forecast model |
publishDate |
2019 |
dc.date.issued.fl_str_mv |
2019-02-21 |
dc.date.accessioned.fl_str_mv |
2021-04-20T11:06:38Z |
dc.date.available.fl_str_mv |
2021-04-20T11:06:38Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://repositorio.ufsm.br/handle/1/20636 |
url |
http://repositorio.ufsm.br/handle/1/20636 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.cnpq.fl_str_mv |
300800000005 |
dc.relation.confidence.fl_str_mv |
600 |
dc.relation.authority.fl_str_mv |
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dc.rights.driver.fl_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Centro de Tecnologia |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Engenharia de Produção |
dc.publisher.initials.fl_str_mv |
UFSM |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Engenharia de Produção |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Centro de Tecnologia |
dc.source.none.fl_str_mv |
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UFSM |
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UFSM |
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Biblioteca Digital de Teses e Dissertações do UFSM |
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