Análise multivariada dos indicadores da indústria de transformação e perspectivas da indústria 4.0 no Brasil
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Manancial - Repositório Digital da UFSM |
Texto Completo: | http://repositorio.ufsm.br/handle/1/22074 |
Resumo: | Currently the Fourth Industrial Revolution has promoted a complex, uncertain and rapidly changing technological environment. The concept of Industry 4.0 has spread around the world as a new innovation strategy oriented to reinvention of manufacturing industry, increasing global competitiveness by quality, costs and flexible processes. The industrial sector is responsible for stimulating the economic and competitive development of the country. In Brazil, even with all the potential to generate wealth, the manufacturing industry has been hampered by deindustrialization and structural problems that affect its income significantly. Therefore, the objective of the present study was to analyze the industrial indicators of manufacturing, made available by the National Confederation of Industry (CNI), in order to understand which have the greatest influence for the formation of the Gross Domestic Product (GDP) of the sector. The multivariate techniques Principal Component Analysis and Cluster Analysis were used to select variables to construct the Multiple Linear Regression model, developed to analyze the association of industrial indicators with the GDP of the sector. In addition, a Systematic Literature Review (RSL) was conducted to identify potential impacts and challenges of Industry 4.0 for manufacturing. The results of the multivariate analyses demonstrated that employability and productivity are the factors with the greatest contribution to the formation of manufacturing GDP, is consistent with the reality of the sector in which the reduction of the industry's participation in the generation of employment and the added value corroborate the process of deindustrialization. From the RSL seven potential impacts of Industry 4.0 on manufacturing were identified (i) environmental; (ii) competitive; (iii) economic; (iv) education; (v) labor market; (vi) business models; and (vii) social. And six potential challenges for manufacturing to embrace digital transformation: (i) management; (ii) government; (iii) implementation; (iv) manpower; (v) operation; and (vi)security. The results indicate the need to promote competitive industrial recovery strategies outlined by high technology and innovation, as well as the development of broad and effective industrial and technological policies. Just as the demand for knowledge generation and sharing of the concepts and scope of Industry 4.0 have been evident to shape the future of the manufacturing sector. |
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Análise multivariada dos indicadores da indústria de transformação e perspectivas da indústria 4.0 no BrasilMultivariate analysis of industry indicators and industry 4.0 perspectives in BrazilIndústria de transformaçãoIndústria 4.0Análise multivariadaRevisão sistemática da literaturaManufacturing industryIndustry 4.0Multivariate analysisSystematic literature reviewCNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAOCurrently the Fourth Industrial Revolution has promoted a complex, uncertain and rapidly changing technological environment. The concept of Industry 4.0 has spread around the world as a new innovation strategy oriented to reinvention of manufacturing industry, increasing global competitiveness by quality, costs and flexible processes. The industrial sector is responsible for stimulating the economic and competitive development of the country. In Brazil, even with all the potential to generate wealth, the manufacturing industry has been hampered by deindustrialization and structural problems that affect its income significantly. Therefore, the objective of the present study was to analyze the industrial indicators of manufacturing, made available by the National Confederation of Industry (CNI), in order to understand which have the greatest influence for the formation of the Gross Domestic Product (GDP) of the sector. The multivariate techniques Principal Component Analysis and Cluster Analysis were used to select variables to construct the Multiple Linear Regression model, developed to analyze the association of industrial indicators with the GDP of the sector. In addition, a Systematic Literature Review (RSL) was conducted to identify potential impacts and challenges of Industry 4.0 for manufacturing. The results of the multivariate analyses demonstrated that employability and productivity are the factors with the greatest contribution to the formation of manufacturing GDP, is consistent with the reality of the sector in which the reduction of the industry's participation in the generation of employment and the added value corroborate the process of deindustrialization. From the RSL seven potential impacts of Industry 4.0 on manufacturing were identified (i) environmental; (ii) competitive; (iii) economic; (iv) education; (v) labor market; (vi) business models; and (vii) social. And six potential challenges for manufacturing to embrace digital transformation: (i) management; (ii) government; (iii) implementation; (iv) manpower; (v) operation; and (vi)security. The results indicate the need to promote competitive industrial recovery strategies outlined by high technology and innovation, as well as the development of broad and effective industrial and technological policies. Just as the demand for knowledge generation and sharing of the concepts and scope of Industry 4.0 have been evident to shape the future of the manufacturing sector.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESAtualmente a Quarta Revolução Industrial tem promovido um ambiente tecnológico complexo, incerto e de mudanças rápidas. O conceito da Indústria 4.0 tem se espalhado pelo mundo como uma nova estratégia de inovação orientada a reinvenção da indústria manufatureira, aumentando a competitividade global por qualidade, custos e processos flexíveis. O setor industrial é responsável por estimular o desenvolvimento econômico e competitivo do país. No Brasil, mesmo com todo potencial para geração de riquezas a indústria de transformação vem sendo prejudicada pela desindustrialização e por problemas estruturais que afetam seu rendimento significativamente. Diante disso, o objetivo do presente trabalho foi analisar os indicadores industriais da manufatura, disponibilizados pela Confederação Nacional da Indústria (CNI), visando compreender quais exercem maior influência para formação do Produto Interno Bruto (PIB) do setor. As técnicas multivariadas Análise de Componentes Principais e Análise de Agrupamento foram utilizadas para selecionar variáveis para construção do modelo de Regressão Linear Múltipla, desenvolvido para analisar a associação dos indicadores industriais com o PIB do setor. Além disso uma Revisão Sistemática da Literatura (RSL) foi realizada para identificar potenciais impactos e desafios da Indústria 4.0 para manufatura. Os resultados das análises multivariadas demonstraram que a empregabilidade e a produtividade são os fatores com maior contribuição para formação do PIB da manufatura, se mostrando coerente com a realidade do setor na qual a redução da participação da indústria na geração de emprego e no valor adicionado corroboram para o processo de desindustrialização. A partir da RSL sete potenciais impactos da Indústria 4.0 na manufatura foram identificados (i) ambiental; (ii) competitivo; (iii) econômico; (iv) ensino; (v) mercado de trabalho; (vi) modelos de negócios; e (vii) social. E seis potenciais desafios enfrentados pela manufatura para adoção da transformação digital: (i) gestão; (ii) governo; (iii) implementação; (iv) mão de obra; (v) operação; e (vi) segurança. Os resultados indicam a necessidade de promover estratégias competitivas de recuperação industrial delineadas por alta tecnologia e inovação, assim como o desenvolvimento de políticas industriais e tecnológicas amplas e efetivas. Assim, como deixaram evidente a demanda por geração de conhecimento e compartilhamento dos conceitos e abrangência da Indústria 4.0 para moldar o futuro do setor manufatureiro.Universidade Federal de Santa MariaBrasilEngenharia de ProduçãoUFSMPrograma de Pós-Graduação em Engenharia de ProduçãoCentro de TecnologiaZanini, Roselaine Ruviarohttp://lattes.cnpq.br/4332331006565656Coronel, Daniel ArrudaRosa, Ariane Ferreira PortoNunes, Tamires Fernanda Barbosa2021-08-26T17:38:03Z2021-08-26T17:38:03Z2021-03-29info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://repositorio.ufsm.br/handle/1/22074porAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessreponame:Manancial - Repositório Digital da UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSM2021-08-27T06:01:58Zoai:repositorio.ufsm.br:1/22074Biblioteca Digital de Teses e Dissertaçõeshttps://repositorio.ufsm.br/ONGhttps://repositorio.ufsm.br/oai/requestatendimento.sib@ufsm.br||tedebc@gmail.comopendoar:2021-08-27T06:01:58Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM)false |
dc.title.none.fl_str_mv |
Análise multivariada dos indicadores da indústria de transformação e perspectivas da indústria 4.0 no Brasil Multivariate analysis of industry indicators and industry 4.0 perspectives in Brazil |
title |
Análise multivariada dos indicadores da indústria de transformação e perspectivas da indústria 4.0 no Brasil |
spellingShingle |
Análise multivariada dos indicadores da indústria de transformação e perspectivas da indústria 4.0 no Brasil Nunes, Tamires Fernanda Barbosa Indústria de transformação Indústria 4.0 Análise multivariada Revisão sistemática da literatura Manufacturing industry Industry 4.0 Multivariate analysis Systematic literature review CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO |
title_short |
Análise multivariada dos indicadores da indústria de transformação e perspectivas da indústria 4.0 no Brasil |
title_full |
Análise multivariada dos indicadores da indústria de transformação e perspectivas da indústria 4.0 no Brasil |
title_fullStr |
Análise multivariada dos indicadores da indústria de transformação e perspectivas da indústria 4.0 no Brasil |
title_full_unstemmed |
Análise multivariada dos indicadores da indústria de transformação e perspectivas da indústria 4.0 no Brasil |
title_sort |
Análise multivariada dos indicadores da indústria de transformação e perspectivas da indústria 4.0 no Brasil |
author |
Nunes, Tamires Fernanda Barbosa |
author_facet |
Nunes, Tamires Fernanda Barbosa |
author_role |
author |
dc.contributor.none.fl_str_mv |
Zanini, Roselaine Ruviaro http://lattes.cnpq.br/4332331006565656 Coronel, Daniel Arruda Rosa, Ariane Ferreira Porto |
dc.contributor.author.fl_str_mv |
Nunes, Tamires Fernanda Barbosa |
dc.subject.por.fl_str_mv |
Indústria de transformação Indústria 4.0 Análise multivariada Revisão sistemática da literatura Manufacturing industry Industry 4.0 Multivariate analysis Systematic literature review CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO |
topic |
Indústria de transformação Indústria 4.0 Análise multivariada Revisão sistemática da literatura Manufacturing industry Industry 4.0 Multivariate analysis Systematic literature review CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO |
description |
Currently the Fourth Industrial Revolution has promoted a complex, uncertain and rapidly changing technological environment. The concept of Industry 4.0 has spread around the world as a new innovation strategy oriented to reinvention of manufacturing industry, increasing global competitiveness by quality, costs and flexible processes. The industrial sector is responsible for stimulating the economic and competitive development of the country. In Brazil, even with all the potential to generate wealth, the manufacturing industry has been hampered by deindustrialization and structural problems that affect its income significantly. Therefore, the objective of the present study was to analyze the industrial indicators of manufacturing, made available by the National Confederation of Industry (CNI), in order to understand which have the greatest influence for the formation of the Gross Domestic Product (GDP) of the sector. The multivariate techniques Principal Component Analysis and Cluster Analysis were used to select variables to construct the Multiple Linear Regression model, developed to analyze the association of industrial indicators with the GDP of the sector. In addition, a Systematic Literature Review (RSL) was conducted to identify potential impacts and challenges of Industry 4.0 for manufacturing. The results of the multivariate analyses demonstrated that employability and productivity are the factors with the greatest contribution to the formation of manufacturing GDP, is consistent with the reality of the sector in which the reduction of the industry's participation in the generation of employment and the added value corroborate the process of deindustrialization. From the RSL seven potential impacts of Industry 4.0 on manufacturing were identified (i) environmental; (ii) competitive; (iii) economic; (iv) education; (v) labor market; (vi) business models; and (vii) social. And six potential challenges for manufacturing to embrace digital transformation: (i) management; (ii) government; (iii) implementation; (iv) manpower; (v) operation; and (vi)security. The results indicate the need to promote competitive industrial recovery strategies outlined by high technology and innovation, as well as the development of broad and effective industrial and technological policies. Just as the demand for knowledge generation and sharing of the concepts and scope of Industry 4.0 have been evident to shape the future of the manufacturing sector. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-08-26T17:38:03Z 2021-08-26T17:38:03Z 2021-03-29 |
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/1/22074 |
url |
http://repositorio.ufsm.br/handle/1/22074 |
dc.language.iso.fl_str_mv |
por |
language |
por |
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.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Brasil Engenharia de Produção UFSM Programa de Pós-Graduação em Engenharia de Produção Centro de Tecnologia |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Brasil Engenharia de Produção UFSM Programa de Pós-Graduação em Engenharia de Produção Centro de Tecnologia |
dc.source.none.fl_str_mv |
reponame:Manancial - Repositório Digital da UFSM instname:Universidade Federal de Santa Maria (UFSM) instacron:UFSM |
instname_str |
Universidade Federal de Santa Maria (UFSM) |
instacron_str |
UFSM |
institution |
UFSM |
reponame_str |
Manancial - Repositório Digital da UFSM |
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Manancial - Repositório Digital da UFSM |
repository.name.fl_str_mv |
Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM) |
repository.mail.fl_str_mv |
atendimento.sib@ufsm.br||tedebc@gmail.com |
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1805922069503803392 |