Análise multivariada dos indicadores da indústria de transformação e perspectivas da indústria 4.0 no Brasil

• Ano de defesa: 2021
• Autor(a) principal: Nunes, Tamires Fernanda Barbosa
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Engenharia de Produção; UFSM; Programa de Pós-Graduação em Engenharia de Produção; Centro de Tecnologia
• Palavras-chave em Português: 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
• Link de acesso: http://repositorio.ufsm.br/handle/1/22074

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.