Big data analytics como ferramenta de adaptação do total quality management na industria 4.0, aplicado a uma empresa multinacional do ramo automobilístico

• Ano de defesa: 2020
• Autor(a) principal: Souza, Fabiane Florencio de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Tecnológica Federal do Paraná; Ponta Grossa; Brasil; Programa de Pós-Graduação em Engenharia de Produção; UTFPR
• Palavras-chave em Português: Gestão da qualidade total; Indústria automobilística; Automação; Plataforma aberta da Web; Big Data; Total quality management; Automobile industry and trade; Automation; Open Web Platform; CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO; Engenharia/Tecnologia/Gestão
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/24085

Total Quality Management represents a management strategy that aims to develop quality awareness in all organizational processes. For that, quality indicators are defined and monitored, so that action plans are developed, aligning all sectors to the same objective. These indicators are fed by a large number of data, coming from the technologies that Industry 4.0 brought with it in this new industrial phase. By gathering all this data from various technologies, there is what is conceptualized as a problem of Big Data, which needs Big Data Analysis able to analyze and promote the visualization of this data in a simple way so that decision-makers can work with them. This situation highlights the need for an adaptation as to the ways of monitoring quality within the industrial context, therefore, this research aims to adapt the management and monitoring of quality indicators of production defects, to the technological changes arising from I4.0 thus developing a greater involvement between quality and technology. For this, a Systematic Literature Review was carried out, using the Methodi Ordinatio methodology, resulting in a portfolio of articles with scientific relevance, which will be the source of data collections for content analysis. Also, field research was carried out at a multinational company in the automotive industry so that the problem can be evaluated and the methodology developed for building an online platform. The combination of these research strategies resulted in the e-TQM online platform for monitoring Total Quality Management, automating the process of obtaining, analyzing, and making available defects in production indicators, adding knowledge about the techniques and technologies for analysis of large amounts of data, in addition to highlighting the relationship between Industry 4.0, Total Quality Management and Big Data Analytics.