A competitividade entre as empresas exige que busquem por alternativas não só na garantia por produtos melhores aos clientes, mas também no que se refere ao processo produtivo sem desperdícios e elevados custos. O presente trabalho apresenta a implementação da metodologia Seis Sigma como meio de obtenção de melhores resultados na qualidade do processo produtivo e como uma mudança organizacional para com a resolução de problemas. A pesquisa foi realizada através de um estudo de caso, na qual foram coletados dados e informações pertinentes para a proposição e implantação de melhorias. O modelo DMAIC foi utilizado para a coordenação das etapas, assim como a utilização de ferramentas da qualidade dentro de cada uma das etapas. Destaca-se a obtenção de resultados satisfatórios com relação a eliminação do problema do peso do presunto fora da especificação, a elevação do nível sigma de 1,16 para 3,24, bem como, o conhecimento fornecido a todos os colaboradores do setor sobre a importância de realizar melhorias, ficam como um primeiro passo para a mudança do setor.

Paper aims: This research presents a literature overview in relation to data mining and machine learning applications in the area of occupational health and safety.Originality: A summary of main insights obtained from the analysis of systematic mapping is presented at the end, as well as a roadmap with recommendations for directing future research on the topic.Research method: This article carries out a thorough descriptive research of the scientific literature on the topic through a systematic mapping covering the period between the years 2008 and 2019 and 12 scientific databases, which at the end presents 68 selected records.Main findings: Around 84% of the selected records were of total significance for the research, with the majority of them being classified in the areas of civil construction and steel industry.Implications for theory and practice: Through this study it is possible to understand the way research has been developed on this theme, as well as point to the guidelines for future studies. Other contribution is the indication of studies in OSH 4.0 concept, based on monitoring workers full-time.

Purpose - This article aims to carry out a bibliometric analysis on data mining and occupational health and safety, covering the period between 2008 and 2020, for seven scientific databases and 68 articles. Theoretical framework - This study was theoretically based on concepts that involve data mining, machine learning and occupational health and safety. Design/methodology/approach - The selected articles were submitted to a statistical analysis, together with the evaluation of one of the bibliometric laws (Bradford's Law), comprising a number of citations, journals, authors, countries of origin, publication categories and an evaluation of production over the years. Findings - As a result, it was found that the most influential journal was Safety Science, and Taiwan was the leading country in terms of articles produced, with an average of 115 citations per article. The best-ranked journals related to Engineering and Health, both corresponding to 30% of the selected articles and journals. Originality/value - This study provides some insights into the growth of the data mining area together with occupational health and safety. Keywords - Bibliometrics analysis. Occupational health and safety. Data mining.

No abstract