Detalhes bibliográficos
| Ano de defesa: |
2021 |
| Autor(a) principal: |
Pavezzi, Camila Cumani
 |
| Orientador(a): |
Soares, Júlio Cesar Valandro
|
| Banca de defesa: |
Soares, Júlio Cesar Valandro,
Guimarães, Núbia Rosa da Silva,
Galo, Nadya Regina |
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal de Goiás
|
| Programa de Pós-Graduação: |
Programa de Pós-graduação em Engenharia de Produção (FCT)
|
| Departamento: |
Faculdade de Ciências e Tecnologia - FCT (RG)
|
| País: |
Brasil
|
| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
http://repositorio.bc.ufg.br/tede/handle/tede/11724
|
Resumo: |
Statistical tools are fundamental to reduce waste caused by non-quality in several processes, through the reduction of their variability, highlighting the statistical process control and the six sigma method, which are focused on fast monitoring. Both bring the concepts of control charts, process capability assessment and root cause analysis as drivers of optimization in various sectors, however, according to the bibliometric research carried out, there are still few studies involving such methods combined. In this sense the study brings the relevance of this theme through an application in the food industry, more specifically in the manufacturing of tomato sauces, aiming to study the variability of the formulation parameter °brix, based on the development of a customized model to the process under study that brings greater predictability to the process. To conduct the research, data from a continuous process were collected, control charts and histograms were elaborated, and the process sigma level was analyzed. Statements were also collected from the main actors in the process to evaluate the causes of variability. It was observed that initially, the process was centralized, but with variability outside the control limits, being verified a 4.15 sigma level for the process, generating 0.4% of products outside the design specifications. After the optimization proposals, the process became more centered in its limits, with a 9% reduction in the standard deviation value and a 48% reduction in the number of defects generated, verifying the variability reduction. The entire study was based on the development of a customized model for the process, considering its particularities, with a step-by-step guide on how to apply the combined methods in the organization. Finally, the research demonstrated the relevance and applicability of the SPC and six sigma methods in the scientific field, as a reference for similar studies in this area of knowledge. |
