FUZZY CONTROL CHART FOR MONITORING MEAN AND RANGE OF UNIVARIATE PROCESSES
The control chart introduced by Shewhart is one of the most important quality control techniques used to detect special causes. Real world data are complicated to interpret since they involve a certain level of uncertainty that may be linked to human subjectivity or measurement device limitations. F...
| Autores: | , , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2019 |
| País: | Brasil |
| Recursos: | Universidade Estadual Paulista (UNESP) |
| Repositorio: | Repositório Institucional da UNESP |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.unesp.br:11449/211310 |
| Acesso em linha: | http://dx.doi.org/10.1590/0101-7438.2019.039.02.0339 http://hdl.handle.net/11449/211310 |
| Access Level: | acceso abierto |
| Palavra-chave: | control chart fuzzy average run length (ARL) extra quadratic loss (EQL) |
| Resumo: | The control chart introduced by Shewhart is one of the most important quality control techniques used to detect special causes. Real world data are complicated to interpret since they involve a certain level of uncertainty that may be linked to human subjectivity or measurement device limitations. Fuzzy set theory can deal with such uncertainty and can be applied to traditional control charts. In this work, the values of the quality characteristic are fuzzified by the insertion of uncertainties and transformed into representative values for a better comparison with traditional control charts. The performance of a control chart can be measured by the average run length (ARL) and the extra quadratic loss (EQL). We observed in the present work that the fuzzy control chart has greater efficiency than the traditional control charts. An illustrative example demonstrates the application of the fuzzy control chart for the measurement of the volume contained in milk bags. |
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