Summary: | 碩士 === 國立高雄應用科技大學 === 工業工程與管理系 === 100 === Quality characteristic of attribute, which is depended on the quality is good or not, cannot be easily and numerically represently. In the real world, the attribute data may not be recorded or collected precisely on account of visual inspection. A number of nonconformities are counted by inspectors according to their subjective decisions, so that we consider attribute data as fuzzy data. To construct an attribute control chart, the traditional method exists a limitation to deal with the data in a fuzzy environment. In this situation, traditional attribute control charts are not apropriate for monitoring the manufacturing process. However, in this paper, we employ the fuzzy sets theory to construct control charts for monitoring fuzzy data.
We construct a fuzzy u control chart for monitoring the average number of nonconformities per unit in a process in which fuzzy sample data are collected from the manufacturing process. Therefore, we also present a fuzzy ranking method, which compares the fuzzy everage number of nonconformities per unit to its respective fuzzy control chart, to classify the manufacturing process such as observations are out-of-control, in-control, rather-in-control, or rather-out-of-control in a fuzzy u control chart.
Finally, a numerical example illustrates the applicability of the proposed fuzzy u control chart.
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