Computational Intelligence in Decision and Control - 8th International FLINS Conference, Madrid, Spain, 21 - 24 September 2008, pp.957-962
Control charts are very useful tool for monitoring and analyzing the processes. When the quality characteristics cannot be represented in numerical form, like softness, appearance, chapped, damaged, etc., control charts for attributes are used. Especially, the binary classification into conforming and non-conforming of product / parts for implementing the p-control chart includes ambiguity or vague, or lack of available information due to process or human subjectivity. Traditional p-control chart is not a sufficient tool to consider these uncertainties and vagueness of data. In this case, the fuzzy set theory is a very useful methodology for dealing with sources of uncertainty or imprecise conditions. In this study, the methodology for constructing fuzzy p-control chart based on fuzzy median transformation method for both constant and variable sample size (n) is proposed by using a-cuts. Here, a-cuts approach to the fuzzy p̃ -control chart provides the ability of determining the tightness of inspection. Thus, the flexibility of control limits is achieved by incorporating fuzzy set theory and control limits calculations.