Ercan-Teksen H.Anagün, Ahmet Sermet2023-06-162023-06-1620209.78E+122194-5357https://doi.org/10.1007/978-3-030-23756-1_137https://hdl.handle.net/20.500.14365/3363International Conference on Intelligent and Fuzzy Systems, INFUS 2019 -- 23 July 2019 through 25 July 2019 -- 228529Control chart is a quality branch that provides information about the process. Fuzzy logic theory is suitable especially for non-measurable data. Using of fuzzy sets for control charts is reasonable given that the data are subjective for qualitative control charts. For this reason, studies of fuzzy control charts are included in the literature. In the literature, fuzzy control charts are generally generated using ordinary fuzzy sets. There is no study about intuitionistic fuzzy control charts in the literature. However, in a process, especially for qualitative data, if some data are considered as intuitionistic fuzzy numbers, corresponding control charts should be created. First of all, within the purpose of this study, upper control limit and lower control limit will be created for intuitionistic fuzzy c-control charts. The other purpose of this study is to generate fuzzy control charts using the intuitionistic fuzzy comparison methods. © 2020, Springer Nature Switzerland AG.eninfo:eu-repo/semantics/closedAccessFuzzy control chartsIntuitionistic fuzzy comparison methodsIntuitionistic fuzzy setsControl chartsDecision makingFlowchartingFuzzy controlFuzzy logicFuzzy setsGraphic methodsComparison methodsFuzzy logic theoryIntuitionistic fuzzyIntuitionistic Fuzzy numberIntuitionistic fuzzy setsLower control limitQualitative controlUpper control limitQuality controlConference Object10.1007/978-3-030-23756-1_1372-s2.0-85069529590