Abstract
ABSTRACT The main purpose of this paper is to use fuzzy logic to provide a systematic approach for designing fuzzy control charts and compare the average run length type 2 of these charts in three different modes: Gaussian fuzzy, triangular fuzzy, and crisp cases. The process of solving and presenting the research results is by calculating the fuzzy control chart conditions and fuzzy descriptive capability indices through theoretical calculations and a project-based organizational case study and comparing the average run length type 2, which represents the expected interval between out-of-control events. Average run length type 2 illustrates that Gaussian and triangular quality control charts are able to detect an out-of-control signal more quickly. The main contributions of this paper are to use Gaussian fuzzy numbers in order to provide a systematic approach for designing fuzzy control charts, estimating descriptive capability indices, and analyzing the results of their estimation under fuzzy logic.
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