aspg-21-3130-1791475512 20261008160512 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group International Journal of Neutrosophic Science IJNS 2692-6148 2690-6805 2025 25 2 Mohammed A. Alshahrani Department of Mathematics, College of Sciences and Humanities, Prince Sattam Bin Abdulaziz University, Alkharj 11942, Saudi Arabia Imad Khan Department of Statistics, Abdul Wali Khan University Mardan, Mardan, 23200, Pakistan Wojciech Sumelka Institute of Structural Analysis, Poznan University of Technology, Poznan, Poland Quality control (QC) charts are essential for ensuring industry process stability, but imprecise data make traditional methods unuseful in such a case. Neutrosophic control charts are available to handle the imprecise data. This article learns fuzzy logic as an approach of handling uncertainty more suitably than neutrosophic approaches. Fuzzy QC charts make use of fuzzy numbers, membership functions and fuzzy control limits and as such are more realistic compared to conventional charts. The study introduces a Fuzzy Adaptive Exponentially Weighted Moving Average (FAEWMA) chart, specifically designed for univariate data in a fuzzy atmosphere. The FAEWMA chart, incorporating α-cuts, is engineered to detect shifts in process means, showcasing its effectiveness through both theoretical development and practical applications. This approach improves decision-making in process control and represents a significant advancement over traditional QC methods. 2025 141 154 3130 https://creativecommons.org/licenses/by/4.0/ 10.54216/IJNS.250212 https://www.americaspg.com/journal/21/article/3130 https://www.americaspg.com/storage/01737216010.pdf