International Journal of Neutrosophic Science IJNS 2690-6805 2692-6148 10.54216/IJNS https://www.americaspg.com/journals/show/2230 2020 2020 Mathematics Department, College of Humanities and Science in Al Aflaj, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia; Business Administration Department, Administrative Science College, Thamar University, Thamar, Yemen Fuad S. Alduais Department of Mathematics and Statistics, Hazara University Mansehra Pakistan Zahid Khan Department of Mathematics and Statistics, Hazara University Mansehra Pakistan Muhammad Waseem The application of neutrosophic statistics provides a novel approach to dealing with uncertain and imprecise data problems. In this study, we present an improved method called neutrosophic Rayleigh exponential weighted moving average  chart. The  chart is an extension of the traditional  model and can be applied in various fields. The proposed  scheme is designed to enhance the detection capability of the traditional  chart. The key features of the suggested chart are discussed, highlighting its capability to handle vague, indeterminate, and fuzzy data situations. We evaluate the performance of the proposed scheme by analyzing the designated limits and charting parameters for different sample sizes. Moreover, we establish the performance metrics of the  chart such as neutrosophic run length ( ) and neutrosophic power curve ( ).Performance metrics demonstrate that the  chart is highly sensitive to persistent shifts in the scaling parameter of the neutrosophic Rayleigh distribution. Monte Carlo simulations are conducted to compare the suggested scheme with the existing model. A comparative study indicates that the proposed chart outperforms the competing design, particularly in detecting smaller shifts. Finally, we provide a charting structure for the proposed design using daily average wind speed data, which can be used as a practical implementation guideline for real-world applications. 2024 2024 59 72 10.54216/IJNS.230105 https://www.americaspg.com/articleinfo/21/show/2230