Fuzzy Logic Technique Based on Classification Function Application in Quality Control.

This work introduces a method for fuzzy control charts. Fuzzy theory and the foundations of Shew Hart control charts form the foundation of the process. The information was gathered from one of the key production facilities to raise the quality standard for one of Iraq's industrial products. Fuzzy control charts were used to quickly and accurately identify the production specifications and efficiency. This work uses the triangle membership function to generate fuzzy numbers, which are then transformed into quality control charts for the real data obtained using the proposed ranking function. Next, contrast the quality control of crisp and fuzzy attributes. The graphs demonstrate how professional techniques can increase output and lower defect rates. To meet the control limits for quality control and defective percentages for all samples using (w = 0.2, 0.5, 0.6) and (λ = 0.5, 0.7, 0.9), then compare the adoption of the traditional technique with fuzzy logic while adopting variable cases through the arrangement function. It can be noticed that the chart of fuzzy control is more economically quicker and more accurate at monitoring production quality, enabling the diagnosis of defective units throughout the production process. [ABSTRACT FROM AUTHOR]