<p>Control charts are crucial in monitoring and improving process quality in industrial and commercial applications. Traditional control charts often rely on assumptions of normality, which may not hold in real-world scenarios. This study focuses on the statistical-economic design of the sign control chart under the Ranked Set Sampling (RSS) scheme in the presence of multiple independent assignable causes. The RSS method enhances efficiency by reducing measurement costs while improving statistical power compared to Simple Random Sampling (SRS). A novel realistic economic model is introduced, extending previous works to address deficiencies in cost modeling under multiple assignable causes. The study incorporates the Weibull shock model to represent failure occurrences and optimizes control chart parameters to minimize the average production cost per unit of time. A comparative analysis between economic design (RED) and statistical-economic design (RESD) highlights the trade-offs between cost efficiency and detection accuracy. Numerical results indicate that the uniform distribution provides the lowest expected cost (E(A)) while increasing accuracy leads to higher costs. The findings offer valuable insights for selecting optimal control chart designs based on cost constraints and process stability requirements.</p>