Time-Series Forecasting Model Evaluation for Cost-Effectiveness in South African Manufacturing Plants Systems,

This study focuses on evaluating manufacturing plants systems in South Africa to assess cost-effectiveness over a specific period. A time-series analysis was conducted using an ARIMA (AutoRegressive Integrated Moving Average) model. The dataset comprised quarterly financial reports of manufacturing plants from -, focusing on energy consumption, labour costs, and production output. The ARIMA(1,1,1) model demonstrated a strong fit with an R² value of 0.85 and a standard error of the estimate (SEE) of ±$345 per quarter, indicating significant predictive power in cost-effectiveness measurement. The time-series forecasting model provided valuable insights into cost control mechanisms within South African manufacturing plants, highlighting areas for improvement in resource management. Manufacturing companies should consider implementing the ARIMA model to forecast costs and enhance operational efficiencies. Policy-makers could use this method to evaluate and suggest improvements to industrial systems. manufacturing efficiency, time-series analysis, cost-effectiveness, South Africa The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.