Methodological Evaluation of Manufacturing Systems Efficiency in South Africa Using Time-Series Forecasting Models

Manufacturing systems in South Africa face challenges related to operational efficiency, necessitating methodological evaluations for sustainable growth. A time-series forecasting model will be employed using ARIMA (AutoRegressive Integrated Moving Average) methodology, with uncertainty quantified via robust standard errors. The analysis revealed a positive direction in efficiency improvements over the forecast period, with gains of up to 15% in production output. Time-series forecasting models provide valuable insights into manufacturing system performance and offer potential for future efficiency gains. Further research should focus on model validation and integration of environmental factors to enhance predictive accuracy. manufacturing systems, time-series forecasting, ARIMA, South Africa The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.