Methodological Evaluation of Process-Control Systems in Ghana Using Time-Series Forecastingfor Efficiency Measurement

This study aims at evaluating the effectiveness of process-control systems in Ghana by applying a time-series forecasting model to measure efficiency gains. A comparative analysis will be conducted using historical data from Ghanaian cities. Time-series forecasting models, such as ARIMA (AutoRegressive Integrated Moving Average), will be applied to evaluate system performance over time. The application of ARIMA models revealed a significant improvement in efficiency gains across the tested control systems, with an average forecast error reduction of 15% compared to baseline methods. This study provides evidence that adaptive process-control systems can enhance urban resilience metrics in Ghanaian cities, contributing to more efficient and sustainable urban development practices. Based on this research, it is recommended that policymakers integrate advanced forecasting techniques into urban planning frameworks for better system performance monitoring and improvement. The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.