Time-Series Forecasting Model Evaluation for System Reliability in Ghanaian Manufacturing Plants

Manufacturing plants in Ghana face challenges related to system reliability, which can impact productivity and efficiency. A comprehensive evaluation of manufacturing systems was conducted using a time-series forecasting model. The study aimed at identifying patterns and predicting future trends to enhance system reliability. The analysis revealed that the time-series model could accurately forecast system failures with an accuracy rate of 85% (95% confidence interval). This research highlights the effectiveness of the proposed forecasting model in enhancing system reliability, providing a robust tool for industry practitioners. Manufacturing plants should leverage this methodological approach to improve their systems and ensure higher operational efficiency. manufacturing systems, time-series forecasting, system reliability, Ghana The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.