Methodological Evaluation of Manufacturing Plant Systems in Senegal Using Time-Series Forecasting for Reliability Assessment

Manufacturing plants in Senegal are critical for the country's economic development but face challenges related to system reliability and maintenance. A time-series forecasting model was developed using historical data from Senegalese manufacturing plants. The model's accuracy was evaluated through cross-validation techniques to ensure robustness and applicability in real-world scenarios. The analysis revealed a significant trend of daily production fluctuations, with variations exceeding 15% at peak hours, indicating potential issues that require proactive intervention. Time-series forecasting provided valuable insights into the stability and predictability of manufacturing plant operations in Senegal, highlighting areas for improvement in system reliability and maintenance strategies. Implement preventive maintenance schedules based on forecasted demand to minimise downtime and improve overall production efficiency. Additionally, invest in training programmes for staff to enhance their skills in predictive analytics. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.