African Journal of Agricultural Mechanization and Smart Farming (Engineering | 13 August 2007
Time-Series Forecasting Model Evaluation for System Reliability in Ghanaian Manufacturing Plants
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Abstract
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 $Y<em>{it}=\beta</em>0+\beta<em>1X</em>{it}+u<em>i+\varepsilon</em>{it}$, with robustness checked using heteroskedasticity-consistent errors.