Manufacturing plants in Nigeria often face challenges related to system reliability due to varying operational conditions and maintenance practices. A comprehensive assessment was conducted using time-series forecasting models such as ARIMA (Autoregressive Integrated Moving Average) to analyse historical data of manufacturing plant operations in Nigeria. The model's effectiveness was evaluated by its ability to predict system reliability over a specified period, considering uncertainties and potential variations in input parameters. The analysis revealed that the ARIMA model accurately predicted system reliability with an R² value of 0. 85 ± 0. 12 for the forecasted data periods, indicating substantial agreement between observed and predicted values. This study demonstrates the utility of time-series forecasting models in enhancing understanding of manufacturing plant systems' reliability within Nigerian environments. The findings suggest that ongoing monitoring and periodic updates to the ARIMA model are necessary for maintaining accuracy in predicting system reliability, especially as operational conditions evolve. manufacturing plants, Nigeria, time-series forecasting, reliability evaluation, ARIMA The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Nworueka et al. (Fri,) studied this question.