The reliability assessment of manufacturing systems in Nigerian plants is crucial for improving productivity and safety. A Bayesian hierarchical model was developed to analyse data from multiple agricultural manufacturing sites. The model incorporates uncertainty through credible intervals around estimated parameters. The analysis revealed significant variation in system reliability between the plants, with some showing a 20% lower mean uptime compared to others. Bayesian hierarchical models effectively captured the variability of manufacturing systems across different locations, providing insights for improvement and risk management strategies. Implementing targeted interventions based on model findings could lead to improved system performance in Nigerian agriculture. The empirical specification follows Y=₀+^ X+, and inference is reported with uncertainty-aware statistical criteria.
Oguntola et al. (Sat,) studied this question.