Bayesian Hierarchical Risk Assessment in Senegalese Process-Control Systems

This Data Descriptor focuses on evaluating process-control systems in Senegal, a country with significant metallurgical industries. A Bayesian hierarchical model was developed and implemented using data from various locations across Senegal. The model accounts for spatial and temporal variability, integrating expert knowledge through hyperpriors. The analysis revealed that the application of this model significantly reduced the overall risk by 15% in the studied sites, indicating a clear potential for improved safety and efficiency. The Bayesian hierarchical model provided valuable insights into risk reduction strategies for process-control systems in Senegal. Further studies should validate these findings through controlled experiments to ensure reliability and applicability across different contexts. The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.