The reliability of industrial machinery in South African fleets is crucial for maintaining productivity and safety in various sectors such as mining, manufacturing, and construction. A Bayesian hierarchical model was applied to analyse data on industrial machinery failures and operational conditions in South African fleets. The model accounts for both systematic differences between fleet types and random variations within each fleet type. The analysis revealed a significant proportion (45%) of machinery failures were attributed to maintenance lapses, indicating the need for improved preventive maintenance practices. The Bayesian hierarchical model provided insights into the reliability characteristics of industrial machinery systems in South African fleets, identifying critical areas for system improvement. Implementing targeted training programmes and enhanced monitoring protocols can significantly reduce machinery failures and improve overall fleet performance. Bayesian Hierarchical Model, Industrial Machinery Reliability, South Africa, Maintenance Practices The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Mkhwanazi et al. (Thu,) studied this question.
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