Industrial machinery fleets play a crucial role in various sectors of Kenya's economy. The efficient operation of these fleets can significantly impact productivity and cost-effectiveness. A Bayesian hierarchical model will be employed to analyse fleet operation costs and benefits. The model accounts for variability across different sectors and fleet sizes through random effects. The analysis revealed significant cost savings in operations when fleets were optimised, with an average reduction of 15% in maintenance costs compared to standard operating procedures. The Bayesian hierarchical model provided robust estimates of fleet performance, enabling informed decision-making for improved cost-effectiveness and resource allocation. Fleet operators should consider implementing optimization strategies based on the findings to enhance efficiency and reduce operational expenses. The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Naikor et al. (Mon,) studied this question.
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