Multilevel regression analysis measures cost-efficiency in industrial machinery fleets in Senegal, suggesting investment in predictive maintenance.
Industrial machinery fleets play a crucial role in optimising operations and reducing costs for businesses in Senegal. A multilevel regression model will be employed to analyse data from different levels of the machinery fleet system (e.g., individual machines, fleets, and industries). The analysis revealed that a significant proportion (35%) of operational costs were attributed to maintenance and repair activities, indicating areas for improvement in cost-efficiency. Multilevel regression analysis proved effective in measuring the cost-effectiveness of industrial machinery fleets in Senegal, providing actionable insights for stakeholders. Stakeholders should prioritise investment in predictive maintenance systems to reduce long-term operational costs and enhance fleet efficiency. The maintenance outcome was modelled as Yᵢₜ=β₀+β₁Xᵢₜ+uᵢ+εᵢₜ, with robustness checked using heteroskedasticity-consistent errors.
No takes yet. Share an insight, caveat, or question.
Ndiaye et al. (2006) studied this question.