Multilevel Regression Analysis for Measuring Efficiency Gains in Industrial Machinery Fleets of Rwanda: A Methodological Evaluation
Key Points
Assess operational efficiency and maintenance costs in industrial machinery fleets using multilevel regression analysis.
Implemented a multilevel regression model analyzing performance data at individual and fleet levels.
Considered nested data structures for accurate analysis.
Focused on maintenance scheduling impacts on cost efficiencies.
Identified a 15% reduction in maintenance costs across the fleet.
Demonstrated significant efficiency gains in maintenance scheduling.
Confirmed that multilevel regression is a robust assessment method for fleet performance.
Abstract
Industrial machinery fleets in Rwanda face challenges related to operational efficiency and maintenance costs. A multilevel regression model is employed to analyse fleet performance data at both the individual machine level (level-1) and the fleet level (level-2). The model accounts for nested structures within the data. The multilevel analysis revealed significant efficiency gains in maintenance scheduling, reducing costs by approximately 15% across the fleet. Multilevel regression analysis provides a robust method for assessing and improving operational efficiency in industrial machinery fleets of Rwanda. Future research should consider extending this methodology to other sectors and regions within Rwanda. multilevel regression, industrial machinery, efficiency gains, Rwanda The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.