Methodological Evaluation of Industrial Machinery Fleets Systems in Rwanda Using Panel Data for Cost-Effectiveness Analysis
Key Points
The research aims to evaluate the cost-effectiveness of industrial machinery fleets in Rwanda by analyzing fleet utilization and maintenance costs.
Utilized econometric techniques including fixed effects models
Analyzed data from Rwandan industrial machinery fleets
Examined utilization and maintenance costs through panel data analysis
52% of operational machinery assets are underutilized
Optimizing fleet operations could reduce overall expenditure by approximately 10%
Predictive maintenance strategies showed potential for cost savings
Abstract
Industrial machinery fleets play a crucial role in Rwanda's manufacturing sector, contributing to productivity and economic growth. The study employs econometric techniques such as fixed effects models to analyse fleet utilization and maintenance costs. A significant proportion (52%) of operational machinery assets are underutilized, indicating potential inefficiencies in management practices. Cost-effectiveness ratios indicate that optimising fleet operations could reduce overall expenditure by approximately 10%. Implementing predictive maintenance strategies and improving asset utilization through data analytics can enhance cost savings. The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.