Methodological Assessment of Industrial Machinery Fleet Systems in Rwanda: Quasi-Experimental Design for Yield Improvement Evaluation

The industrial machinery fleet systems in Rwanda have seen limited adoption of advanced management techniques, leading to suboptimal performance and inefficiencies. A mixed-method approach combining quantitative analysis with qualitative interviews was employed. Data on fleet utilization, maintenance costs, and operational yields were collected from ten randomly selected enterprises over one year. Significant variations were observed in the yield improvement across different fleet management systems, with an average increase of 18% in those using predictive maintenance models compared to baseline systems. The quasi-experimental design proved effective for measuring yield improvements and highlighted the benefits of adopting advanced machinery management strategies. Rwanda's industrial sectors should consider implementing a similar comparative analysis to identify optimal fleet management solutions. This could lead to substantial cost savings and efficiency gains. industrial machinery, fleet systems, quasi-experimental design, yield improvement, Rwanda The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.