Methodological Evaluation of Industrial Machinery Fleets: A Difference-in-Differences Model for Yield Improvement in Rwanda (2000–2026)

{ "background": "The optimisation of industrial machinery fleets is critical for enhancing manufacturing productivity in developing economies. However, rigorous, quantitative methodologies for evaluating the causal impact of fleet modernisation programmes on production yield are lacking in the engineering literature, particularly in sub-Saharan African contexts.", "purpose and objectives": "This study aims to develop and apply a robust quasi-experimental framework to measure the causal effect of a national industrial machinery upgrade initiative on manufacturing yield. The primary objective is to provide a methodological blueprint for engineering impact evaluation.", "methodology": "A comparative study employing a difference-in-differences (DiD) model. Treatment and control groups were formed from manufacturing plants based on their adoption status of modernised machinery fleets. The core econometric specification is $Y{it} = \\alpha + \\beta (Treati \\times Postt) + \\gammai + \\deltat + \\epsilon{it}$, where robust standard errors were clustered at the plant level. Longitudinal operational data were analysed.", "findings": "The DiD estimator revealed a statistically significant positive treatment effect. Plants in the treatment group experienced an average yield improvement of 17.3 percentage points (95% CI: 14.1, 20.5) relative to the control group following the intervention, indicating the efficacy of the systematic fleet upgrade.", "conclusion": "The applied DiD model provides a rigorous, evidence-based methodology for evaluating capital-intensive engineering interventions. It confirms that structured machinery fleet modernisation can substantially improve industrial production yields.", "recommendations": "Engineering policymakers should adopt quasi-experimental evaluation designs for large-scale infrastructure programmes. Future research should integrate maintenance log data into the DiD framework to disentangle the effects of equipment quality from operational practices.", "key words": "Difference-in-differences, causal inference, machinery fleets, yield improvement, industrial engineering, impact evaluation", "contribution statement": "This paper provides a novel application of the DiD econometric model to the field of industrial systems engineering, establishing