Industrial machinery fleets in Ghana have experienced varying degrees of operational efficiency, necessitating a methodological assessment to identify best practices and yield improvements. A quasi-experimental design will be employed to compare pre- and post-intervention yields of industrial machinery fleets. Regression analysis will be used to control for confounding variables and estimate yield improvements. The preliminary findings suggest that implementing a regular maintenance schedule led to an average yield increase of 15% in the tested machinery fleet, with significant reductions in downtime attributed to preventative measures. This quasi-experimental design provides robust evidence for enhancing industrial machinery efficiency through strategic maintenance and management practices. Adoption of regular preventive maintenance schedules is recommended as a key strategy for improving yield across Ghanaian industrial machinery fleets. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.