"background": "Industrial machinery fleets in developing economies are critical for productivity, yet systematic analysis of their operational yield is limited. In Uganda, a lack of robust methodological frameworks hinders the empirical measurement of performance improvements and the identification of key drivers. ", "purpose and objectives": "This working paper aims to methodologically evaluate approaches for analysing fleet systems and to develop a panel-data estimation model for quantifying yield improvement. The objective is to provide a replicable analytical framework for engineering management. ", "methodology": "We construct a novel unbalanced panel dataset from maintenance and operational logs of heterogeneous machinery across multiple industrial sites. The core econometric specification is a two-way fixed effects model: Y{it = \ + \ Xit + \ + \ +, where Yit is the availability-adjusted yield. Inference is based on cluster-robust standard errors to account for within-fleet serial correlation. ", "findings": "The methodological evaluation identifies maintenance scheduling consistency as a superior predictor of yield compared to fleet age alone. The panel estimation reveals a positive and statistically significant relationship, with a one-standard-deviation improvement in preventive maintenance adherence associated with an approximate 7. 5% increase in mean yield (95% CI: 5. 1% to 9. 9%). ", "conclusion": "The proposed panel-data model provides a validated methodological framework for yield analysis in industrial machinery contexts. It demonstrates that operational practices, notably systematic maintenance, are quantifiable and significant levers for performance enhancement. ", "recommendations": "Fleet managers should prioritise the implementation of data-tracking systems to enable panel analysis. Policy should support the development of standardised performance metrics aligned with the model's variables to facilitate benchmarking across sectors. ", "key words": "panel data, fixed effects, yield, machinery, maintenance, operational efficiency, industrial engineering", "contribution statement": "This paper provides a novel application of panel-data econometrics to the analysis of industrial machinery fle
Otieno et al. (Wed,) studied this question.