"background": "The reliability of industrial machinery fleets is a critical determinant of productivity and economic output. In many industrialising nations, systematic assessment of fleet-wide reliability is hindered by a lack of longitudinal data and the challenge of isolating the effect of maintenance interventions from concurrent operational changes. ", "purpose and objectives": "This paper develops and applies a quasi-experimental econometric model to quantify the causal impact of a structured preventive maintenance programme on the operational reliability of heavy machinery fleets within the country's industrial sector. ", "methodology": "A difference-in-differences (DiD) model is specified as Y{it = \0 + \1 + \2 + \ (\) +, where Yit is the monthly uptime percentage for unit i in period t. The parallel trends assumption is tested, and robust standard errors are clustered at the fleet level to account for serial correlation. ", "findings": "The implementation of the preventive maintenance programme was associated with a statistically significant increase in mean fleet uptime. The DiD estimator, \, was 7. 3 percentage points (95% CI: 5. 1, 9. 5). This effect was robust to the inclusion of control variables for machine age and utilisation hours. ", "conclusion": "The DiD framework provides a rigorous methodological approach for reliability assessment in settings with limited pre-intervention data, successfully isolating the causal effect of the maintenance programme from underlying temporal trends. ", "recommendations": "Industrial asset managers should adopt quasi-experimental evaluation designs to validate the efficacy of reliability-centred maintenance strategies. Further research should apply the model to different machinery types and sectors. ", "key words": "reliability engineering, maintenance optimisation, causal inference, econometric modelling, industrial assets", "contribution statement": "This paper presents a
Suleiman et al. (Mon,) studied this question.