{ "background": "The operational reliability of industrial machinery fleets is a critical determinant of productivity and economic output in developing industrial sectors. However, rigorous, field-based methodologies for assessing the reliability of such complex systems in real-world, resource-constrained environments are notably absent from the literature.", "purpose and objectives": "This study aimed to develop and implement a novel randomised field trial (RFT) protocol to quantitatively evaluate the reliability of industrial machinery fleet systems. The primary objective was to estimate key reliability metrics, including mean time between failures (MTBF) and availability, under actual operating conditions.", "methodology": "A randomised field trial was conducted across multiple industrial sites. Machinery units within fleets were randomly assigned to different operational and maintenance monitoring regimes. System reliability was modelled using a Weibull survival analysis, with the hazard function given by $h(t) = \\frac{\\beta}{\\eta} \\left( \\frac{t}{\\eta} \\right)^{\\beta-1}$. Data on failure times, repair durations, and contextual operational variables were collected prospectively.", "findings": "The application of the RFT protocol yielded a statistically significant increase in measured system availability. Specifically, fleets under the trial's intensified monitoring regime demonstrated a 17.5 percentage point improvement in operational availability (95% CI: 12.1 to 22.9) compared to control groups operating under standard practice.", "conclusion": "The randomised field trial proved to be a feasible and powerful methodological tool for the empirical assessment of machinery fleet reliability in a real-world industrial setting. It provided robust, quantitative evidence that structured monitoring directly enhances measurable system performance.", "recommendations": "Industrial operators should adopt principles of randomised evaluation for ongoing reliability and maintenance programme assessment. Further research should focus on integrating the RFT methodology with predictive maintenance frameworks to optimise resource allocation.", "key words": "reliability engineering, randomised field trial, maintenance, survival analysis, industrial machinery, developing context", "contribution statement": "This