Quasi-Experimental Evaluation of Machinery Fleet Diagnostics and Yield Optimisation in Nigerian Industrial Systems

"background": "Industrial machinery fleets in Nigeria face persistent challenges with unplanned downtime and suboptimal output, yet there is a paucity of rigorous, field-based evaluations of diagnostic interventions within the local operational context. ", "purpose and objectives": "This study aimed to quantify the causal impact of a structured diagnostic protocol on the operational yield of industrial machinery fleets, evaluating its efficacy as a yield optimisation strategy. ", "methodology": "A quasi-experimental, difference-in-differences design was employed, comparing a treatment group (n=12 fleets) implementing the diagnostic protocol against a matched control group (n=12). The primary yield metric was Overall Equipment Effectiveness (OEE). The treatment effect was estimated using a fixed-effects panel model: Y{it = \0 + \1 (\) + \ + \ +, with inference based on cluster-robust standard errors. ", "findings": "Implementation of the diagnostic protocol significantly increased aggregate OEE by 7. 3 percentage points (95% CI: 4. 1, 10. 5; p<0. 01). The improvement was driven predominantly by enhanced availability, with a noted reduction in mean time to repair. ", "conclusion": "The structured diagnostic intervention proved to be a statistically significant and operationally meaningful driver of yield improvement, demonstrating the value of systematic fleet health monitoring in an industrial setting. ", "recommendations": "Industrial operators should integrate systematic diagnostic protocols into routine fleet management. Policymakers and industry bodies should consider developing guidelines to standardise such practices across sectors. ", "key words": "Machinery diagnostics, yield optimisation, quasi-experimental design, overall equipment effectiveness, industrial engineering, maintenance management", "contribution statement": "This paper provides novel empirical evidence from a quasi-experimental field study, establishing a causal link between diagnostic protocols and yield gains in an under-researched industrial context. "