Abstract
{ "background": "Manufacturing systems in developing economies often face chronic inefficiencies, yet rigorous, field-based evidence on the efficacy of targeted interventions remains scarce. Prior studies in the region have largely relied on observational data, limiting causal inference.", "purpose and objectives": "This study aimed to quantify the causal impact of a structured process optimisation protocol on production efficiency within Ugandan manufacturing plants. The primary objective was to measure the treatment effect on overall equipment effectiveness (OEE).", "methodology": "A randomised field trial was conducted across 62 medium-scale manufacturing facilities. Plants were randomly assigned to treatment (implementation of a lean manufacturing protocol) or control groups. Efficiency was measured using OEE over a six-month period. The treatment effect was estimated using a linear mixed-effects model: $Y{it} = \\beta0 + \\beta1 Treatmenti + \\gamma X{it} + \\alphai + \\epsilon{it}$, where $\\alphai$ denotes plant-level random effects. Robust standard errors were clustered at the plant level.", "findings": "The intervention yielded a statistically significant increase in mean OEE. Treated plants achieved a 14.2 percentage point gain in OEE (95% CI: 9.8, 18.6; p < 0.001) relative to the control group. The largest efficiency improvements were observed in the performance and quality components of the OEE metric.", "conclusion": "The randomised trial provides robust causal evidence that systematic process interventions can generate substantial efficiency gains in this industrial context. The results demonstrate the viability of field-experimental methods for engineering research in manufacturing systems.", "recommendations": "Manufacturing practitioners should adopt evidence-based, incremental process protocols. Policymakers supporting industrial productivity programmes should incorporate randomised evaluation designs to validate intervention efficacy before scaling.", "key words": "randomised controlled trial, manufacturing efficiency, lean production, overall equipment effectiveness, industrial engineering, sub-Saharan Africa", "contribution statement": "This paper provides the first