A Randomised Field Trial for the Cost-Effectiveness Diagnostics of Manufacturing Systems in Ethiopia

{ "background": "Manufacturing systems in developing economies often lack robust, field-validated methods for cost-effectiveness diagnostics. Existing evaluation frameworks are typically derived from high-income contexts and may not account for local operational constraints and resource availability.", "purpose and objectives": "This study aimed to develop and empirically test a novel, randomised field trial methodology for evaluating the cost-effectiveness of diagnostic interventions in manufacturing plants. The primary objective was to determine the causal impact of a structured diagnostic protocol on operational cost reduction.", "methodology": "A randomised controlled trial was conducted across a sample of manufacturing facilities. Plants were randomly assigned to a treatment group receiving the diagnostic intervention or a control group. Cost data were collected pre- and post-intervention. The primary analysis used a difference-in-differences model: Cit = \α + \β1 (Treati \× Postt) + \β2 Xit + \εᵢₜ, where C is cost, with inference based on cluster-robust standard errors.", "findings": "The diagnostic intervention significantly reduced average monthly operational costs by 18.2% (95% CI: 12.5% to 23.9%, p<0.01) in treatment plants relative to controls. The most substantial savings were identified in energy consumption and raw material waste streams.", "conclusion": "The randomised field trial provides a rigorous methodological framework for cost-effectiveness evaluation in industrial settings. The applied diagnostic protocol demonstrated a statistically and economically significant positive impact.", "recommendations": "Manufacturing enterprises should adopt structured diagnostic evaluations informed by field-trial evidence. Policymakers and engineering practitioners should prioritise interventions targeting energy and material efficiency.", "key words": "randomised controlled trial, industrial diagnostics, cost-effectiveness, operational efficiency, manufacturing systems", "contribution statement": "This paper provides the first application of a randomised field trial methodology to evaluate engineering diagnostics in an industrial context, generating a novel dataset of causal evidence on cost-reduction interventions