"background": "The Ethiopian industrial sector faces persistent challenges in productivity and global competitiveness. While manufacturing systems engineering principles are promoted for efficiency gains, rigorous empirical evidence of their impact within the local operational context is scarce. ", "purpose and objectives": "This study aimed to quantify the causal effect of implementing integrated lean-production systems on operational efficiency within manufacturing plants. The primary objective was to measure gains in Overall Equipment Effectiveness (OEE) following a structured intervention. ", "methodology": "A quasi-experimental, difference-in-differences design was employed, comparing 12 treatment plants undergoing a standardised systems intervention with 12 matched control plants. Efficiency was measured via OEE over multiple periods. The core impact was estimated using the model \ OEE{it = \0 + \1 (\) + \ Xit + \₈ₓ, with inference based on cluster-robust standard errors. ", "findings": "The intervention yielded a statistically significant positive effect. The estimated average treatment effect on OEE was 14. 7 percentage points (95% CI: 9. 2, 20. 2). Analysis of components showed the largest gain derived from improved performance rate, rather than availability or quality rate. ", "conclusion": "The implementation of formal manufacturing systems engineering significantly enhances operational efficiency in the studied context. The quasi-experimental design provides robust evidence of a causal relationship, moving beyond correlational analysis. ", "recommendations": "Industry policymakers should develop targeted support programmes to facilitate the adoption of integrated lean-production systems. Plant managers should prioritise performance rate improvements through standardised work and downtime analysis as initial implementation steps. ", "key words": "manufacturing systems, quasi-experimental design, operational efficiency, lean production, industrial engineering, Ethiopia", "contribution statement": "This study provides the first application of a quasi-experimental, difference-in-differences methodology to isolate the causal impact of manufacturing systems interventions
Tadesse et al. (Thu,) studied this question.