{ "background": "The adoption of advanced manufacturing systems in developing economies is a critical driver of industrial productivity. However, rigorous, evidence-based evaluations of adoption rates and causal impacts within the African context remain scarce, with many studies relying on descriptive or correlational analyses.", "purpose and objectives": "This study aims to provide a robust methodological evaluation of manufacturing systems adoption. Its primary objective is to quantify the causal effect of targeted intervention programmes on the uptake of integrated computer-aided manufacturing (ICAM) systems using a quasi-experimental design.", "methodology": "A comparative, longitudinal study was conducted, analysing panel data from a treatment group of plants participating in a national industrial modernisation scheme and a matched control group. The core impact was estimated using a difference-in-differences model: $Y{it} = \\beta0 + \\beta1 (\\text{Treat}i \\times \\text{Post}t) + \\gammai + \\deltat + \\epsilon{it}$, where $Y_{it}$ is the adoption index for plant $i$ in period $t$. Inference was based on cluster-robust standard errors at the plant level.", "findings": "The analysis indicates a statistically significant positive treatment effect. Plants under the intervention scheme demonstrated a 34% higher aggregate adoption rate of ICAM systems compared to the control group (95% CI: 22% to 46%). The integration of production planning and control modules showed the most substantial increase.", "conclusion": "The quasi-experimental design confirms that structured intervention programmes can significantly accelerate the adoption of advanced manufacturing systems. The findings underscore the importance of policy-supported mechanisms for technological upgrading.", "recommendations": "Policymakers should design and scale intervention schemes with clear technical support components. Plant managers should prioritise the implementation of integrated planning modules as a foundational step. Future research should incorporate lifecycle cost analysis.", "key words": "manufacturing systems, technology adoption, quasi-experimental design, difference-in-differences, industrial