{ "background": "The persistent challenge of low productivity and high operational costs within the nation's manufacturing sector necessitates robust, data-driven methodologies for evaluating plant system efficiency. Existing cost-effectiveness analyses often rely on cross-sectional data, which fails to account for unobserved heterogeneity and dynamic performance changes over time.", "purpose and objectives": "This case study aims to methodologically evaluate the application of panel-data econometric techniques for measuring cost-effectiveness in manufacturing plant systems. Its objective is to demonstrate a replicable framework that isolates true efficiency gains from transient shocks and firm-specific effects.", "methodology": "A longitudinal dataset from multiple manufacturing plants was analysed using a fixed-effects panel regression model. The core specification was $\\ln(\\text{Unit Cost}){it} = \\alphai + \\beta1 \\ln(\\text{Output}){it} + \\beta2 \\text{TechIndex}{it} + \\epsilon{it}$, where $\\alphai$ captures plant-specific fixed effects. Inference was based on robust standard errors clustered at the plant level.", "findings": "The panel estimation revealed that a one-unit increase in the technology adoption index was associated with a 4.7% reduction in unit cost, a relationship obscured in pooled OLS estimates. The fixed effects were statistically significant, confirming substantial unobserved heterogeneity across plants.", "conclusion": "Panel-data methods provide a superior methodological framework for cost-effectiveness evaluation in this context, controlling for biases inherent in simpler analytical approaches. This leads to more accurate identification of the drivers of engineering and operational efficiency.", "recommendations": "Industry practitioners and engineering managers should adopt panel-data frameworks for internal performance benchmarking. Future research should integrate engineering system parameters directly into the econometric specification.", "key words": "panel data, fixed effects, cost-effectiveness, manufacturing systems, operational efficiency, econometric modelling", "contribution statement": "This study provides a novel applied framework for integrating panel-data econometrics into engineering management practice, demonstrating that accounting for unobserved plant heterogeneity reverses the