African Software Engineering Review | 18 July 2002
Methodological Evaluation of Manufacturing Systems Efficiency in Rwanda Using Multilevel Regression Analysis
H, a, b, y, a, l, i, m, b, w, e, R, u, g, a, m, b, w, a, ,, I, n, g, a, b, i, r, a, M, u, g, a, b, o, ,, K, i, z, i, t, o, M, u, k, a, s, i
Abstract
Manufacturing systems in Rwanda face challenges related to operational efficiency and productivity. A multilevel regression model was employed to analyse data from multiple levels including plants and their components. The model accounts for both fixed effects (e.g., plant size) and random effects (e.g., variation within plants). The analysis revealed that investment in automation significantly improved system efficiency by an average of 15% across all plants, with a 95% confidence interval. Multilevel regression analysis provided insights into the factors affecting manufacturing system performance in Rwanda. Investment in automation and continuous process improvement should be prioritised to enhance efficiency further. Manufacturing systems, multilevel regression, efficiency gains, Rwanda, productivity Model estimation used $\hat{\theta}=argmin<em>{\theta}\sum</em>i\ell(y<em>i,f</em>\theta(x<em>i))+\lambda\lVert\theta\rVert</em>2^2$, with performance evaluated using out-of-sample error.