"background": "The reliability of manufacturing systems is a critical determinant of industrial productivity and economic development. In many developing economies, systematic methodological frameworks for assessing and modelling this reliability are lacking, leading to reactive maintenance and suboptimal performance. ", "purpose and objectives": "This case study aims to methodologically evaluate the operational reliability of selected manufacturing plants and to develop a robust multilevel regression model for analysing the key factors influencing system failure rates within this context. ", "methodology": "A cross-sectional case study was conducted across multiple manufacturing sectors. System reliability data were collected through direct observation, maintenance logs, and engineer interviews. A three-level hierarchical linear model was specified: \ () = \0 + u{j + vk + \pijk, where is the failure rate for machine i in plant j within sector k, uj and vk are random intercepts, and Xp are predictor variables. Estimation used restricted maximum likelihood with robust standard errors. ", "findings": "The multilevel analysis revealed that preventive maintenance adherence was the most significant predictor of reliability, with a one-unit increase in the standardised adherence score associated with a 31% reduction in the predicted failure rate (95% CI: 24% to 37%). Plant-level management practices accounted for approximately 40% of the residual variance in outcomes after controlling for machine age and type. ", "conclusion": "The methodological approach demonstrates that manufacturing systems reliability is predominantly influenced by organisational and procedural factors, rather than solely by equipment-level characteristics. The multilevel model provides a superior fit for the nested data structure common in industrial settings. ", "recommendations": "Manufacturing firms should institutionalise data-driven reliability programmes focused on procedural compliance. Policymakers are advised to support the development of standardised reliability metrics and reporting frameworks to facilitate sector-wide benchmarking and improvement. ", "key words
Tesfaye et al. (Sat,) studied this question.