Multilevel regression analysis evaluates system reliability in industrial machinery fleets, suggesting better maintenance strategies for enhanced performance.
Industrial machinery fleets play a crucial role in Ghana's manufacturing sector, impacting productivity and operational costs. A multilevel regression model was employed to assess system reliability, accounting for both fixed effects (industry type) and random effects (geographical regions). The multilevel regression analysis revealed that machinery age significantly affects fleet reliability, with older machines being less reliable. This study provides a robust framework for assessing industrial machinery reliability in Ghana, contributing to improved maintenance strategies. Industry stakeholders should prioritise the replacement of aging machinery to enhance system performance and reduce downtime. Industrial Machinery Reliability Multilevel Regression Analysis Ghana The maintenance outcome was modelled as Yᵢₜ=β₀+β₁Xᵢₜ+uᵢ+εᵢₜ, with robustness checked using heteroskedasticity-consistent errors.
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Kofi Ameyaw (2003) studied this question.
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