Journal Design Engineering Masthead
African Civil Engineering Journal | 08 December 2001

Multilevel Regression Analysis of Industrial Machinery Fleet Reliability for Maintenance Policy in Uganda, 2000–2026

G, r, a, c, e, A, k, e, l, l, o, ,, I, s, a, a, c, M, u, g, i, s, h, a, ,, P, a, t, i, e, n, c, e, N, a, l, w, o, g, a, ,, M, o, s, e, s, K, a, t, o
Maintenance PolicyMultilevel ModellingSystem ReliabilityUganda
A 15.2% increase in MTBF is associated with greater predictive maintenance investment.
Firm-level practices, not sectoral traits, are the primary drivers of fleet reliability.
Multilevel regression isolates variance across machines, firms, and industrial sectors.
Findings support a policy shift from reactive to predictive maintenance strategies.

Abstract

{ "background": "The reliability of industrial machinery fleets is a critical determinant of productivity and economic growth in developing economies. In Uganda, systemic maintenance policy has historically been reactive, leading to high downtime and capital inefficiency. A rigorous, data-driven framework for evaluating fleet reliability to inform national policy is absent.", "purpose and objectives": "This policy analysis article aims to develop and apply a multilevel regression modelling framework to quantify the reliability of industrial machinery fleets. The objective is to identify the key operational and policy-level factors influencing reliability to provide evidence for a shift towards predictive maintenance strategies.", "methodology": "A longitudinal dataset of maintenance records from multiple industrial sectors was analysed. The core methodological approach is a three-level hierarchical linear model, specified as $\\text{Log}(\\text{MTBF}{ijk}) = \\beta{0} + \\beta{1}X{ijk} + u{j} + v{k} + \\epsilon_{ijk}$, where $i$, $j$, and $k$ index machines, firms, and sectors, respectively. Robust standard errors were used for inference on fixed effects.", "findings": "The analysis reveals that firm-level maintenance expenditure and operator training protocols explain approximately 40% of the variance in mean time between failures (MTBF). A one-standard-deviation increase in predictive maintenance investment is associated with a 15.2% increase in MTBF (95% CI: 11.8% to 18.6%). Sectoral differences were statistically significant but substantively small.", "conclusion": "Fleet reliability in Uganda is predominantly driven by firm-level practices rather than sector-wide characteristics. This underscores the potential for targeted policy interventions to elevate maintenance standards across industries.", "recommendations": "National industrial policy should incentivise capital investment in predictive maintenance technologies. A state-supported technician certification programme should be established. Fiscal measures, including accelerated depreciation for maintenance software and sensor systems, are recommended.", "key words": "Maintenance policy, multilevel modelling, system reliability