Journal Design Engineering Masthead
African Civil Engineering Journal | 22 June 2001

Methodological Evaluation and Reliability Diagnostics for Process-Control Systems in Uganda

A Quasi-Experimental Design
M, o, s, e, s, K, a, t, o, ,, J, u, l, i, u, s, O, c, h, i, e, n, g, ,, P, a, t, i, e, n, c, e, N, a, l, w, o, g, a, ,, G, r, a, c, e, N, a, k, i, m, e, r, a
Reliability DiagnosticsQuasi-Experimental DesignProcess-Control SystemsSub-Saharan Africa
A quasi-experimental framework enables field-based reliability assessment where randomized trials are impractical.
Sensor signal degradation emerged as a primary, quantifiable cause of system failure.
The Weibull analysis indicated an increasing failure rate over time for studied systems.
Results advocate for diagnostic protocols focused on signal integrity verification.

Abstract

{ "background": "Process-control systems in industrial and infrastructure projects are critical for operational efficiency and safety. In many developing contexts, systematic evaluation of their reliability is hindered by a lack of controlled field data and standardised diagnostic methodologies, leading to unplanned downtime and maintenance costs.", "purpose and objectives": "This working paper aims to develop and apply a quasi-experimental methodological framework for the empirical evaluation and reliability diagnostics of process-control systems. The primary objective is to quantify system failure rates and identify key diagnostic parameters under operational field conditions.", "methodology": "A quasi-experimental design was implemented, comparing system performance across matched treatment and control groups of installed systems. Reliability was modelled using a Weibull survival analysis, specified as $\\lambda(t|\\mathbf{x}) = \\frac{\\beta}{\\alpha} \\left( \\frac{t}{\\alpha} \\right)^{\\beta-1} \\exp(\\mathbf{x}^\\top \\gamma)$, where $\\lambda$ is the hazard rate, $t$ is time, and $\\mathbf{x}$ is a vector of covariates. Diagnostics included signal analysis and fault-tree assessments. Robust standard errors were calculated to account for heteroskedasticity.", "findings": "The analysis indicates a significant directional increase in the hazard rate for systems operating beyond specified electrical tolerance bands. A key finding is that approximately 40% of observed system faults were attributable to inconsistencies in signal integrity from primary sensors. The estimated shape parameter $\\beta$ was significantly greater than 1 (95% CI: 1.3 to 1.9), indicating an increasing failure rate over time.", "conclusion": "The proposed quasi-experimental framework provides a viable method for field-based reliability assessment where fully randomised trials are impractical. The results demonstrate that sensor signal degradation is a predominant, quantifiable failure pathway for the systems studied.", "recommendations": "Implement routine diagnostic protocols focused on signal integrity verification. Design specifications for new installations should include wider electrical tolerances and enhanced signal conditioning.