Abstract
Process-control systems are critical for industrial and infrastructure operations, yet their reliability in developing contexts is poorly understood. Inadequate maintenance and governance frameworks often lead to systemic failures, but diagnostic methods to quantify these issues are lacking. This policy analysis aims to develop and test a novel field-based diagnostic methodology for evaluating the reliability of process-control systems. The objective is to provide a replicable tool for identifying specific maintenance and governance failures affecting engineering system performance. A randomised field trial was conducted across multiple industrial sites. System reliability was measured as a binary operational state, analysed using a logistic regression model: $\logit(pi) = \beta0 + \beta1 Gi + \beta2 Mi + \epsiloni$, where $Gi$ and $M_i$ represent governance and maintenance indices. Robust standard errors were clustered by site. The governance index was a stronger predictor of failure than the maintenance index. Sites with governance scores below the trial median were 2.3 times more likely to experience a control system failure (95% CI: 1.7 to 3.2). A key theme was the critical role of documented accountability procedures. Governance structures, more than technical maintenance inputs, are the primary determinant of process-control system reliability in the studied context. This necessitates a shift in policy focus towards institutional accountability. Policy should mandate regular, standardised reliability diagnostics using this field-trial methodology. Investment should be directed towards strengthening operational governance protocols, including clear failure reporting lines and accountability frameworks for system upkeep. system reliability, randomised trial, maintenance diagnostics, governance, process control, industrial policy This paper provides a novel, empirically validated field methodology for diagnosing the root causes of engineering system failures, moving beyond anecdotal evidence to targeted policy intervention.