Statistical Data Analysis of Low-Level Nonconformances for Risk Assessment in Trackway Asset Management

Abstract

The purpose of this paper is to present a risk assessment approach for trackway asset management based on the statistical data analysis of low-level nonconformance rates, a key health monitoring parameter. Four elements in this analysis provide a systems engineering basis for: establishing the initial appearance of a nonconformance, key life cycle parameters, estimated delay mitigation costs, and capacity loss rate as a function of the nonconformance rate. Significant research has been done on risk assessment of severe and catastrophic nonconformances, focusing mainly on the steel rail sub-component. Instead, this research is focused on identifying the effect of aging on deterioration of trackway performance of the invert, ties, plates, and fastener sub-components, exclusive of rails, long before the initiation of impending critical nonconformances. While low-level trackway nonconformances pose virtually no risk to safety or service continuity, they do represent initial phase conditions of the deterioration cycle offering an intriguing opportunity for the study of behavioral forecasting. This research introduces the concept of a serviceability performance degradation rate, in an asset management framework, consisting of: (i) the useful service life expectancy of a device and the ages at which nonconformances at different severity levels can be expected; (ii) developing a serviceability performance degradation rate model; and (iii) forecasting the cost implications of deferred maintenance and associated financial risks. Focus on this early stage offers managers important insight into the assessment of the effect of aging on the asset deterioration cycle, and its associated financial risk, for prioritization of early intervention.