Multiple perspective consequence of failure estimation of subway stations

According to the Canadian Urban Transit Association (CUTA), the capital infrastructure needs for the period (2012-2016) are estimated at 53.5 billion CAD from which 40 Billion CAD only can be met by existing programs whereas a shortage of 13.5 billion CAD exists. The subway maintenance process is usually constrained by fund scarcity, which calls for a comprehensive prioritization method. The current practice adopted by most transit authorities prioritizes elements per station for rehabilitation based on the structural performance only while neglecting consequences of failure despite being crucial in ranking stations for rehabilitation. This paper presents a qualitative multi-perspective consequence of failure estimation model for subway metro stations. Consequences of failure are identified and assessed on multiple perspectives, namely; financial, operational, and social impacts of failure. The research revealed that the expected consequences of failure are interdependent and strongly connected; hence, the Fuzzy Analytic Network Process (FANP) is used with application to the Fuzzy Preference Programming (FPP) method. The FANP accommodates the subjectivity of human judgment as being expressed in natural language which entails 'fuzziness' in real-life problems and accounts for the interdependency between the selected attributes. The developed model offers a framework for clustering subway stations according to the expected consequences of failure severity for element level and station level. An illustrative example is presented to validate the model and prove its robustness. The proposed framework helps authorities prioritize stations and elements along stations for rehabilitation and highlights stations with more expected failure consequences for a more comprehensive asset analysis.