Toward Quantifying Metrics for Rail-system Resilience: Identification and Analysis of Performance Weak Resilience Signals

This paper aims to enhance tangibility of the resilience engineering concept by facilitating understanding and operationalization of weak resilience signals (WRSs) in the rail sector. Within complex socio-technical systems, accidents can be seen as unwanted outcomes emerging from uncontrolled sources of entropy (functional resonance). Various theoretical models exist to determine the variability of system interactions, the resilience state and the organization’s intrinsic abilities to reorganize and manage their functioning and adaptive capacity to cope with unexpected and unforeseen disruptions. However, operationalizing and measuring concrete and reliable manifestations of resilience and assessing their impact at a system level have proved to be a challenge. A multi-method, ethnographic observation and resilience questionnaire, were used to determine resilience baseline conditions at an operational rail traffic control post. This paper describes the development, implementation and initial validation of WRSs identified and modeled around a ‘performance system boundary.’ In addition, a WRS analysis function is introduced to interpret underlying factors of the performance WRSs and serves as a method to reveal potential sources of future resonance that could comprise system resilience. Results indicate that performance WRSs can successfully be implemented to accentuate relative deviations from resilience baseline conditions. A WRS analysis function can help to interpret these divergences and could be used to reveal (creeping) change processes and unnoticed initiating events that facilitate emergence that degrades rail-system resilience. Establishing relevant change signals in advance can contribute to anticipation and awareness, enhance organizational learning and stimulate resilient courses of action and adaptive behavior that ensures rail operation reliability.


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  • Accession Number: 01598273
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Apr 11 2016 10:24AM