Complexity on the rails: A systems-based approach to understanding safety management in rail transport

• Published in: Reliability engineering & system safety Vol. 188; pp. 352 - 365
• Main Authors: Read, G.J.M., Naweed, A., Salmon, P.M.
• Format: Journal Article
• Language: English
• Published: Barking Elsevier Ltd 01.08.2019; Elsevier BV
• Subjects: Accident analysis; Adaptive control; Catastrophe theory; Catastrophic events; Complexity; Domains; Feedback; Forensic engineering; Locomotives; Rail transport; Rail transportation; Railroads; Reliability engineering; Risk management; Safety; Safety critical; Safety management; STAMP; System theory; Systems theory; Transportation safety; Rail transport; STAMP; Risk management; Safety management
• ISSN: 0951-8320; 1879-0836
• DOI: 10.1016/j.ress.2019.03.038

•STAMP control structure model developed for rail transport system.•Participatory process with industry subject matter experts to refine model.•Feedback mechanisms need improvement to understand effectiveness of controls.•Lack of formal controls exists at higher levels of the system.•Feedback mechanisms focus on failures rather than learning from normal performance. Rail transport is a complex, safety-critical system which experiences catastrophic events. Systems theory-based approaches have been applied to understand risk and safety management in a range of safety-critical domains, however in rail, systems approaches have tended to be applied for accident analysis, rather than to describe how risk and safety is proactively managed. This study involved the development of a control structure model of rail transport in Australia using the Systems Theoretic Accident Model and Processes (STAMP) method. The control structure identifies the actors involved in managing safety, and shows the control and feedback mechanisms that comprise the adaptive feedback function to maintain safety. The control structure was refined in a participative process involving subject matter experts. Insights identified for improving safety management included: a need to improve feedback mechanisms to better understand the effectiveness of control measures; a lack of formal controls at higher levels of the system; and a focus within current feedback mechanisms on failures rather than understanding and learning from normal performance. Opportunities for applying the model in industry practice are also explored.