The Risk Situation Awareness Provision Capability and its Degradation in the Überlingen Accident over Time

AbstractThis paper presents a STAMP-based indicator of measuring the inherent, in terms of the system design and development, capability of each system part to provide its agent with Situation Awareness (SA) about the presence of system threats and vulnerabilities that may lead to accidents. An agent is a human or automated controller that possesses reasoning mechanisms and demonstrates a capability to influence others or modify situations. This capability – in as far as it pertains to risk modification - is called “risk SA provision capability” (RiskSOAP) and can be modelled in a control loop. This capability is considered as dynamic because it can fluctuate over time due to changes in safety specifications and short- or long-term conditions. In order to demonstrate the fluctuation of the risk SA provision capability along the development of an accident, the STAMP-based RiskSOAP indicator is calculated throughout the Überlingen accident timeline. This timeline incorporates four milestones, each one denoting a particular time point in the accident development. The decline in the value of the RiskSOAP indicator is attributed to the presence of flaws and unsafe control actions, through which accident scenarios are verified and the system is headed for an accident. The main conclusion is that in such socio-technical systems there is a tight coupling between the degradation of the risk SA provision capability and the degradation of safety

Managing sociotechnical risks in infrastructure projects : Sociotechnical Systems (STS) perspectives on systems

As systems become larger, more complex and integrated, the cost of failure increases rapidly, leading to a need for effective risk management tools. However, conventional risk management tools such as the ones based on hazard analysis or accident causation analysis have a narrow focus on either human or technical actors and on single causal chains at one organisational level. This led researchers to introduce the concept of Sociotechnical Systems (STS), involving the interaction of human and non-human technical components. The present study was conducted with the aim of developing ways of applying STS principles and STS-based methods to improve the risk management in large infrastructure projects. Initially, the sets of STS principles for the system design, which had been developed so far, were identified and then integrated and synthesised to produce a list of 20 core STS principles for applying them further in the current study. A comprehensive literature review of the work done in this field since its inception in the 1950s was then conducted, producing a unified list of 103 STS-based methods. These methods were then evaluated for their validity and visibility (occurrence). To identify and analyse major risks in complex infrastructure projects from an STS perspective, an observational case study of a large-scale collaborative design project at Heriot-Watt University was conducted, including running the surveys and interviews with the project participants. The aim was to find out if the presence or absence of the 20 STS principles and 18 associated risk factors affected the performance of the teams. It was found that the team performance was strongly related to the presence or absence of STS principles that was supported by statistically meaningful results of a quantitative analysis. The same STS principles were then applied retrospectively to a second case study, which was the construction of the Edinburgh Tram Network, based on documentary sources and employing the AcciMap and Abstraction Hierarchy (AH) methods. It was concluded that failure to apply these principles and the resulting risks could play a major role in the failure to deliver the project on time and within budget. Finally, a five-phase framework was constructed for STS-based risk management framework of infrastructure projects, with the guideline principles aligning the existing risk management framework with STS theory