Incorporating epistemic uncertainty into the safety assurance of socio-technical systems

In system development, epistemic uncertainty is an ever-present possibility when reasoning about the causal factors during hazard analysis. Such uncertainty is common when complicated systems interact with one another, and it is dangerous because it impairs hazard analysis and thus increases the chance of overlooking unsafe situations. Uncertainty around causation thus needs to be managed well. Unfortunately, existing hazard analysis techniques tend to ignore unknown uncertainties, and system stakeholders rarely track known uncertainties well through the system lifecycle. In this paper, we outline an approach to managing epistemic uncertainty in existing hazard analysis techniques by focusing on known and unknown uncertainty. We have created a reference populated with a wide range of safety-critical causal relationships to recognise unknown uncertainty, and we have developed a model to systematically capture and track known uncertainty around such factors. We have also defined a process for using the reference and model to assess possible causal factors that are suspected during hazard analysis. To assess the applicability of our approach, we have analysed the widely-used MoDAF architectural model and determined that there is potential for our approach to identify additional causal factors that are not apparent from individual MoDAF views. We have also reviewed an existing safety assessment example (the ARP4761 Aircraft System analysis) and determined that our approach could indeed be incorporated into that process. We have also integrated our approach into the STPA hazard analysis technique to demonstrate its feasibility to incorporate into existing techniques. It is therefore plausible that our approach can increase safety assurance provided by hazard analysis in the face of epistemic uncertainty

Incorporating epistemic uncertainty into the safety assurance of socio-technical systems

In system development, epistemic uncertainty is an ever-present possibility when reasoning about the causal factors during hazard analysis. Such uncertainty is common when complicated systems interact with one another, and it is dangerous because it impairs hazard analysis and thus increases the chance of overlooking unsafe situations. Uncertainty around causation thus needs to be managed well. Unfortunately, existing hazard analysis techniques tend to ignore unknown uncertainties, and system stakeholders rarely track known uncertainties well through the system lifecycle. In this paper, we outline an approach to managing epistemic uncertainty in existing hazard analysis techniques by focusing on known and unknown uncertainty. We have created a reference populated with a wide range of safety-critical causal relationships to recognise unknown uncertainty, and we have developed a model to systematically capture and track known uncertainty around such factors. We have also defined a process for using the reference and model to assess possible causal factors that are suspected during hazard analysis. To assess the applicability of our approach, we have analysed the widely-used MoDAF architectural model and determined that there is potential for our approach to identify additional causal factors that are not apparent from individual MoDAF views. We have also reviewed an existing safety assessment example (the ARP4761 Aircraft System analysis) and determined that our approach could indeed be incorporated into that process. We have also integrated our approach into the STPA hazard analysis technique to demonstrate its feasibility to incorporate into existing techniques. It is therefore plausible that our approach can increase safety assurance provided by hazard analysis in the face of epistemic uncertainty

Going one step further: towards cognitively enhanced problem-solving teaming agents

Operating current advanced production systems, including Cyber-Physical Systems, often requires profound programming skills and configuration knowledge, creating a disconnect between human cognition and system operations. To address this, we suggest developing cognitive algorithms that can simulate and anticipate teaming partners' cognitive processes, enhancing and smoothing collaboration in problem-solving processes. Our proposed solution entails creating a cognitive system that minimizes human cognitive load and stress by developing models reflecting humans individual problem-solving capabilities and potential cognitive states. Further, we aim to devise algorithms that simulate individual decision processes and virtual bargaining procedures that anticipate actions, adjusting the system’s behavior towards efficient goal-oriented outcomes. Future steps include the development of benchmark sets tailored for specific use cases and human-system interactions. We plan to refine and test algorithms for detecting and inferring cognitive states of human partners. This process requires incorporating theoretical approaches and adapting existing algorithms to simulate and predict human cognitive processes of problem-solving with regards to cognitive states. The objective is to develop cognitive and computational models that enable production systems to become equal team members alongside humans in diverse scenarios, paving the way for more efficient, effective goal-oriented solutions

Managing Epistemic Uncertainties in the Underlying Models of Safety Assessment for Safety-Critical Systems

When conducting safety assessment for safety-critical systems, epistemic uncertainty is an ever-present challenge when reasoning about the safety concerns and causal relationships related to hazards. Uncertainty around this causation thus needs to be managed well. Unfortunately, existing safety assessment tends to ignore unknown uncertainties, and stakeholders rarely track known uncertainties well through the system lifecycle. In this thesis, an approach is described for managing epistemic uncertainties about the system and safety causal models that are applied in a safety assessment. First, the principles that define the requirements for the approach are introduced. Next, these principles are used to construct three distinct steps that constitute an approach to manage such uncertainties. These three steps involve identifying, documenting and tracking the uncertainties throughout the system lifecycle so as to enable intervention to address the uncertainties. The approach is evaluated by integrating it with two existing safety assessment techniques, one using models from a system viewpoint and the other with models from a component viewpoint. This approach is also evaluated through peer reviews, semi-structured interviews with practitioners, and by review against requirements derived from the principles. Based on the evaluation results, it is plausible that our approach can provide a feasible and systematic way to manage epistemic uncertainties in safety assessment for safety-critical systems

Pushing the Boundaries of System Safety: 35th International System Safety Conference

The 35th Annual ISSC was held August 21-25, 2017 in Albuquerque, New Mexico. This year’s theme was intended not only to redefine how system safety is applied in different domains, but to also reach into our past for lessons learned and go beyond our present thinking as we confront new challenges. It was intended to push the boundaries of the system of safety, as well as how we think about the safety of systems. Highlights of the 35th International System Safety Conferenc

Applying the water safety plan to water reuse: towards a conceptual risk management framework

The Water Safety Plan (WSP) is receiving increasing attention as a recommended risk management approach for water reuse through a range of research programmes, guidelines and standards. Numerous conceptual modifications of the approach – including the Sanitation Safety Plan, the Water Cycle Safety Plan, and even a dedicated Water Reuse Safety Plan – have been put forward for this purpose. However, these approaches have yet to encapsulate the full spectrum of possible water reuse applications, and evidence of their application to reuse remains limited. Through reviewing the existing evidence base, this paper investigates the potential for adapting the WSP into an approach for water reuse. The findings highlight a need for the management of risk to reflect on, and facilitate the inclusion of, broader contexts and objectives for water reuse schemes. We conclude that this could be addressed through a more integrated approach to risk management, encapsulated within an overarching risk management framework (adapted from the WHO's Framework for safe drinking water) and operationalised through the Water Reuse Safety Plan (WRSP). We also propose that the WRSP should be based on modifications to the existing WSP approach, including an increased emphasis on supporting communication and engagement, and improvements in decision support mechanisms to better account for uncertainty, risk interactions and risk prioritisation

Structural identification: Opportunities and challenges

Some of the significant opportunities and facing successful implementation of the structural identification (St-Id) in civil infrastructure are discussed. The greatest challenges in successful applications of St-Id have emerged as systems integration requirements, requiring mastery in management, modeling and simulation, experimental arts, information technology, and decision-making. Formulating effective policies, strategies, and project-specific designs for improving their performance as systems cannot be expected unless it is understood how infrastructures perform as complex systems. The St-Id may be a means of establishing a quantitative and mechanistic baseline characterization for a newly constructed system similar to a birth certificate. Some major infrastructure owners and consultants have developed an appreciation of the value of St-Id in relation to retrofit design and historic preservation