A systems-theoretic hazard analysis for safety-critical medical gas pipeline and oxygen supply systems

Providing an approach to analyze the risk of central oxygen tanks in hospitals during the COVID-19 pandemic

The central oxygen unit of hospitals is considered a high-risk unit, requiring high safety standards to maintain the integrity of the system during the COVID-19 pandemic. The linear reasoning assumption of conventional risk analysis methods cannot adequately describe these modern systems, which are characterized by tight connections and complex interactions between technical, human, and organizational aspects. Therefore, this study presents a new and comprehensive approach to oxygen tanks in hospitals during the COVID-19 pandemic. In this study, trapezoidal fuzzy numbers were used to calculate failure rates. After determining the probability of basic events (BEs), intermediate events (IE), and top event (TE) with fuzzy logic and transferring it into Bayesian Network (BN), deductive and inductive reasoning, and sensitivity analysis were performed using RoV in GeNIe software. The results of the case study showed that the IE of "Human Error" had the highest probability of fuzzy fault tree (FFT) and the probability of oxygen leakage was lower using FBN than FFT. According to the results, BE16 (failure to use standard and updated instructions) and BE12 (defects in the inspection and testing program of tank devices) had the highest posterior probability, while based on the FFT results, BE4 (defects in the external coating system of the tank) and, BE3 (Corrosive environment (acidity state)) had the least probability. According to the sensitivity analysis, basic events 10, 11, and 16 were the most important in the oxygen leakage event with a very small difference, which was almost in line with the results of posterior FBN (FBNPO). Updating the existing guidelines, fixing defects in the inspection of all types of tank gauges, and testing related equipment can greatly help the reliability of these tanks. Root cause analysis of these events provides opportunities for prevention and emergency response in critical situations, such as the COVID-19 pandemic.

Learning from Incidents in Socio-Technical Systems: A Systems-Theoretic Analysis in the Railway Sector

Post mortem incident investigations are vital to prevent the occurrence of similar events and improve system safety. The increasing interactions of technical, human and organizational elements in modern systems pose new challenges for safety management, demanding approaches capable of complementing techno-centric investigations with social-oriented analyses. Hence, traditional risk analysis methods rooted in event-chain reactions and looking for individual points of failure are increasingly inadequate to deal with system-wide investigations. They normally focus on an oversimplified analysis of how work was expected to be conducted, rather than exploring what exactly occurred among the involved agents. Therefore, a detailed analysis of incidents beyond the immediate failures extending towards socio-technical threats is necessary. This study adopts the system-theoretic accident model and process (STAMP) and its nested accident analysis technique, i.e., causal analysis based on systems theory (CAST), to propose a causal incident analysis in the railway industry. The study proposes a hierarchical safety control structure, along with system-level safety constraints, and detailed investigations of the system’s components with the purpose of identifying physical and organizational safety requirements and safety recommendations. The analysis is contextualized in the demonstrative use of a railway case. In particular, the analysis is instantiated for a 2011 incident in the United Kingdom (UK) railway system. Hence, the CAST technique requires information regarding incidents, facts and processes. Therefore, the case study under analysis provided the information to analyze the accidents based on system theory, in which the results of the analysis prove the benefits of a CAST application to highlight criticalities at both element- and system-level, spanning from component failure to organizational and maintenance planning, enhancing safety performance in normal work practices.