Accident precursors, near misses, and warning signs: Critical review and formal definitions within the framework of Discrete Event Systems

Saleh, Joseph H.; Saltmarsh, Elizabeth A.; Favaró, Francesca; Brevault, Loïc

doi:10.1016/j.ress.2013.01.006

Cited by 65 publications

(22 citation statements)

References 14 publications

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“…Therefore, lowering precursor frequency is an effective approach to reduce the accident probability [50]. An accident precursor is broadly defined as the "conditions, events, and sequences that precede and lead up to an accident" by the National Academy of Engineering [51]. Even though it is impossible to completely prevent coal mine accident, monitoring and controlling precursory information is a useful and effective approach for safety managers to identify hazards or risks in advance.…”

Section: Discussionmentioning

confidence: 99%

An Approach for Understanding and Promoting Coal Mine Safety by Exploring Coal Mine Risk Network

et al. 2017

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Capturing the interrelations among risks is essential to thoroughly understand and promote coal mining safety. From this standpoint, 105 risks and 135 interrelations among risks had been identified from 126 typical accidents, which were also the foundation of constructing coal mine risk network (CMRN). Based on the complex network theory and Pajek, six parameters (i.e., network diameter, network density, average path length, degree, betweenness, and clustering coefficient) were employed to reveal the topological properties of CMRN. As indicated by the results, CMRN possesses scale-free network property because its cumulative degree distribution obeys power-law distribution. This means that CMRN is robust to random hazard and vulnerable to deliberate attack. CMRN is also a small-world network due to its relatively small average path length as well as high clustering coefficient, implying that accident propagation in CMRN is faster than regular network. Furthermore, the effect of risk control is explored. According to the result, it shows that roof collapse, fire, and gas concentration exceeding limit refer to three most valuable targets for risk control among all the risks. This study will help offer recommendations and proposals for making beforehand strategies that can restrain original risks and reduce accidents.

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Section: Discussionmentioning

confidence: 99%

An Approach for Understanding and Promoting Coal Mine Safety by Exploring Coal Mine Risk Network

et al. 2017

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“…For the identification of the Near Misses, i.e., sequences of events that are similar to those accidental sequences leading the system into fault conditions, with the exception of a characteristic which is missing or is slightly different (e.g., sequence time lag, different failure magnitude, involved components) [Saleh et al, 2013], we adopt a risk-based clustering method [Di Maio et al, 2015c] that accounts for the order and timing of the events occurring along an accident sequence, and the magnitude of the process variables at the time of event occurrence [Aldemir et al, 2008;Di Maio et al, 2015c].…”

Section: Post-processing Analysis For Pis and Near Misses Identificationmentioning

confidence: 99%

Transient identification by clustering based on Integrated Deterministic and Probabilistic Safety Analysis outcomes

Maio

Vagnoli

Zio

2016

Annals of Nuclear Energy

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In this work, we present a transient identification approach that utilizes clustering for retrieving scenarios information from an Integrated Deterministic and Probabilistic Safety Analysis (IDPSA).The approach requires: i) creation of a database of scenarios by IDPSA; ii) scenario post-processing for clustering Prime Implicants (PIs), i.e., minimum combinations of failure events that are capable of leading the system into a fault state, and Near Misses, i.e., combinations of failure events that lead the system to a quasi-fault state; iii) on-line cluster assignment of an unknown developing scenario.In the step ii), we adopt a visual interactive method and risk-based clustering to identify PIs and Near Misses, respectively; in the on-line step iii), to assign a scenario to a cluster we consider the sequence of events in the scenario and evaluate the Hamming similarity to the sequences of the previously clustered scenarios. The feasibility of the analysis is shown with respect to the accidental scenarios of a dynamic Steam Generator (SG) of a NPP.

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“…The pilot was able to return the aircraft to base safely following the mishap. Despite successful recovery, the mishap is considered as a potential precursor to other accidents with more serious consequences [34].…”

Section: F-22 Raptor Accident September 28 2004mentioning

confidence: 99%

Software in military aviation and drone mishaps: Analysis and recommendations for the investigation process

Foreman¹,

Favaró²,

Saleh³

et al. 2015

Reliability Engineering & System Safety

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Software plays a central role in military systems. It is also an important factor in many recent incidents and accidents. A safety gap is growing between our software-intensive technological capabilities and our understanding of the ways they can fail or lead to accidents. Traditional forms of accident investigation are poorly equipped to trace the sources of software failure, for instance software does not age in the same way that hardware components fail over time. As such, it can be hard to trace the causes of software failure or mechanisms by which it contributed to accidents back into the development and procurement chain to address the deeper, systemic causes of potential accidents. To identify some of these failure mechanisms, we examined the database of the Air Force Accident Investigation Board (AIB) and analyzed mishaps in which software was involved. Although we have chosen to focus on military aviation, many of the insights also apply to civil aviation. Our analysis led to several results and recommendations. Some were specific and related for example to specific shortcomings in the testing and validation of particular avionic subsystems. Others were broader in scope: for instance, we challenged both the investigation process (aspects of) and the findings in several cases, and we provided recommendations, technical and organizational, for improvements. We also identified important safety blind spots in the investigations with respect to software, whose contribution to the escalation of the adverse events was often neglected in the accident reports. These blind spots, we argued, constitute an important missed learning opportunity for improving accident prevention, and it is especially unfortunate at a time when Remotely Piloted Air Systems (RPAS) are being integrated into the National Airspace. Our findings support the growing recognition that the traditional notion of software failure as non-compliance with requirements is too limited to capture the diversity of roles that software plays in military and civil aviation accidents. The identification of several specific mechanisms by which software contributes to accidents can help populate a library of patterns and triggers of software contributions to adverse events, a library which in turn can be used to help guide better software development, better coding, and better testing to avoid or eliminate these particular patterns and triggers. Finally, we strongly argue for the examination of software's causal role in accident investigations, the inclusion of a section on the subject in the accident reports, and the participation of software experts in accident investigations.

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Accident precursors, near misses, and warning signs: Critical review and formal definitions within the framework of Discrete Event Systems

Cited by 65 publications

References 14 publications

An Approach for Understanding and Promoting Coal Mine Safety by Exploring Coal Mine Risk Network

An Approach for Understanding and Promoting Coal Mine Safety by Exploring Coal Mine Risk Network

Transient identification by clustering based on Integrated Deterministic and Probabilistic Safety Analysis outcomes

Software in military aviation and drone mishaps: Analysis and recommendations for the investigation process

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