A novel qualitative prospective methodology to assess human error during accident sequences

Numerous theoretical models and techniques to assess human error were developed since the 60's. Most of these models were developed for the nuclear, military, and aviation sectors. These methods have the following weaknesses that limit their use in industry: the lack of analysis of underlying causal cognitive mechanisms, need of retrospective data for implementation, strong dependence on expert judgment, focus on a particular type of error, and/or analysis of operator behaviour and decision-making without considering the role of the system in such decisions. The purpose of the present research is to develop a qualitative prospective methodology that does not depend exclusively on retrospective information, that does not require expert judgment for implementation and that allows predicting potential sequences of accidents before they occur. It has been proposed for new (or existent) small and medium- scale facilities, whose processes are simple. To the best of our knowledge, a methodology that meets these requirements has not been reported in literature thus far. The methodology proposed in this study was applied to the methanol storage area of a biodiesel facility. It could predict potential sequences of accidents, through the analysis of information provided by different system devices and the study of the possible deviations of operators in decision-making. It also enabled the identification of the shortcomings in the human-machine interface and proposed an optimization of the current configuration.Fil: Calvo Olivares, Romina Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Cuyo. Facultad de Ingenieria. Instituto de Capacitación Especial y Desarrollo de Ingeniería Asistida por Computadora; ArgentinaFil: Rivera, Selva Soledad. Universidad Nacional de Cuyo. Facultad de Ingenieria. Instituto de Capacitación Especial y Desarrollo de Ingeniería Asistida por Computadora; ArgentinaFil: Núñez Mc Leod, Jorge Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Cuyo. Facultad de Ingenieria. Instituto de Capacitación Especial y Desarrollo de Ingeniería Asistida por Computadora; Argentin

Civil and Military Airworthiness

Effective safety management has always been a key objective for the broader airworthiness sector. This book is focused on safety themes with implications on airworthiness management. It offers a diverse set of analyses on aircraft maintenance accidents, empirical and systematic investigations on important continuing airworthiness matters and research studies on methodologies for the risk and safety assessment in continuing and initial airworthiness. Overall, this collection of research and review papers is a valuable addition to the published literature, useful for the community of aviation professionals and researchers

A new approach to analysing human-related accidents by combined use of HFACS and activity theory-based method

This study proposes a new method for modelling and analysing human-related accidents. It integrates HFACS (Human Factors Analysis and Classification System), which addresses most of the socio-technical system levels and offers a comprehensive failure taxonomy for analysing human errors, and AT (Activity Theory)-based approach, which provides an effective way for considering various contextual factors systematically in accident investigation. By combining them, the proposed method makes it more efficient to use the concepts and principles of AT. Additionally, it can help analysts use HFACS taxonomy more coherently to identify meaningful causal factors with a sound theoretical basis of human activities. Therefore, the proposed method can be effectively used to mitigate the limitations of traditional approaches to accident analysis, such as over-relying on a causality model and sticking to a root-cause, by making analysts look at an accident from a range of perspectives. To demonstrate the usefulness of the proposed method, we conducted a case study in nuclear power plants. Through the case study, we could confirm that it would be a useful method for modelling and analysing human-related accidents, enabling analysts to identify a plausible set of causal factors efficiently in a methodical consideration of contextual backgrounds surrounding human activities

Classification and reduction of pilot error

Human error is a primary or contributing factor in about two-thirds of commercial aviation accidents worldwide. With the ultimate goal of reducing pilot error accidents, this contract effort is aimed at understanding the factors underlying error events and reducing the probability of certain types of errors by modifying underlying factors such as flight deck design and procedures. A review of the literature relevant to error classification was conducted. Classification includes categorizing types of errors, the information processing mechanisms and factors underlying them, and identifying factor-mechanism-error relationships. The classification scheme developed by Jens Rasmussen was adopted because it provided a comprehensive yet basic error classification shell or structure that could easily accommodate addition of details on domain-specific factors. For these purposes, factors specific to the aviation environment were incorporated. Hypotheses concerning the relationship of a small number of underlying factors, information processing mechanisms, and error types types identified in the classification scheme were formulated. ASRS data were reviewed and a simulation experiment was performed to evaluate and quantify the hypotheses

Compressor station facility failure modes: causes, taxonomy and effects

This report addresses the failure modes of compressor stations as key facilities of gas transmission networks. This is done by finding possible failure causes, establishing a taxonomy and identifying possible effects. Given the interest of this study to analyse and identify potential critical facilities in gas transmission networks, and their possible impact on energy security, loss of capacity (partial or total) has been identified as the effect of interest of the different failures. Probabilistic results provided are unavailability, expected number of failures per year, downtime and average downtime.JRC.C.3-Energy Security, Distribution and Market

Study of Major-Accident Risk Assessment Techniques in the Environmental Impact Assessment Process

[EN] Design, implementation, and operation of any project are affected by the environment where it is developed; at the same time, the project will influence the environment, since during its life cycle it can cause an impact on it. This impact can lead to social, economic, and environmental results. Directive 2014/52/EU, on the assessment of the effects of certain public and private projects on the environment, reflects the obligation for the project promoter to consider, in the Environmental Impact Study (EIS) of the project, their vulnerability (exposure and resilience) to major accidents and/or disasters, evaluating both the risk and their effects on the environment, in case these major accidents and/or disasters appear. The IEC 31.010:2019 Risk management-Risk assessment techniques standard defines 45 risk appreciation techniques that are useful when analysing the risks, in general. The objective of this paper is to review these 45 techniques, and establish which ones can be used for the assessment of accidents or disasters required in the specific environmental impact assessment process to accomplish with the regulation. After the revision, the authors propose five risks appreciation techniques that could be used for the assessment of major accidents and or disasters in projects for which EIA has to be carried out.The APC was funded by Universitat Politecnica de Valencia, Spain.Fuentes Bargues, JL.; Bastante Ceca, MJ.; Ferrer-Gisbert, P.; González-Cruz, M. (2020). Study of Major-Accident Risk Assessment Techniques in the Environmental Impact Assessment Process. Sustainability. 12(14):1-16. https://doi.org/10.3390/su12145770S1161214Gimenez, C., Sierra, V., & Rodon, J. (2012). Sustainable operations: Their impact on the triple bottom line. International Journal of Production Economics, 140(1), 149-159. doi:10.1016/j.ijpe.2012.01.035Kleindorfer, P. R., Singhal, K., & Wassenhove, L. N. (2009). Sustainable Operations Management. Production and Operations Management, 14(4), 482-492. doi:10.1111/j.1937-5956.2005.tb00235.xZhang, X., Wu, Y., & Shen, L. (2015). Embedding «green» in project-based organizations: the way ahead in the construction industry? Journal of Cleaner Production, 107, 420-427. doi:10.1016/j.jclepro.2014.10.024Chofreh, A. G., Goni, F. A., Malik, M. N., Khan, H. H., & Klemeš, J. J. (2019). The imperative and research directions of sustainable project management. Journal of Cleaner Production, 238, 117810. doi:10.1016/j.jclepro.2019.117810Armenia, S., Dangelico, R. M., Nonino, F., & Pompei, A. (2019). Sustainable Project Management: A Conceptualization-Oriented Review and a Framework Proposal for Future Studies. Sustainability, 11(9), 2664. doi:10.3390/su11092664Silvius, A. J. G., & Schipper, R. P. J. (2014). Sustainability in project management: A literature review and impact analysis. Social Business, 4(1), 63-96. doi:10.1362/204440814x13948909253866Dong, N., Fu, Y., Xiong, F., Li, L., Ao, Y., & Martek, I. (2019). Sustainable Construction Project Management (SCPM) Evaluation—A Case Study of the Guangzhou Metro Line-7, PR China. Sustainability, 11(20), 5731. doi:10.3390/su11205731Gilbert Silvius, A. J., Kampinga, M., Paniagua, S., & Mooi, H. (2017). Considering sustainability in project management decision making; An investigation using Q-methodology. International Journal of Project Management, 35(6), 1133-1150. doi:10.1016/j.ijproman.2017.01.011Demidova, O., & Cherp, A. (2005). Risk assessment for improved treatment of health considerations in EIA. Environmental Impact Assessment Review, 25(4), 411-429. doi:10.1016/j.eiar.2004.09.008Zeleňáková, M., & Zvijáková, L. (2017). Risk analysis within environmental impact assessment of proposed construction activity. Environmental Impact Assessment Review, 62, 76-89. doi:10.1016/j.eiar.2016.10.003Marconi, M., Marilungo, E., Papetti, A., & Germani, M. (2017). Traceability as a means to investigate supply chain sustainability: the real case of a leather shoe supply chain. International Journal of Production Research, 55(22), 6638-6652. doi:10.1080/00207543.2017.1332437Torres-Ruiz, A., & Ravindran, A. R. (2018). Multiple criteria framework for the sustainability risk assessment of a supplier portfolio. Journal of Cleaner Production, 172, 4478-4493. doi:10.1016/j.jclepro.2017.10.304Oliveira, F. N. de, Leiras, A., & Ceryno, P. (2019). Environmental risk management in supply chains: A taxonomy, a framework and future research avenues. Journal of Cleaner Production, 232, 1257-1271. doi:10.1016/j.jclepro.2019.06.032Chen, Z., Li, H., Ren, H., Xu, Q., & Hong, J. (2011). A total environmental risk assessment model for international hub airports. International Journal of Project Management, 29(7), 856-866. doi:10.1016/j.ijproman.2011.03.004Zeleňáková, M., Labant, S., Zvijáková, L., Weiss, E., Čepelová, H., Weiss, R., … Minďaš, J. (2020). Methodology for environmental assessment of proposed activity using risk analysis. Environmental Impact Assessment Review, 80, 106333. doi:10.1016/j.eiar.2019.106333Tixier, J., Dusserre, G., Salvi, O., & Gaston, D. (2002). Review of 62 risk analysis methodologies of industrial plants. Journal of Loss Prevention in the Process Industries, 15(4), 291-303. doi:10.1016/s0950-4230(02)00008-6Marhavilas, P. K., Koulouriotis, D., & Gemeni, V. (2011). Risk analysis and assessment methodologies in the work sites: On a review, classification and comparative study of the scientific literature of the period 2000–2009. Journal of Loss Prevention in the Process Industries, 24(5), 477-523. doi:10.1016/j.jlp.2011.03.004Zheng, X., & Liu, M. (2009). An overview of accident forecasting methodologies. 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What Happened, and Why: Toward an Understanding of Human Error Based on Automated Analyses of Incident Reports

The objective of the Aviation System Monitoring and Modeling (ASMM) project of NASA s Aviation Safety and Security Program was to develop technologies that will enable proactive management of safety risk, which entails identifying the precursor events and conditions that foreshadow most accidents. This presents a particular challenge in the aviation system where people are key components and human error is frequently cited as a major contributing factor or cause of incidents and accidents. In the aviation "world", information about what happened can be extracted from quantitative data sources, but the experiential account of the incident reporter is the best available source of information about why an incident happened. This report describes a conceptual model and an approach to automated analyses of textual data sources for the subjective perspective of the reporter of the incident to aid in understanding why an incident occurred. It explores a first-generation process for routinely searching large databases of textual reports of aviation incident or accidents, and reliably analyzing them for causal factors of human behavior (the why of an incident). We have defined a generic structure of information that is postulated to be a sound basis for defining similarities between aviation incidents. Based on this structure, we have introduced the simplifying structure, which we call the Scenario as a pragmatic guide for identifying similarities of what happened based on the objective parameters that define the Context and the Outcome of a Scenario. We believe that it will be possible to design an automated analysis process guided by the structure of the Scenario that will aid aviation-safety experts to understand the systemic issues that are conducive to human error

Modelling airport surface safety: a framework for a holistic airport safety management

Airports are complex systems involving the continuous interaction of human operators with the physical infrastructure, technology and procedures to ensure the safe and efficient conduct of flights. From an operational perspective, airport surface operations (i.e. runway and taxiway operations) require the interaction of five main stakeholders (i.e. crew or pilots, air traffic control, airport operator, ground handling and regulator) both to facilitate the ground movement of aircraft and vehicles, and to maintain the surface in a working condition. The complexity of these operations makes the runway and taxiway system vulnerable and presents a risk of failure with the consequent potential for the occurrence of accidents. Therefore, the development and implementation of an effective Safety Management System (SMS) are required to ensure the highest level of safety for surface operations. A SMS is a systematic approach to managing safety based on the four cornerstones of safety policy and objectives, risk management, assurance, and safety promotion. Although the International Civil Aviation Organisation (ICAO) provides the global legislative framework for SMS, the relevant regulations are still to be established at the national level with the consequence that practical guidance on the development and implementation of SMS is rare, and reliable tools to support SMS are lacking. The consequence of this is that the current approach to surface safety management is piecemeal and not integrated. Typically, a single accident and incident type is investigated from the perspective of an individual stakeholder with the consequence that resulting proposals for safety mitigation measures are biased and limited in terms of their impact. In addition, the industry is characterised by non-standardised data collection and investigation practices, insufficient or missing definitions, differing reporting levels, and a lack of a coherent and standardised structure for efficient coding and analysis of safety data. Since these shortcomings are a major barrier to the required holistic and integrated approach to safety management, this thesis addresses the four cornerstones of SMS and recommends major enhancements. In particular, a framework for a holistic airport surface safety management is proposed. The framework comprises the static airport architecture, a process model of surface operations, the determination of causal factors underlying failure modes of these operations, a macroscopic scenario tool and a functional relationship model. Safety data and other data sources feed the framework and a dedicated data pre-processing strategy ensures its validity. Unlike current airport surface safety management practices, the proposed framework assesses the safety of the operations of all relevant actors. Firstly, the airport architecture is modelled and the physical and functional variability of airports defined. Secondly, a process model of surface operations is developed, which captures the tasks of the stakeholders and their interactions with physical airport surface infrastructure. This model serves as a baseline model and guides the further development of the airport SMS. To manage the safety of surface operations, the causes of accidents and incidents must be identified and their impacts understood. To do so, a reference data set combining twelve databases from airlines, airport operators, Air Navigation Service Providers (ANSPs), ground handling companies and regulators is collected. Prior to its analysis, the data is assessed for its quality, and in particular, for its internal validity (i.e. precision), external validity (i.e. accuracy) and in terms of reporting levels. A novel external data validation framework is developed and each database is rated with a data quality index (DQI). In addition, recommendations for reporting systems and safety policies are given. Subsequently, the data is analysed for causal factors across stakeholders and the contribution of the individual actors are highlighted. For example, the analysis shows that the various stakeholders capture different occurrence types and underlying causal factors, often including information that is of potential use for another party. The analysis is complemented by interviews, observations and statistical analysis, and the results are summarised in a new taxonomy. This taxonomy is applicable to all relevant stakeholders and is recommended for operational safety risk management. After the airport surface operations have been modelled and the drivers to safety identified, the results are combined, resulting in a macroscopic scenario tool which supports the management of change (i.e. safety assurance), training and education, and safety communication (i.e. safety promotion) functions of the SMS. Finally, a structured framework to assess the functional relationship between airport surface accidents / incidents and their underlying causal factors is proposed and the system is quantified in terms of safety. Compared to the state-of-the-art safety assessments that are biased and limited in terms of their impact, the holistic approach to surface safety allows modelling the safety impact of each system component, their interactions and the entire airport surface system architecture. The framework for a holistic airport surface safety management developed in this thesis delivers a SMS standard for airports. The standard exceeds international requirements by standardizing the two SMS core functions (safety risk management and safety assurance) and integrating safety-relevant information across all relevant stakeholders. This allows a more effective use of safety information and provides an improved overview on, and prediction of, safety risks and ultimately improves the safety level of airports and their stakeholders. Furthermore, the methodology employed in this thesis is flexible and could be applied to all aspects of aviation SMS and system analysis.Open Acces