scholarly journals On the Use of the Hybrid Causal Logic Methodology in Ship Collision Risk Assessment

2020 ◽  
Vol 8 (7) ◽  
pp. 485 ◽  
Author(s):  
Tengfei Wang ◽  
Qing Wu ◽  
Mihai A. Diaconeasa ◽  
Xinping Yan ◽  
Ali Mosleh
Keyword(s):  
Risk Assessment ◽  
Bayesian Networks ◽  
Human Behavior ◽  
Human Error ◽  
Risk Identification ◽  
System Level ◽  
Sequence Diagrams ◽  
Fault Trees ◽  
Ship Collision ◽  
Causal Logic

A ship collision accident is one of the most dangerous and common types of maritime accidents. Traditional probabilistic risk assessment (PRA) of ship collision accidents is a methodology that can be adopted to ensure maritime safety. Nevertheless, a need for better approaches to model human behavior, such as risk identification, communication, and decision-making, has been identified. Such advanced PRA methods require a more explicit way of taking human factors into consideration than the traditional risk assessment methods. Hybrid causal logic (HCL) is an advanced PRA method due to its unique three-level framework that includes event sequence diagrams, fault trees, and Bayesian networks, which makes it suitable for modeling human behavior that is important to ship collision accidents. This paper discusses the applicability of the HCL methodology for the ship collision accident. Firstly, the event sequences of typical ship collision accidents are summarized based on the study of 50 accident investigation reports. Then, fault trees for mechanical failure events and the Bayesian networks for human error events are constructed to analyze the events in a structured way at a more detailed level. Finally, the three main end-state types of ship collision avoidance scenario have been quantified. The result of the probability of a ship collision accident is verified by estimating the annual frequency of collision accidents in the Singapore Strait. Comparing with the historical data, the estimation results are quite near to the real case. By taking advantage of the HCL methodology, the modeling of ship collision scenarios can be carried out at a deep logical level. At the same time, it is possible to combine a detailed analysis of various primary events with a comprehensive analysis at the system level.

scholarly journals Application of an Enhanced Version of Recursive Operability Analysis for Combustible Dusts Risk Assessment

2020 ◽  
Vol 17 (9) ◽  
pp. 3078
Author(s):  
Marco Barozzi ◽  
Sabrina Copelli ◽  
Martina Silvia Scotton ◽  
Vincenzo Torretta
Keyword(s):  
Risk Assessment ◽  
Corn Starch ◽  
Logical Structure ◽  
Critical Issue ◽  
Sequence Diagrams ◽  
Chemical Safety ◽  
Fault Trees ◽  
Sugar Refinery ◽  
Dust Explosions ◽  
Application Fields

Organic dust explosions were and are still today a critical issue in the food, pharmaceutical, and fine chemical industry. Materials such as flour, corn starch, sugar and APIs represent a cause of severe accidents. In this framework, we investigated a modified version of Recursive Operability Analysis−Incidental Sequence Diagrams (ROA–ISD), called ROA Plus−ISD, specifically tailored to describe industrial processes involving organic combustible dusts. Compared to more classical techniques such as Hazard and Operability (HazOp), ROA−ISD allows for a direct generation of fault trees, providing a useful tool to connect Qualitative with Quantitative Risk Analysis (QRA). ROA Plus−ISD is very similar to ROA−Cause Consequence Diagrams (CCD), which has already proven to be an effective tool to perform both risk assessment on existing plants and reconstructing already occurred accidents, given its logical structure and width of the application fields. In this work, we modified specific parts of the standard ROA−CCD method: (1) the Failure Mode and Operability Analysis (FMEA) database has been structured in order to retrieve the well-known explosion pentagon (for dusts) and all the instruments, devices, apparatuses and controllers typical of industries which process organic dusts; (2) a new comprehensive list of process variables has been compiled. In this way, it is possible to tailor the information required for the generation of the fault trees concerning top events involving mainly dust explosions and fires. This method has been implemented in order to reconstruct the dynamics of the February 2008 Imperial Sugar refinery plant accident (Port Wentworth, GA, USA). Results demonstrated the applicability of the enhanced method by highlighting the criticalities of the process already showed by a previously detailed reconstruction performed by the Chemical Safety Board.

scholarly journals Quantitative Ship Collision Frequency Estimation Models: A Review

2021 ◽  
Vol 9 (5) ◽  
pp. 533
Author(s):  
Mirko Čorić ◽  
Sadko Mandžuka ◽  
Anita Gudelj ◽  
Zvonimir Lušić
Keyword(s):  
Risk Assessment ◽  
Collision Frequency ◽  
Frequency Estimation ◽  
Cost Effective ◽  
Future Improvement ◽  
Ship Collision ◽  
Estimation Models

Ship collisions are one of the most common types of maritime accidents. Assessing the frequency and probability of ship collisions is of great importance as it provides a cost-effective and practical way to mitigate risk. In this paper, we present a review of quantitative ship collision frequency estimation models for waterway risk assessment, accompanied by a classification of the models and a description of their main modelling characteristics. Models addressing the macroscopic perspective in the estimation of ship collision frequency on waterways are reviewed in this paper with a total of 29 models. We extend the existing classification methodology and group the collected models accordingly. Special attention is given to the criteria used to detect potential ship collision candidates, as well as to causation probability and the correlation of models with real ship collision statistics. Limitations of the existing models and future improvement possibilities are discussed. The paper can be used as a guide to understanding current achievements in this field.

Identification of Human Errors During Early Design Stage Functional Failure Analysis

2018 ◽  
Author(s):  
Lukman Irshad ◽  
Salman Ahmed ◽  
Onan Demirel ◽  
Irem Y. Tumer
Keyword(s):  
Failure Analysis ◽  
Human Error ◽  
System Level ◽  
Design Stage ◽  
Human Factors Engineering ◽  
Human Errors ◽  
Functional Failure ◽  
Early Design ◽  
Early Design Stage ◽  
Early Design Stages

Detection of potential failures and human error and their propagation over time at an early design stage will help prevent system failures and adverse accidents. Hence, there is a need for a failure analysis technique that will assess potential functional/component failures, human errors, and how they propagate to affect the system overall. Prior work has introduced FFIP (Functional Failure Identification and Propagation), which considers both human error and mechanical failures and their propagation at a system level at early design stages. However, it fails to consider the specific human actions (expected or unexpected) that contributed towards the human error. In this paper, we propose a method to expand FFIP to include human action/error propagation during failure analysis so a designer can address the human errors using human factors engineering principals at early design stages. To explore the capabilities of the proposed method, it is applied to a hold-up tank example and the results are coupled with Digital Human Modeling to demonstrate how designers can use these tools to make better design decisions before any design commitments are made.

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