Bow-tie Analysis Research Articles

Customer-Driven Water Supply Systems: Synergizing System Reliability and Customer Satisfaction with Bowtie Analysis

Customer-Driven Water Supply Systems: Synergizing System Reliability and Customer Satisfaction with Bowtie Analysis

BowTie analysis of rooftop grid‐connected photovoltaic systems

AbstractWith the rapid growth of the worldwide photovoltaic (PV) installation, the number of fire incidents involving PV systems also shows an increasing trend. Several studies revealed that installing PV systems on the rooftop has introduced an additional fire risk to the building. Therefore, risk assessment is required to identify the possible cause of fire initiation involving PV systems and subsequently provide the solar industry with fire risk information regarding PV faults. A BowTie analysis of rooftop grid‐connected PV systems was conducted, where initiation of ignition was determined as the hazard and PV fires as the loss event. Four threats in the BowTie analysis were identified using fault tree analysis, that is, arc fault, ground fault, hotspot effect at PV modules, and overheating. Arc fault contributes the most to PV fire incidents, while poor installation of PV systems was found to be the primary underlying cause of all PV fault scenarios. The main factor is due to lack of fire safety knowledge and negligence behavior of the installers. The consequences of PV fires in the BowTie diagram were investigated from the event tree analysis. Twelve possible outcomes were identified and regrouped to five consequences, that is, respiratory poisons, electrical shock, fall from heights, asset damage, and fire propagation. The evaluation of the consequences of PV fire shows that electrical shock poses a very high risk to the surrounding people, including firefighters. Additional measures are proposed to reduce the impact of electric shock.

Visualizing primary cooling system risks with bowtie diagram for RSG GAS operator guidance

AbstractThe G.A. Siwabessy Multipurpose Reactor (RSG GAS) is a pool‐type research reactor. When the reactor operates, the heat released in the core is removed by the primary cooling system. It is necessary to evaluate this system, because failure can cause worst events such as the melting of reactor fuel and the release of radioactivity to the environment. Due to the possibility of radioactive material releases, safety issues are important to be evaluated. Several studies using event tree analysis (ETA), fuzzy fault tree analysis (FFTA) describe the results quantitatively. The varied educations of operators will provide various responses to quantitative results, and a need to create qualitative results that are simple and easy to understand using bowtie analysis that visualizes the risk scenario. Failure of this system causes loss of coolant accident (LOCA) and loss of flow accident (LOFA). The results show that the relationship between the consequences and causes of the risk occurrence LOCA and LOFA, and the controls used to prevent and reduce the hazard based on safety and emergency system at RSG GAS, can be depicted in a bowtie diagram. The bowtie diagram is simple and easy for an RSG GAS operator to carry out their duties and increase awareness regarding the safety of reactor operations.

Critical Analysis of Train Derailments in Canada through Process Safety Techniques and Insights into Enhanced Safety Management Systems

Canada’s rail transportation network is a critical part of Canada’s integrated supply chain which connects industries, consumers, and resource sectors to ports on the Atlantic and Pacific coasts. One transportation activity that is essential to most industries, especially oil and manufacturing, is the rail transport of dangerous goods (DG). Although rail transportation of DG is beneficial to Canada’s economy, not paying attention to the safe transportation of these types of goods can have irreparable effects on the economy, human lives, and the environment. Recent rail accidents, such as Lake Wabamun in 2005 and Lac-Mégantic in 2013, have shown that there is still room to increase the safety of transportation of DG by rail through improving railways’ safety management systems (SMS). As a result, investigations to increase the safety of rail transportation of DG have been started. This work is part of these initiatives focusing on enhancing railways’ SMS, particularly DG main-track train derailments. The current study applied detailed root cause analysis (RCA), the bow tie analysis (BTA), and incident databases to identify the main causes and consequences of these types of accidents (2007–2017). Then, the relationship between these factors and gaps in SMS elements were identified and the frequency of each factor was investigated. The results showed that the main gaps are related to process and equipment integrity, incident investigation, and company standards, codes, and regulations. Furthermore, some useful recommendations are presented to improve the management of each SMS element and reduce these gaps.

Fuzzy Bayesian estimation and consequence modeling of the domino effects of methanol storage tanks

In this study, a fuzzy Bayesian network (FBN) approach was proposed to analyze the domino effects of pool fire. Failure probabilities were calculated using triangular fuzzy numbers, the combined center of area (CoA)/sum-product method and the BN approach. Consequence modeling, probit equations and leaky–noisy-OR (L-NOR) gates were used to analyze the domino effects, and modify conditional probability tables (CPTs). Methanol storage tanks were selected to confirm the practical feasibility of the suggested method. The domino probability using bow-tie analysis (BTA) and FBN in the first and second levels was compared, and the ratio of variation was used for sensitivity analysis. Probability of the domino effect in the first and second levels (FBN) was 0.0071472631 and 0.0090630640, respectively. The results confirm this method is a suitable tool for analyzing the domino effects and that using FBN and L-NOR gate is a good way to assess the reliability of tanks.

Cyber Physical Systems Security for Maritime Assets

The integration of IT, OT, and human factor elements in maritime assets is critical for their efficient and safe operation and performance. This integration defines cyber physical systems and involves a number of IT and OT components, systems, and functions that involve multiple and diverse communication paths that are technologically and operationally evolving along with credible cyber security threats. These cyber security threats and risks as well as a number of known security breach scenarios are described in this paper to highlight the evolution of cyber physical systems in the maritime domain and their emerging cyber vulnerabilities. Current industry and governmental standards and directives related to cyber security in the maritime domain attempt to enforce the regulatory compliance and reinforce asset cyber security integrity for optimum and safe performance with limited focus, however, in the existing OT infrastructure and systems. The use of outside-of-the-maritime industry security risk assessment tools and processes, such the API STD 780 Security Risk Assessment (SRA) and the Bow Tie Analysis methodologies, can assist the asset owner to assess its IT and OT infrastructure for cyber and physical security vulnerabilities and allocate proper mitigation measures assuming their similarities to ICS infrastructure. The application of cyber security controls deriving from the adaptation of the NIST CSF and the MITRE ATT&CK Threat Model can further increase the cyber security integrity of maritime assets, assuming they are periodically evaluated for their effectiveness and applicability. Finally, the improvement in communication among stakeholders, the increase in operational and technical cyber and physical security resiliency, and the increase in operational cyber security awareness would be further increased for maritime assets by the convergence of the distinct physical and cyber security functions as well as onshore- and offshore-based cyber infrastructure of maritime companies and asset owners.

The risk assessment of a crude oil pipeline using fuzzy and bayesian based bow-tie analysis

Cross country pipelines are one of the major modes of transportation of petroleum products. Due to external and internal factors, the failure probability of pipeline is increasing over the past decades. The failure of pipelines can cause fires, which can result in environmental damage, loss of materials and further resulting into casualties. Effective risk assessment is vital to prevent and mitigate such potential incidents. In this work, an efficient tool that makes use of Bayesian approach along with Bow-tie analysis is used to obtain the failure frequencies of all the identified causes that may lead to failure of the selected pipeline located in Kerala, India. Bayesian networks can perform effective dynamic risk analysis by considering the conditional dependencies between various basic events leading to pipeline failure. The fuzzy logic and expert elicitation method are incorporated to determine the prior failure frequencies of all the identified causes of pipeline failure. The effectiveness of Bayesian network in performing forward analysis to determine the probabilities of pipeline failure consequences is demonstrated. This study also identifies the weak links associated with the occurrence of particular consequences, so that adequate measures can be taken to rectify them.

Application of the bow-tie analysis technique in quantitative risk assessment of gas condensate storage considering domino effects

Application of the bow-tie analysis technique in quantitative risk assessment of gas condensate storage considering domino effects

Human resource risk control through COVID-19 risk assessment in Indonesian manufacturing

The COVID-19 outbreak that began at the end of 2019 brought a crisis impact on the health sector and other sectors such as the economy, social and politics. Human resource problems that emerged as a result of the pandemic made every company strive to protect employee safety. The food and beverage sector is one of the industries maintained to continue operating despite the large-scale social restrictions imposed in several regions, including an instant food company in East Java. This study aims to identify and determine human resource risk control to support employee productivity during the COVID-19 pandemic. This research used qualitative data based obtained through interviews, observation, and documentation. The method in this study used a combination of Failure Mode Effect Analysis (FMEA) and Bow Tie to identify, measure, and anticipate the risk of COVID-19 transmission in the company. The output result of the Failure Mode Effect Analysis (FMEA) method is the Risk Priority Number (RPN) score. The three activities with the highest RPN value were health services at the polyclinic, employee meal activities in the canteen, and activities inside and outside the factory. This analysis's results were continued by using the Bow Tie method to identify the causes, prevention, impact, and recovery of these risks. Bow Tie analysis results formed the basis for the preparation of Corrective Action and Preventive Action (CAPA). The risk control of human resources is focused on increasing employee productivity by reducing days lost due to labor shortages. In the end, the study results are expected to become recommendations in the evaluation of risk control and preventive measures for COVID-19 in manufacturing companies.

Pandemic risk management; protecting people while ensuring business continuity

The COVID‐19 pandemic swept across the globe in the latter half of 2019, throughout 2020 and into 2021. In response, many organizations implemented work from home policies, while others stopped operations entirely in an effort to limit the spread throughout their workforce and supporting communities. This containment strategy was not universally viable; long‐term shutdowns impacted the economic viability of companies, and some industries were designated as an “essential service” and thus continued operations. These employers faced the proposition of balancing the needs of the business and the community with a continued responsibility to provide a safe workplace for employees. This paper demonstrates how the application of common risk management methodologies, such as bowtie analysis combined with an appropriate assurance and verification process (e.g., the lines of defense model), can help the risks associated with a resumption or continuation of in‐person operations in a pandemic to be better understood and ensure the measures in place to manage said risk are appropriate and effective.

Corruption Risk Analysis at the Project Planning Stage in the Iraqi Construction Sector using the Bowtie Methodology

In this paper, the bowtie method was utilized by a multidisciplinary team in the Federal Board of Supreme Audit (FBSA)for the purpose of managing corruption risks threatening the Iraqi construction sector. Corruption in Iraq is a widespread phenomenon that threatens to degrade society and halt the wheel of economic development, so it must be reduced through appropriate strategies. A total of eleven corruption risks have been identified by the involved parties in corruption and were analyzed by using probability and impact matrix and their priority has been ranked. Bowtie analysis was conducted on four factors with high score risk in causing corruption in the planning stage. The number and effectiveness of the existing proactive measures to prevent threats from resulting in corruption and were examined for each threat.

Risk Assessment of Petroleum Products Loading Arm by BTA Technique

Background: Loading of petroleum products consists of several parts, of which the arm platform section is known to be the source of most accidents. Objectives: Therefore, this study was done to evaluate the risk of arm loading platforms using the bow-tie analysis (BTA) technique to identify the causes and the probability of occurrence of hazardous events. Methods: In this study, we first identified the risks of the loading arm using the expert’s judgment. The risk of overflow is considered as the top event. Then, the basic events were identified by the fault tree analysis (FTA), and the possible consequences of the top event were predicted using the event tree. Next, using the computational equations, the probability of spillover and its consequences were calculated. The path of the risk event from the causal phase to the consequent phase was also illustrated by sketching the structure of the BTA. Results: A total of 14 basic events and 8 intermediate events were involved in the occurrence of the top event, and 5 consequences were identified for the risk of spillover. The probability of the top event occurring was calculated to be 3.12 × 10-7. Conclusions: According to the results of this study, tank overflow is one of the most important hazards in the loading arm section.

Preliminary case report study of training and support needed to conduct bowtie analysis in healthcare

BackgroundThere is limited engagement in healthcare with the kinds of proactive approaches to risk assessment used in other industries. Bowtie analysis (BTA) has previously been shown to have potential as...

A novel risk evaluation method for fire and explosion accidents in oil depots using bow-tie analysis and risk matrix analysis method based on cloud model theory

Due to the catastrophic impact of Fire and Explosion Accidents in Oil Depots (FEAOD), the prevention and control of such accidents is the most critical part of risk management. In this study, a Bow-tie (BT) model was built for FEAOD, while a quantitative risk assessment and consequence assessment was performed in conjunction with the risk matrix. Then, due to the uncertainty and ambiguity of the probability data of Basic Events (BEs) during the expert elicitation process, this study creatively proposed a Cloud-Analytic Hierarchy Process (Cloud-AHP) algorithm and Group Cloud Decision-Making (GCDM) algorithm based on the Fuzzy Cloud Membership Function (FCMF). Finally, combined with the probability estimation algorithm and the sensitivity analysis, a novel risk quantitative assessment algorithm for a BT model was developed based on Cloud Model (CM) theory. The discretion, ambiguity, and randomness were considered during the evaluation process, and a more scientific assessment fusion result of Decision makers (DMs) was obtained, while the Delphi iteration process further reduced personal errors. A case study of an oil depot in Dalian was investigated. The results showed that the proposed method more accurately identified the weak links in the safety system, providing a theoretical basis for the risk prevention and control.

Risk Assessment of the Large-Scale Hydrogen Storage in Salt Caverns

Salt caverns are accepted as an ideal solution for high-pressure hydrogen storage. As well as considering the numerous benefits of the realization of underground hydrogen storage (UHS), such as high energy densities, low leakage rates and big storage volumes, risk analysis of UHS is a required step for assessing the suitability of this technology. In this work, a preliminary quantitative risk assessment (QRA) was performed by starting from the worst-case scenario: rupture at the ground of the riser pipe from the salt cavern to the ground. The influence of hydrogen contamination by bacterial metabolism was studied, considering the composition of the gas contained in the salt caverns as time variable. A bow-tie analysis was used to highlight all the possible causes (basic events) as well as the outcomes (jet fire, unconfined vapor cloud explosion (UVCE), toxic chemical release), and then, consequence and risk analyses were performed. The results showed that a UVCE is the most frequent outcome, but its effect zone decreases with time due to the hydrogen contamination and the higher contents of methane and hydrogen sulfide.

Corrosion risk assessment using adaptive bow-tie (ABT) analysis

Corrosion is a major threat to safety and asset integrity in oil and gas production and processing facilities. This paper proposes a simple, yet practical model for quantitative corrosion risk assessment from safety and economic perspectives. This includes an Adaptive Bow-Tie (ABT) model for the corrosion risk with a specific focus on microbiologically influenced corrosion, along with corrosion economic risk profile. The ABT model is logically tested using corrosion science and statistically verified using a pipeline corrosion database, including cases of corrosion-induced failures. The ABT model also provides opportunities to run root-cause contribution (RCC) analysis and to estimate the probability of corrosion, corrosion-induced failures, and highly probable sequences leading to failure. The model application is demonstrated using a crude oil transportation pipeline system. The study identifies and quantifies parameters that helps to prioritize the actions needed to prevent and control corrosion and avoid failures. The proposed model can serve as an important mechanism to identify, assess, and manage corrosion threat to an asset.

Risk Assessment and Sustainability of Wastewater Treatment Plant Operation

Water and water management, which also includes wastewater treatment plants (WWTPs), are considered essential elements critical infrastructure. A disruption of their operation can result in the discharge of wastewater into the environment without having been adequately treated. This can cause health problems, contamination of soil, groundwater and surface water, etc. In order to provide operational safety and sustainability of WWTP operation, it is necessary to establish protection against potential risk activation, together with risk minimization and enhanced preparedness to address the risks. The article deals with the application of risk management stages on the selected object of the municipal WWTP facility in the form of a case study. The risk identification phase consisted of the identification of assets and risks. The assets were grouped together due to the complexity of the WWTP operation. A combination of methods, a safety audit, a checklist and semi-structured interviews were used to identify the risks in three iterations. A risk register was created as a result of the risk identification phase. Subsequently, a risk analysis was carried out, in which the scenarios of the risk impact on the assets were examined, the index levels of probability and impacts were determined, and the risk estimate was performed. The Bowtie Analysis Method was used to illustrate the causes and consequences for one of the critical risks. The result of the study is the risk evaluation identified undesirable and unacceptable risks for which risk management methods were proposed

Money flow network among firms\u2019 accounts in a regional bank of Japan

In this study, we investigate the flow of money among bank accounts possessed by firms in a region by employing an exhaustive list of all the bank transfers in a regional bank in Japan, to clarify how the network of money flow is related to the economic activities of the firms. The network statistics and structures are examined and shown to be similar to those of a nationwide production network. Specifically, the bowtie analysis indicates what we refer to as a “walnut” structure with core and upstream/downstream components. To quantify the location of an individual account in the network, we used the Hodge decomposition method and found that the Hodge potential of the account has a significant correlation to its position in the bowtie structure as well as to its net flow of incoming and outgoing money and links, namely the net demand/supply of individual accounts. In addition, we used non-negative matrix factorization to identify important factors underlying the entire flow of money; it can be interpreted that these factors are associated with regional economic activities. One factor has a feature whereby the remittance source is localized to the largest city in the region, while the destination is scattered. The other factors correspond to the economic activities specific to different local places. This study serves as a basis for further investigation on the relationship between money flow and economic activities of firms.

Methodology for Evaluating Risk of Visual Inspection Tasks of Aircraft Engine Blades

Risk assessment methods are widely used in aviation, but have not been demonstrated for visual inspection of aircraft engine components. The complexity in this field arises from the variety of defect types and the different manifestation thereof with each level of disassembly. A new risk framework was designed to include contextual factors. Those factors were identified using Bowtie analysis to be criticality, severity, and detectability. This framework yields a risk metric that describes the extent to which a defect might stay undetected during the inspection task, and result in adverse safety outcomes. A simplification of the framework provides a method for go/no-go decision-making. The results of the study reveal that the defect detectability is highly dependent on specific views of the blade, and the risk can be quantified. Defects that involve material separation or removal such as scratches, tip rub, nicks, tears, cracks, and breaking, are best shown in airfoil views. Defects that involve material deformation and change of shape, such as tip curl, dents on the leading edges, bents, and battered blades, have lower risk if edge views can be provided. This research proposes that many risk assessments may be reduced to three factors: consequence, likelihood, and a cofactor. The latter represents the industrial context, and can comprise multiple sub-factors that are application-specific. A method has been devised, including appropriate scales, for the inclusion of these into the risk assessment.

A Risk Assessment Framework Proposal Based on Bow-Tie Analysis for Medical Image Diagnosis Sharing within Telemedicine.

The purpose of this paper is to propose a framework for cybersecurity risk management in telemedicine. The framework, which uses a bow-tie approach for medical image diagnosis sharing, allows the identification, analysis, and assessment of risks, considering the ISO/TS 13131:2014 recommendations. The bow-tie method combines fault tree analysis (FTA) and event tree analysis (ETA). The literature review supported the identification of the main causes and forms of control associated with cybersecurity risks in telemedicine. The main finding of this paper is that it is possible, through a structured model, to manage risks and avoid losses for everyone involved in the process of exchanging medical image information through telemedicine services. Through the framework, those responsible for the telemedicine services can identify potential risks in cybersecurity and act preventively, recognizing the causes even as, in a mitigating way, identifying viable controls and prioritizing investments. Despite the existence of many studies on cybersecurity, the paper provides theoretical contributions to studies on cybersecurity risks and features a new methodological approach, which incorporates both causes and consequences of the incident scenario.