Fault Tree Research Articles

Risk Analysis of Hydrogen Leakage at Hydrogen Producing and Refuelling Integrated Station

Hydrogen energy is considered the most promising clean energy in the 21st century, so hydrogen refuelling stations (HRSs) are crucial facilities for storage and supply. HRSs might experience hydrogen leakage (HL) incidents during their operation. Hydrogen-producing and refuelling integrated stations (HPRISs) could make thermal risks even more prominent than those of HRSs. Considering HL as the target in the HPRIS, through the method of fault tree analysis (FTA) and analytic hierarchy process (AHP), the importance degree and probability importance were appraised to obtain indicators for the weight of accident level. In addition, the influence of HL from storage tanks under ambient wind conditions was analysed using the specific model. Based upon risk analysis of FTA, AHP, and ALOHA, preventive measures were obtained. Through an evaluation of importance degree and probability importance, it was concluded that misoperation, material ageing, inadequate maintenance, and improper design were four dominant factors contributing to accidents. Furthermore, four crucial factors contributing to accidents were identified by the analysis of the weight of the HL event with AHP: heat, misoperation, inadequate maintenance, and valve failure. Combining the causal analysis of FTA with the expert weights from AHP enables the identification of additional crucial factors in risk. The extent of the hazard increased with wind speed, and yet wind direction did not distinctly affect the extent of the risk. However, this did affect the direction in which the risk spreads. It is extremely vital to rationally plan upwind and downwind buildings or structures, equipment, and facilities. The available findings of the research could provide theoretical guidance for the applications and promotion of hydrogen energy in China, as well as for the proactive safety and feasible emergency management of HPRISs.

Risk analysis of mechanical cross passage construction using work breakdown and fault tree

A subway cross passage is a connecting aisle between main tunnels. Owing to its narrow construction site, it is difficult to implement safety measures, and intensive construction techniques are often required. With the development of technology, the mechanical cross-passage technology has emerged. To address the risk problem of mechanical cross-passage construction, the construction process was systematically decomposed based on the work breakdown structure (WBS), and a fault tree of each construction process was established for qualitative analysis. Various factors leading to construction risks have been identified, such as head sinking of the excavation machine, spiral machine gushing, excavation deviation from axis, excavation surface soil instability, and ground deformation, and corresponding risk response measures have been proposed. The targeted measures were applied to the mechanical construction of Qingdao Subway Line 8, and the successful completion of the cross-passage verified the applicability of the risk analysis and the effectiveness of the response measures.

Quality Control on Packing Process of Willarine Margarine Products at PT. XYZ with FMEA and FTA Methods

PT. XYZ is a company engaged in the crude palm oil processing sector, one of which is willarine margarine which is exported to various countries. In maintaining global competitiveness, the company strives to produce high-quality products. However, in practice there are still obstacles that need to be overcome. One of them is during the packing process there are three types of product defects identified, namely leakage in the pouch packaging, lack of margarine volume, and damage to the pouch carton. So this research uses the FMEA (Failure Mode and Effect Analysis) method used to determine and transfer the severity, occurrence, and detection levels, so that it is obtained with the highest total RPN, namely leaky pouch packaging of 904, and FTA (Fault Tree Analysis) as a clue with the root of the problem tree, so that it is known that the root causes are lack of rest time, lack of supervision, no concern for the importance of track setting instructions, and no worker concern for cleanliness. After the results are known, improvement proposals are given, namely providing sufficient rest time and always rechecking, providing track setting instructions, and always doing routine cleaning at the beginning and end of work.

Analysis of Kazakhstan Oil Shale Deposits in Accordance with Resource Estimation Practices for Consideration of Potential Shale Oil Reserves

Most oil shale deposits in Kazakhstan were estimated without detailed calculations of the grade and tonnages and included low confidence categories, i.e., Inferred, Off-Balance, and Non-Economic oil shales, on which cannot be given any oil reserves. An analysis of Kazakhstan oil shale deposits in accordance with resource estimation practices for consideration of potential shale oil tonnages has been produced. The developed methodology considers extraction and processing recoveries of conventional and unconventional mining methods. The methodology uses Monte Carlo modeling to estimate a range of oil content and oil recoveries and uses the event tree analysis to demonstrate how the initial oil shale material tonnages and grades go through various fault and success branches, considering probabilities distributions and estimating potential shale oil tones at the end. As a result, this estimation methodology has been validated by high-ranked resource category oil shale deposits, which demonstrated the range of potential shale oil in the range of 10.7–16.8 Mt at the 50% confidence level. The results will be used for further consideration in financial-economic feasibility studies, which must take into account operational and capital expenses, product sale prices and market, and social-environmental aspects.

Mechanism-Based Fire Hazard Chain Risk Assessment for Roll-On/Roll-Off Passenger Vessels Transporting Electric Vehicles: A Fault Tree–Fuzzy Bayesian Network Approach

Roll-on/Roll-off passenger vessels transporting electric vehicles (Ro-Ro EVs) face unique fire hazards, challenging traditional fire risk management strategies. This study integrates fault tree analysis (FTA) with Fuzzy Bayesian Network (FBN) to assess the fire risks of Ro-Ro EVs across the entire hazard chain. Given limited historical accident data, five experts familiar with the Shanghai Baoshan–Chongming ferry route refine fault tree models to visualize key fire hazard chain mechanisms and estimate risk probabilities. The FBN incorporates fault tree hierarchical structures, EV and Ro-Ro vessel-related risk factors, and applies a nine-level fuzzy scoring system to assess these risks. The FTA-FBN model offers a comprehensive framework for evaluating emerging fire risks specific to Ro-Ro EVs. Findings indicate that the highest risk occurs during the ignition phase. Primary triggers include external heat sources, improper vehicle securing, and vehicle collisions, leading to thermal runaway in lithium batteries. Failures in extinguishing and detecting lithium battery fires exacerbate fire spread. Effective fire compartmentalization and flammable material management are essential to prevent uncontrolled fires. Recommendations for fire prevention and control include shipboard battery level monitoring, charging restrictions, explosion-proof electrical installations, enhanced ventilation, lithium battery fire suppression systems, and vehicle securing.

A reliability, availability and maintainability (RAM) model for electromechanical components in hydropower plants

Abstract Hydropower generation is world best source of renewable energy and is continuously playing a tremendous job in energy requirement. To cope up with day by day increasing demand in electric energy, it is very essential to keep the hydropower plants in sustainable operational condition. To achieve this, the maintenance strategies based on Reliability, Availability and Maintainability (RAM) analysis play a pivotal role in sustainability of the hydropower plants. In our case study various critical components of hydropower plant were identified such as turbine, governor and generator. The causes and effects of various failures in the critical components were identified using Failure Mode Effect Analysis (FMEA) and Fault tree Analysis (FTA). The main role in the study is presenting a RAM model which helps in evaluating different levels of performance in Hydropower plant. Finally, the RAM parameters were evaluated and their outcomes were suggested to find the convenient maintenance intervals. The results of the proposed model revealed that the critical flaws of the hydrogenation process such as turbines, governors and generator should to be taken on priority basis to achieve the high level of reliability and safety. The results of present framework is to achieve the high level of reliability, hence, the main flaws of the hydrogenation process such as turbines, governors and generator should to be taken on priority basis. The proposed study could be valuable for improving the availability and safety of the critical equipment in hydropower plant. As a consequence, the results of present study could be beneficial for other hydro generating facilities to achieve the sustainable maintenance and operation programs in electricity generation systems.

Risk assessment and quality management in AIO based on CT-linac for nasopharyngeal carcinoma: An improved FMEA and FTA approach.

All-in-one radiotherapy workflow (AIO) is a novel one-stop solution that integrates the multiple conventional radiotherapy steps from simulation, contouring, planning, image guidance, beam delivery, and in vivo dosimetry into a single device (integrated computed tomography linac, the uRT-linac 506c), making the treatment process more efficient and convenient while reducing errors for cancer patients' initial radiotherapy. Despite its numerous advantages, the implementation of AIO faces challenges such as interdisciplinary coordination, software and hardware complexity, and reliance on artificial intelligence. To ensure its safety and effectiveness, it is necessary to conduct a risk assessment and identify appropriate quality management measures. To perform risk assessment on the AIO for nasopharyngeal carcinoma using failure mode and effects analysis (FMEA) and fault tree analysis (FTA), and to validate the effectiveness of the quality management measures. A flowchart was established for the AIO of nasopharyngeal carcinoma. FMEA analysis was conducted based on the flowchart, and quantitative assessments of each failure mode (FM) were performed to obtain (occurrence), (severity), and (Detectability). Weighted , , and were obtained using the similarity aggregation method (SAM), and the final risk priority number (RPN) was calculated by multiplying these values. The FMs were then evaluated into two groups based on whether quality management (QM) measures were implemented, and sorted by the RPN. Finally, FTA analysis was conducted on the highest-risk FMs identified through ranking. A flowchart of AIO for nasopharyngeal carcinoma was established, consisting of 5 main steps and 28 sub-steps. After FMEA analysis, 86 FMs were identified. In the group without implementing QM measures (QM-free group), the RPN of FMs ranged from 13.5 to 186.2, with a threshold of 94.6 for the top 20% RPN scores, resulting in 17 high-risk FMs. Additionally, 21 FMs had , with a cumulative total of 25 high-risk FMs after removing duplicates. In the group that implemented QM measures (QM group), the RPN of FMs ranged from 3.0 to 46.7, showing an overall decrease compared to the QM-free group. There was a statistically significant difference in RPN between the QM-free (55.80±38.40) and QM (16.17±10.99) groups (p<0.001), validating the effectiveness of the QM measures. Finally, FTA analysis was performed on the highest-risk step identified in the QM-free group with the highest RPN. The improved FMEA and FTA analysis methods are practical and operational, allowing for a comprehensive analysis of potential failures and risks in the AIO for nasopharyngeal carcinoma. They can effectively assist in establishing and evaluating QM standards for AIO of nasopharyngeal carcinoma. Moreover, the analytical methods and QM measures of this study can be effectively applied to AIO for tumors in other sites.

Relay Protection Device Reliability Assessment Through Radiation, Fault Injection and Fault Tree Analysis.

Relay protection devices must operate continuously throughout the year without anomalies. With the integration of advanced technology and process chips in secondary equipment, new risks need to be addressed to ensure the reliability of these relay protection devices. One such risk is the impact of α-particles inducing single event effects (SEEs) on the secondary equipment. To date, there has been limited assessment of the effects of α-particles on relay protection devices from a system perspective. This study evaluates the impact of SEE on relay protection devices through a Monte Carlo simulation, which is verified by α-particle radiation, fault injection, and fault tree analysis. It discusses the influence of SEEs with and without hardening measures in place. Additionally, this study examines the soft error probability when the target processor runs both general workloads and specific application workloads. The current research proposes a low-cost and effective reliability assessment method for secondary equipment considering single event effects. The findings provide new insights for the enhancement of future electric power grid systems.

Quantitative failure analysis for IoT systems: an integrated model-based framework

AbstractThe widespread adoption of Internet of Things (IoT) systems emphasises the need for dependable performance. However, challenges emerge due to the inadequacy of informal failure analysis models in evaluating the complex and distributed nature of IoT designs. These challenges can lead to inconsistencies, complicated system modifications, and extended development timelines. This paper presents a Model-Based Systems Engineering (MBSE) approach to create an integrated quantitative analysis framework for assessing the reliability of IoT systems. This approach simplifies the modelling and analysis of failure behaviours in IoT design, linking failure models to system design using standard engineering frameworks. Based on descriptions of IoT systems, the integrated approach establishes a traceability link between the system description and the analysable artefacts generated, such as stochastic Fault Tree Analysis (FTA) and Bayesian network (BN) models, which are essential for effective failure analysis of IoT systems. The approach demonstrates how to quantify system-level failures, identify and prioritise the weakest links in the design, and show how targeted modifications can improve the overall reliability of IoT systems. An illustrative case study on IoT is included to highlight the effectiveness and practical applicability of the proposed framework.

Enhancing reliability in garment manufacturing through FMEA and FTA

This study employs Failure Mode and Effect Analysis (FMEA) and Fault Tree Analysis (FTA) to comprehensively investigate product defects in Biyan Konveksi's manufacturing processes, one of the growing SMEs producing clothing pieces. Analyzing critical failure modes, including tear failures, stitching irregularities, sizing discrepancies, and ribbon imperfections, the research employs FTA to trace root causes, revealing the interconnected nature of these failures. The initial defect percentage, attributed to human, machine, material, and environmental factors, stood above 3%, with culottes experiencing the highest defect percentage at 3.95%. After the company implemented the enhancement measures, the defect percentage dropped significantly, reaching a range of 1 to 1.25%. Subsequently, targeted enhancement strategies are proposed, encompassing the implementation of additional worker rest breaks to alleviate fatigue, comprehensive training for new staff, and stringent machine maintenance protocols. These interventions aim to curtail tear failures, refine stitching precision, rectify sizing errors, and enhance ribbon placement. Anticipated to yield a substantial reduction in overall defect percentages, the suggested improvements position Biyan Konveksi for sustained excellence, emphasizing proactive measures to enhance worker performance and optimize manufacturing processes. The study underscores the significance of a systematic approach, combining FMEA and FTA, in diagnosing and rectifying complex failure scenarios within manufacturing environments, offering practical implications for companies aiming to fortify their competitive edge in the market.

Evaluation of safety instrumented system using “HAZOP-LOPA-FTA” methodology

Following the IEC 61508 standard, this paper presents a combined "HAZOP-LOPA-FTA" method for evaluating the safety level of a High Integrity Pressure Protection System (HIPPS) which is a type of SIS. The technique combines hazard and operability analysis (HAZOP), layers of protection analysis (LOPA), and fault tree analysis (FTA). This paper aims to confirm that a safety instrumented system achieves the intended safety integrity level as per IEC 61508. If not, suggest upgrading the safety instrumented system to lessen the effects of the scenario under study. The technique was used in the C-63 distillation column at RA1K Skikda refinery. HAZOP identified important causes and effects. According to LOPA, a minimum safety level was determined. The real SIL rating was calculated using the Tree module in the GRIF software.

ANALYSIS OF WORK ACCIDENTS DURING THE PLUMBING INSTALLATION PROCESS USING THE FAULT TREE ANALYSIS METHOD

The plumbing installation process often harbors potential risks that can lead to workplace accidents. Considering the serious consequences of workplace accidents both in terms of health and economy, there are six types of workplace accidents in the plumbing installation process: foot crushed by a pipe, hand cut by a cutting tool blade, eyes exposed to welding smoke, burnt by hot welding slag, sparked by friction between iron and a cutting blade, and leg scratched by the edge of a pipe. This study aims to analyze workplace accident incidents during the plumbing installation process using the Fault Tree Analysis (FTA) method with the hope of identifying the root causes of the accidents and formulating recommendations to improve work safety. The FTA method allows for the development of a systematic model that illustrates the cause-and-effect relationships of system failures and their components. The primary advantage of using FTA is its ability to provide a comprehensive understanding of complex accident scenarios by breaking them down into simpler basic events. The novelty of this research lies in its application of FTA specifically to the plumbing installation process, which has not been extensively explored in previous studies. The results identified that the cause of eyes exposed to welding fumes led to 11 basic events, while the mocus analysis revealed 7 basic events with 11 failure combinations.

Quantitative Risk Assessment of Hydrotreated Vegetable Oil at an Oil and Gas Company

Introduction: An oil and gas refinery operates various equipment with specific functions for different processes. Each piece of equipment has potential hazards that can damage the equipment and injure or kill workers. This study focuses on the hydrotreated vegetable oil (HVO) export facility from the jetty loading area at an oil and gas company that processes flammable liquid using various equipment. Methods: The HAZOP method determined the hazardous spots, and the probability of each equipment failure corresponding to the system was also determined using fault tree analysis (FTA). Furthermore, every event tree analysis (ETA) output probability was also determined. The probability and radius of pool fire varied for different leak hole scenarios. The final steps are individual risk per annum and potential loss of life to measure the risk level of the system. Results: Based on HAZOP deviation scenarios, every operating equipment can potentially cause a pool fire. In FTA, scenarios were developed based on different leakage hole sizes, ranging from 1-3 mm, 3-10 mm, 10-50 mm, 150 mm, and &gt;150 mm. The results indicated that leakage could occur across all operating equipment. Similarly, the ETA applied the same bore size scenarios. The consequence analysis yielded a worst-case outcome of pool fire and a best-case outcome of un-ignited fluid release. Subsequently, the pool fire output was modeled using ALOHA, which resulted in three heat flux zones: the red zone (10 kW/m²), the orange zone (5 kW/m²), and the yellow zone (2 kW/m²). Smaller leak holes had a higher probability but smaller pool fire radius. The initial risk of the export facility was unacceptable. Furthermore, insufficient safeguards contribute significantly to the resulting high-risk level. Two mitigations were implemented: adding safeguards and reducing worker hours. Conclusion: The final results showed that for every piece of equipment, the overall risk of the export facility became acceptable after mitigation..

Research on Modeling Method of Testability Design Based on Static Automatic Fault Tree

Ensuring user safety has become increasingly essential, especially for safety-critical systems (SCSs) that are vital to human life or significant property. However, the prevailing design-for-testability (DFT) model, which relies on dependencies, overlooks safety-related faults and lacks adequate metrics for evaluating system safety. Consequently, the current dependency model is insufficient in effectively assessing system safety. To address this issue, this study has developed a comprehensive DFT model that integrates system safety considerations, known as the safety-related fault model (SRFM). SRFM uses internal block diagrams (IBDs) as a means, employs a nine-tuple model to create a static automatic fault tree, and establishes mapping relationships. Sensitivity analysis is utilized to quantify system safety factors, resulting in a safety-related dependency matrix. Two crucial concepts, design safety sensitivity (DSS) and theoretical safety sensitivity (TSS), are introduced to quantify system safety loss after a fault occurs. Additionally, two new safety-related testability metrics—test advantage of safety assessment on probability (TASAP) and test advantage of safety assessment on number (TASAN)—are developed for a robust evaluation of system safety. To validate the effectiveness of SRFM, it is applied to an electronic safety and arming device (ESA), demonstrating superior performance in TASAP and TASAN compared to existing models, with a negligible impact on expected test cost (ETC).

Optimizing a robust medical consortium emergency supply planning under probability uncertainty

Emergency supply planning (ESP) addresses the production and supply planning after the occurrence of emergency events. Since the outbreak of COVID-19, hospitals have faced a severe shortage of medical protective products. Therefore, ESP is an important research topic. In addition, the exact probability distribution of disaster occurrence is usually difficult to estimate due to limited data. For this purpose, this study adopts a pair of uncertainty sets to characterise the uncertain probability, where the nominal probability is estimated via the event tree analysis (ETA) method. Based on the constructed uncertainty sets, a novel two-stage globalised robust multi-objective ESP model is developed under the conditional value-at-risk (CVaR) criterion. A case study about a medical consortium in Tangshan, Hebei Province is conducted to demonstrate the advantages of the proposed optimisation method. Finally, according to the computational results of the numerical experiments and sensitivity analysis, some practical management implications are provided for decision-makers in management.

Reliability analysis of phased mission systems based on generalized stochastic Petri nets under mixed uncertainty

Phased mission systems (PMS) are widely applied across diverse industrial systems. Technological advancements in these systems have markedly improved their performance. However, fault characteristics such as uncertainty and common cause failure (CCF) frequently emerge during failures, which significantly raises new challenges in reliability analysis. A novel system reliability analysis framework is proposed to address the mixed uncertainty and CCF in PMS. Specifically, a hybrid modeling approach that combines dynamic fault trees and generalized stochastic Petri nets (GSPN) is employed to accurately model PMS containing CCF. This approach integrates predicates and assertions from GSPN to define four reusable sub-Petri net models at different hierarchical levels, including module, phase, CCF, and overall mission levels. Furthermore, interval theory is incorporated into the framework to manage imprecise component lifetime data. For uncertainty quantification, a synergistic approach combining genetic algorithm and Monte Carlo simulation is utilized. Additionally, a simplified approach is introduced to reduce the complexity of computing the reliability boundary values of PMS. Finally, the proposed method is applied to conduct reliability analysis of a phased altitude and orbit control system. The analysis results validate its effectiveness and applicability in addressing the mixed uncertainty and CCF of PMS.

Initial Event Analysis for Turbine Missile Events at Floating Nuclear Power Plants Using the Master Logic Diagram Method

Floating Nuclear Power Plants (FNPP) have become a popular design choice in several countries, including South Korea, China, and Denmark. Safety analysis, including probabilistic safety assessment, must be conducted for every nuclear reactor design. Among the parameters that need to be determined are initiating events. Initiating events is crucial information as it impacts further analyses, such as event and fault tree analyses. Various methods exist for deciding and initiating events, including the Master Logic Diagram (MLD). The determination of initiating events can be based on the potential impact of internal or external hazards on the FNPP. This study aims to demonstrate the application of MLD in determining initiating events in the case of a turbine missile incident on Akademik Lomonosov floating NPP. Turbine missile events are critical due to their potential to damage important safety-related structures, systems, and components in the vicinity. From the analysis, it was found that ten basic events could be candidates for initiating events. After the screening process, four initiating events were identified as the final result: reactor vessel rupture (RVR), loss of feedwater (LOFW), feedwater line break (FWLB), and loss of condenser vacuum (LOCV). Keywords: Floating NPP, safety analysis, initiating event, master logic diagram (MLD)

Reliability analysis of subsea control system using FMEA and FFTA

Reliability technology plays a significant role in ensuring the safe operation of the subsea control system. To perform a comprehensive analysis of the reliability of complex systems, a combination of Failure Mode and Effects Analysis (FMEA) and Fuzzy Fault Tree Approach (FFTA) is introduced. Firstly, the FMEA method is used to analyze the potential failure modes and causes of system failure by completing the qualitative analysis of system reliability from the perspective of multi-factor failure modes. And the risk matrix diagram is applied to determine the degree of harm of different failure modes to the system. Then, the system reliability is quantitatively analyzed using FFTA, and a fault tree model is established by dividing the system into "system-subsystem-component" and solving for the minimum cut set. In addition, the failure probability of the top-level event is quantitatively calculated by introducing fuzzy set theory, and the probabilistic importance of the bottom-level event is analyzed to find out the weak points of each subsystem. Finally, a qualitative and quantitative reliability analysis is conducted by using FMEA-FFTA method for subsea control system. Effective measures should be taken to focus on preventive protection and regular testing for the high risk, medium–high risk and medium risk modes for subsea control system.

Determining The Causation Probability of Ship Collision in the Barito River Using Fault Tree analysis (FTA) & Bayesian Network Modelling

Abstract In Indonesia, five of the twenty-five vital ports are situated along rivers, with the Port of Banjarmasin having the highest visit value. Over the previous five years from 2017 to 2021, 20 collision-type accidents have occurred on the Barito River shipping channel. With the large number of ship collision accidents and fatalities occurring on the Barito River, it is necessary to make initial efforts to determine the probability of the main causal factors in order to carry out a risk assessment. This paper aims to determine the causation probability of ship collisions on the Barito River so that it can be used in risk assessments to formulate recommendations for mitigating the risk of ship collisions. The causes for ship collisions are identified using fault tree analysis (FTA) and modelled using bayesian networks, including the technical factors, environment factors, and human factors. Based on FTA result and BN sensitivity analysis, the main factor causing ship collision accidents with the largest probability value is environmental factors.

Analysis of ship collision accidents in Indonesia using fault tree analysis (FTA) method

Abstract As an archipelagic country with emerging economies, maritime transportation has significantly contributed to the Indonesian economy by ensuring the fullness of domestic demand for goods and services, accelerating annually. However, with the increase in sea traffic, the probability of collision accidents may also grow, posing non-negligible risks to individuals and society in various aspects. Considering this condition, this paper assesses and evaluates past maritime collision accidents in Indonesia to observe and analyze the tendency of factors contributing to collision accidents. The analysis was conducted using the Fault Tree Analysis (FTA) method, qualitative and quantitative, on data obtained from the collision investigation report in the last 20 years. The qualitative approach is used to propose the minimal cut set, and the quantitative analysis is conducted to estimate the probability. Based on the obtained probability and the produced cut set diagram, the conclusion states that human-related factors contribute to the top even occurrence at most, implying that the human factor is the most contributing factor to collisions. Those factors include the lack of training, lack of experience, and improper decisions.