Search Results (95)

Most of the failures during the actual operation of equipment are caused by improper human operation, tools, spare parts, and environmental factors. These faults are routine. Conventional faults have been validated during equipment development, testing, identification, and maintenance processes, with clear definitions and clear fault tree analysis (FTA) conclusions. Digital twins can offer rapid and interactive diagnostic capabilities for routine equipment failures. To enhance the efficiency of routine fault diagnosis and the interactive experience of the diagnosis process, this paper proposes a digital twin-based equipment routine fault diagnosis model. On this basis, considering the excellent interactivity of the Interactive Electronic Technical Manual (IETM), a conventional equipment fault diagnosis scheme based on twin data and IETM is designed. This scheme converts the equipment fault tree into an IETM fault data model (DM), which is structured and stored in a database to form a fault database. Using real-time twin data of equipment as input, the FTA method is adopted to perform step-by-step fault diagnosis and isolation guidance operation through the IETM process DM combined with fault, while providing maintenance operation guidance. When the real-time twin data of the equipment is not completely consistent with the fault information in the fault library, the case analysis method is used to calculate the similarity between the real-time twin data of the equipment and the clearly defined fault symptom information in the fault library. Based on the set similarity threshold, IETM pushes fault DMs above the threshold for corresponding fault diagnosis isolation guidance. Full article

This paper presents a novel risk-based maintenance (RBM) approach for the development of a structured maintenance strategy for the power-generating (PG) unit at the gas plant of the Sirte Oil Company (SOC). The proposed approach comprises three key aspects: estimated risk (ER), risk evaluation (RV), and maintenance planning (MP). To identify and prioritize critical components, the methodology integrates fault tree analysis (FTA) with Monte Carlo simulations, enabling the probabilistic modeling of failure scenarios and the accurate quantification of risk. High-pressure (HP) water systems were selected as a case study due to their significant role and failure consequences within the PG unit. Through this RBM methodology, risk levels—based on the probability of failure (PoF) and consequence of failure (CoF)—were quantified, and maintenance tasks were rescheduled to target the most vulnerable components. The results demonstrate that implementing the RBM strategy reduced unplanned shutdowns and optimized uptime, achieving 348 operational days per year, compared to the baseline 365-day mean time to failure (MTTF) cycle (reduction in downtime of around 4.65%). This translated into a measurable improvement in system reliability and operational efficiency. The approach is especially applicable to processing units operating under harsh conditions, offering a preventive tool for the reduction of risk exposure and improvements in asset performance. Full article

Flying cars are an important vehicle for future urban air mobility. Mainstream flying cars predominantly adopt the e-VTOL-like configuration. Unlike traditional aircraft, these flying cars must be operated by a single pilot. The corresponding hybrid ground-flight control scheme remains immature, with only a few reliability analyses focused on flight safety. Based on the single-pilot operation (SPO) concept, this paper designs a hybrid control scheme for e-VTOL-like flying cars and proposes a restricted driving mode for the the take-off and landing stages and an autonomous driving mode for the cruising stage, respectively. Taking the landing phase as an example, a fault mode analysis and fault tree analysis are conducted for the restricted driving mode, focusing on factors that are sensitive to flight safety. A fault probability analysis is performed of the landing control unit in the restricted driving mode. The calculated probability of the top event occurring is 1.98 × 10⁻⁸ per flight, which proves the feasibility of the design meets the safety requirements. This study provides a foundation for a safety assessment of driving modes in future designs of flying cars. Full article

Negative Ion Source Neutral beam Injection (NNBI), as a critical auxiliary heating system for magnetic confinement fusion devices, directly affects the plasma heating efficiency of tokamak devices through the reliability of its beam source system. The single-shot experiment constitutes a significant experimental program for NNBI. This study addresses the frequent equipment failures encountered by the NNBI beam source system during a cycle of experiments, employing fault tree analysis (FTA) to conduct a systematic reliability assessment. Utilizing the AutoFTA 3.9 software platform, a fault tree model of the beam source system was established. Minimal cut set analysis was performed to identify the system’s weak points. The research employed AutoFTA 3.9 for both qualitative analysis and quantitative calculations, obtaining the failure probabilities of critical components. Furthermore, the F-V importance measure and mean time between failures (MTBF) were applied to analyze the system. This provides a theoretical basis and practical engineering guidance for enhancing the operational reliability of the NNBI system. The evaluation methodology developed in this study can be extended and applied to the reliability analysis of other high-power particle acceleration systems. Full article

Ocean-going vessels rely on marine diesel engines, referred to as the main engine, to carry the vessel’s load and ensure safe travel. These engines play a critical role, as their operation impacts on all aspects of the vessel’s functionality. To meet increasing demands for extended run times while maintaining reliability, it is essential to address the risks of main engine failure. Previous studies have highlighted numerous accidents resulting from such failures. Consequently, the reliability of the main propulsion engine is a crucial component of safe vessel operation. This study addresses the lack of methodologies for predicting engine reliability using failure running hours (FRHs). A data-driven model was developed using FRH data collected from marine engineers during on-board maintenance operations. Additionally, fault tree analysis (FTA) was employed to calculate the reliability of individual subsystems and the overall main propulsion engine. The findings indicate that the lube oil system, freshwater cooling system, scavenge system, and fuel system reach 0% reliability at approximately 2000 h, 14,000 h, 2500 h, and 1400 h of operation, respectively. Additionally, the reliability of the main propulsion engine drops to 0% after around 900 h of operation. By incorporating this prediction model, ship operators can better schedule maintenance, significantly enhancing engine reliability and reducing maritime accidents. This approach contributes to safer and more efficient operations for commercial marine systems. This study represents a vital step toward improving the reliability of ocean-going vessels. Full article

The air transportation system is composed of multiple elements and belongs to a complex socio-technical system. It is difficult to assess the risk of an aircraft fault because it could constantly change during operation and is influenced by numerous factors. Although traditional methods such as Failure Mode, Effects, and Criticality Analysis (FMECA) and Fault Tree Analysis (FTA) can reflect the degree of fault risk to a certain extent, they cannot accurately quantify and evaluate the fault risk under the multiple influences of human factors, random faults, and external environment. In order to solve these problems, this article proposes a fault risk assessment method for aircraft control systems based on a fault risk composite assessment framework using the Improved Risk Priority Number (IRPN) as the basis for the fault risk assessment. Firstly, a Bayesian network (BN) and Gated Recurrent Unit (GRU) are introduced into the traditional evaluation framework, and a hybrid prediction model combining static and dynamic failure probability is constructed. Subsequently, this paper uses the functional resonance analysis method (FRAM) by introducing a risk damping coefficient to analyze the propagation and evolution of fault risks and accurately evaluate the coupling effects between different functional modules in the system. Finally, taking the fault of a jammed flap/slat drive mechanism as an example, the risk of the fault is evaluated by calculating the IRPN. The calculation results show that the comprehensive failure probability of the aircraft control system in this case is 3.503 × 10⁻⁴. Taking into account the severity, the detection, and the risk damping coefficient, the calculation result of IRPN is 158.00. According to the classification standard of the risk level, the failure risk level of the aircraft belongs to a controlled risk, and emergency measures need to be taken, which is consistent with the actual disposal decision in this case. Therefore, the evaluation framework proposed in this article not only supports a quantitative assessment of system safety and provides a new method for fault risk assessments in aviation safety management but also provides a theoretical basis and practical guidance for optimizing fault response strategies. Full article

A palm oil company based in Bangka is actively expanding its operations in the palm oil processing industry. The company specializes in producing crude palm oil (CPO) and palm kernel, with its production process encompassing five key stages: weighing, sterilization, threshing, pressing, and clarification. Oil loss, especially at the pressing station, is one of the company’s biggest problems. Nuts, fibers, empty bunches, and effluent are some of the sources of oil loss in CPO production. Since extreme losses that exceed set norms can cause serious inefficiencies and financial repercussions, it is imperative that the organization identifies and mitigates the underlying causes of oil loss. One option that the business could use is the fault tree analysis (FTA) method, which offers a methodical way to pinpoint the root causes of production inefficiencies to solve this problem. According to current assessments, empty bunches caused the largest average oil loss over a one-month period, with a loss rate of 0.11%. Oil loss at the pressing station is caused by a number of factors, such as inadequate maintenance practices, non-compliance with established work procedures, suboptimal ripeness levels of harvested palm fruit, and operator neglect in maintaining optimal machine pressure in accordance with company standards. To reduce oil loss in the production process and increase efficiency, these concerns need to be addressed. Full article

Worker safety has been relatively overlooked in the rapidly growing aquaculture industry. To address this gap, industrial accident compensation insurance data—mainly from floating cage and seaweed farming—were analyzed to quantify accident types and frequencies, with a focus on human elements as root causes. Basic causes were selected based on IMO Resolution A/Res.884 and assessed through a worker awareness survey. Fault Tree Analysis (FTA), a Formal Safety Assessment technique, was applied to evaluate risks associated with these causes. The analysis identified organization at the farm site (23.3%), facility and equipment factors (22.8%), and people factors (21.4%) as the primary causes. Among secondary causes, personal negligence (13.2%), aging gear and poor maintenance (11.4%), and insufficient risk training (10.4%) were the most significant. Selective removal of these causes reduced the probability of human element-related accidents from 64.6% to 48.6%. While limited in scope to Korean data and self-reported surveys, the study demonstrates the value of combining quantitative data with worker perspectives. It provides foundational data for developing tailored safety strategies and institutional improvements—such as standardized procedures, multilingual education, and inclusive risk management—for sustainable safety in aquaculture. Full article

Multimodal freight transport systems, integrating maritime, rail, and road modes, play a vital role in modern logistics but face elevated operational, human, and environmental risks due to their complexity and interdependencies. To address the limitations of conventional risk assessment methods, this study proposes a hybrid risk modeling framework that integrates fault tree analysis (FTA), dynamic fault trees (DFTs), and fuzzy logic reasoning. This approach supports the modeling of sequential failures and captures qualitative uncertainties such as human fatigue and inadequate training. The framework incorporates reliability metrics, including Mean Time to Failure (MTTF) and Mean Time Between Failures (MTBF), enabling the quantification of system resilience and identification of critical failure pathways. Application of the model revealed human error, particularly procedural violations, insufficient training, and fatigue, as the dominant risk factor across transport modes. Road transport exhibited the highest probability of risk occurrence (p = 0.9960), followed by rail (p = 0.9937) and maritime (p = 0.9900). By integrating probabilistic reasoning with qualitative insights, the proposed model offers a flexible decision support tool for logistics operators and policymakers, enabling scenario-based risk planning and enhancing system robustness under uncertainty. Full article

(1) Background: With the deep integration of e-commerce and video technology, live-streaming marketing has emerged globally and maintained rapid growth. However, most of the current research on live-streaming e-commerce marketing focuses on merchants’ sales strategies and consumers’ purchase intentions, and there is relatively little research related to the risks of live-streaming e-commerce marketing. Nevertheless, with the development of live-streaming e-commerce marketing and its integration with technologies such as artificial intelligence and virtual reality (VR), live-streaming e-commerce marketing still faces challenges such as unclear subject responsibility, difficulty in verifying the authenticity of marketing information, and uneven product quality. It also harbors problems such as the ethical misbehavior of AI anchors and the excessive beautification of products by VR technology. (2) Methods: This study systematically analyzes the scenarios of live-streaming marketing to elucidate the mechanisms of risk formation. Utilizing fault tree analysis (FTA) and risk checklist methods, risks are identified based on the three core elements of live-streaming marketing: “people–products–scenes”. Subsequently, the Delphi method is employed to refine the initial risk indicator system, resulting in the construction of a comprehensive risk indicator system comprising three first-level indicators, six second-level indicators, and 16 third-level indicators. A hesitant fuzzy multi-attribute group decision-making method (HFMGDM) is then applied to calculate the weights of the risk indicators and comprehensively assess the live-streaming marketing risks in live broadcast rooms of three prominent celebrity anchors in China. Furthermore, a detailed analysis is conducted on the risks associated with the six secondary indicators. Based on the risk evaluation results, targeted recommendations are proposed. This study aims to enhance consumers’ awareness of risk prevention when conducting live-streaming transactions and pay attention to related risks, thereby safeguarding consumer rights and fostering the healthy and sustainable development of the live-streaming marketing industry. (3) Conclusions: The results show that the top five risk indicators in terms of weight ranking are: Ethical Risk of the AI Anchor (A4), VR Technology Promotion Risk (F3), Anchor Reputation (A1), Product Quality (D1), and Logistics Distribution Service Quality (D2). The comprehensive live-streaming marketing risk of each live broadcast room is Y > L > D. Based on the analysis results, targeted recommendations are provided for anchors, MCN institutions, merchants, supply chains, and live-streaming platforms to improve consumer satisfaction and promote sustainable development of the live-streaming marketing industry. Full article

The maritime transport of liquefied gases poses significant safety and environmental hazards such as fire, explosion, toxic gas emissions, and air pollution. The main objective of this study was to systematically identify, analyze, and prioritise the potential risks associated with the operation of liquefied gas tankers using a hybrid methodological framework. This framework integrates Fuzzy Delphi, Fuzzy DEMATEL, and Fault Tree Analysis (FTA) techniques to provide a comprehensive risk assessment. Initially, 20 key risk factors were identified through expert consensus using the Fuzzy Delphi method. The causal relationships between these factors were then assessed using Fuzzy DEMATEL to understand their interdependencies. Based on these results, accident probabilities were further analyzed using FTA modelling. The results show that fires, explosions, and large gas leaks are the most serious threats. Equipment failures—often caused by corrosion and operational errors by crew members—are also significant contributors. In contrast, cyber-related risks were found to be of lower criticality. The study highlights the need for improved crew training, rigorous inspection mechanisms, and the implementation of robust preventive risk controls. It also suggests that the prioritisation of these risks may need to be reevaluated as autonomous ship technologies become more widespread. By mapping the interrelated structure of operational hazards, this research contributes to a more integrated and strategic approach to risk management in the LNG/LPG shipping industry. Full article

The operational efficiency and reliability of the ship’s lubrication oil system directly impact the vessel’s safety. Traditional reliability analysis methods struggle to effectively handle the system’s dynamic characteristics and multi-source data analysis. To address these issues, this study proposes an innovative method that integrates feature dimensionality reduction, a dynamic Bayesian network of gravity model to improve the accuracy of system reliability analysis. First, the proportional hazards model is used to evaluate the operational reliability of each component, providing a quantitative basis for assessing the system’s health status through failure rate estimation. Then, a dynamic Bayesian network model is employed for overall system reliability analysis, fully considering the impact of multi-state devices and different maintenance strategies. The proposed DBN-based reliability assessment method achieves significant improvements over the traditional Fault Tree Analysis (FTA). The reliability of the main lubrication oil system (GUB) increases from 0.169 to 0.261, representing a 9.2% improvement; under scheduled maintenance conditions, the system reliability stabilizes at approximately 0.9873 after $0.4\times {10}^5$ h, compared to only 0.24 without maintenance. The proposed method effectively evaluates the reliability of the lubrication oil system, and the maintenance strategy using this method can greatly improve the reliability, providing strong support for scientifically guiding maintenance decisions. Full article

Mining companies are increasingly being motivated to become High Reliability Organisations (HROs) in order to achieve better results in critical areas such as safety, environment management, and loss avoidance despite their complex environments. High Reliability Organisations are recognised by their abilities to effectively anticipate failures and disasters, including use of lessons learnt from previous failures. This paper seeks to demonstrate how designers for systems in the mining industry can learn from failures to anticipate failures and effectively manage them. It also demonstrates the applicability of a hybrid model which incorporates and integrates Fault Tree Analysis (FTA), Reliability Block Diagram (RBD) analysis, Risk Priority Number (RPN) concepts, and Analytical Hierarchy Processes (AHPs) in a case study for a High Potential Incident (HPI) at an underground hard rock mine. It shows how valuable lessons can be extracted and how these lessons can be used in decision making to prevent and manage future failures. The main contribution of this work is the demonstration of incorporating HRO principles with a hybrid modelling framework for learning from failures. Full article

This study is concerned with the critical issue of ensuring safety in the maritime transportation of hazardous materials, specifically LPG and LNG. These gases, which are increasingly adopted as cleaner alternatives to traditional fuels, pose significant risks due to their flammable and hazardous nature, thus making safety a priority for both policy and practice. In order to address these challenges, this research employs the Delphi method to gather expert opinions and Fault Tree Analysis (FTA) to systematically analyze potential fault points in loading, unloading, and storage processes. The findings of the study indicate that human faults, such as inadequate maintenance and overwork, are the most significant contributors to accidents, followed by environmental factors like adverse weather and machinery faults. The study offers actionable recommendations, including the enhancement of training programs, the implementation of advanced monitoring technologies, and the strengthening of safety protocols. These findings offer critical insights to policymakers and practitioners, with a view to mitigating risks in LPG and LNG operations. Full article

In the present paper, the subject of investigation is the reliability assessment of the single-stage reversible Hydropower Unit No. 3 (HU3) in the Bulgarian Pumped Hydro-Electric Storage (PHES) plant “Chaira”, which processes the waters of the “Belmeken” dam and “Chaira” dam. Preceding the destruction of HU4 and its virtual simulation, an analysis and its conclusions for rehabilitation and safety provided the information required for the reliability assessment of HU3. Detailed analysis of the consequences of the prolonged use of HU3 was carried out. The Supervisory Control and Data Acquisition (SCADA) system records were studied. Fault Tree Analysis (FTA) was applied to determine the component relationships and subsystem failures that can lead to an undesired primary event. A Failure Modes and Effect Analysis methodology was proposed for the large-scale hydraulic units and PHES. Based on the data of the virtual simulation and the investigations of the HU4 and its damages, as well as on the failures in the stay vanes of HU3, it is recommended to organize the monitoring of crucial elements of the structure and of water ingress into the drainage holes, which will allow for detecting failures in a timely manner. Full article