Risk Analysis Method Research Articles

Earthquake Disaster Risk Assessment in Purworejo District, Central Java Province, Indonesia

<p class="Abstract">Purworejo Regency is directly adjacent to the Indian Ocean and is close to the Java subduction, so it is estimated to have a high earthquake risk index. This study aims to analyze the earthquake disaster risk in Purworejo District, Central Java Province, Indonesia. Earthquake risk analysis methods follow Perka BNPB No 02 of 2012, including hazard, vulnerability, and capacity analysis. The disaster risk index combines the disaster, vulnerability, and capacity indexes. The findings of this study reveal the following: (1) 295 villages within Purworejo Regency fall into the high earthquake hazard category, primarily located in the southern region of Purworejo or near the Java subduction zone. (2) The high vulnerability to earthquakes is widespread across almost all villages in Purworejo Regency. The highest concentration of villages with a high vulnerability index is found in Ngombol District (57 villages), Butuh District (41 villages), and Purwodadi District (40 villages). (3) Purworejo Regency exhibits a capacity to cope with earthquakes that are not categorized as low. The majority, comprising 464 villages (93.92%), falls within the middle class, while 30 villages (6.08%) are classified as having a high capacity. (4) Within Purworejo Regency, 117 villages (23.7%) are at a high risk of earthquakes, and 376 villages face a moderate risk. Only one village has a low disaster risk index.</p>

Study of Phase Changes in Operational Risk for Trucks

This study concerns the management of operational risk in truck transport using the reliability theory of risks. In this regard, the risk analysis of changes in the vehicle unavailability represents an important topic. In this study, the authors present their own method for analysing the phase changes in risk corresponding to successive sections (phases) of vehicle mileage. The presented risk analysis method is based on an integrated assessment of losses associated with the costs of incidental repairs and losses caused by lost income during vehicle downtime. This includes the following: assessment of differences in average risk and differences in the coefficient of variation in the time series of vehicle mileage phases, indicating the outliers and extremes of phase risk, identifying their physical causes and testing the statistical significance of phase risk differences. The proposed method is described mathematically and verified experimentally based on the operational data concerning trucks from two selected brands (20 trucks from each brand). We show that the method can be used to predict the continuity of transport services in the short term (one-year horizon). The method could also be useful to compare vehicles of different brands in the context of their sensitivity to operational risks.

A novel risk analysis method for hazardous cargo operations at port integrating the HFLC model and DEMATEL method

The development of maritime chemical and industrial trade has led to the large-scale hazardous cargo operations at port, making it essential to conduct risk analysis to analyze the risk factors affecting port safety and prevent the occurrence of accident. However, the complex interrelationships among risk factors in hazardous cargo operations and the uncertainties in the risk analysis process pose significant challenges to the effectiveness of risk analysis results. To this end, this paper proposes an integrated risk analysis method for hazardous cargo operations at port based on the hesitant fuzzy linguistic cloud (HFLC) model and the DEMATEL method. Firstly, 20 risks related to hazardous cargo operations are determined based on accident analysis and previous literatures. The HFLC model is then applied to characterize the linguistic judgements with uncertainty provided by the experts on the different risk factors. Next, the DEMATEL method is extended to the HFLC environment and utilized to calculate the centrality degree and causality degree of different risk factors in the form of HFLC. Finally, ten factors for cause group and effect group are identified separately, and the critical influence relationships between the factors are determined. This study can assist port managers in mitigating the risks of hazardous cargo operations at port, and can also serve as a crucial basis for the formulation of management decision-making and emergency response strategy.

The risk-based operational safety strategy for Perkin-Elmer/Cetus DNA Thermal Cycler PCR systems

Introduction: this article was conducted in the field of polymerase chain reaction (PCR) test safety, where it is essential to understand the contribution and impact of risk analysis methods to improve test safety medical diagnosis at the institutional level. In this context, the current study focuses on failure modes and effects analysis (FMEA) applied to the Perkin-Elmer/Cetus deoxyribonucleic acid (DNA) thermocycler.Objective: to describe the application of FMEA to improve the operational safety of Perkin-Elmer/Cetus DNA thermal cyclers used in medical diagnostics in ataxic patients. Methods: to carry out this study, a methodology based on an exhaustive review of the scientific literature available in academic databases and relevant sources was used. Previous studies on FMEA analysis of DNA thermocyclers in common and expanded forms were collected and analyzed.Results: the results obtained demonstrated that FMEA is an effective tool to identify and evaluate possible failure modes of Perkin-Elmer/Cetus DNA thermal cyclers. Several defects were identified and their consequences, causes and classification based on their severity and frequency were determined. Likewise, corrective actions are proposed to reduce the identified risks.Conclusions: early identification of possible failure modes and implementation of corrective actions can reduce risk and guarantee the quality of the diagnoses carried out and therefore improve operational safety

Artificial intelligence for risk analysis-A risk characterization perspective on advances, opportunities, and limitations.

Artificial intelligence (AI) has seen numerous applications for risk analysis and provides ample opportunities for developing new and improved methods and models for this purpose. In the present article, we conceptualize the use of AI for risk analysis by framing it as an input-algorithm-output process and linking such a setup to three tasks in establishing a risk description: consequence characterization, uncertainty characterization, and knowledge management. We then give an overview of currently used concepts and methods for AI-based risk analysis and outline potential future uses by extrapolating beyond currently produced types of output. We end with a discussion of the limits of automation, both near-term limitations and a more fundamental question related to allowing AI to automatically prescribe risk management decisions. We conclude that there are opportunities for using AI for risk analysis to a greater extent than is commonly the case today; however, critical concerns about proper uncertainty representation and the need for risk-informed rather than risk-based decision-making also lead us to conclude that risk analysis and decision-making processes cannot be fully automated.

Risk Measurement, Analysis, and Prediction Methods for Online Financial Services

The analysis and research on the risk of online financial business is divided into four main areas; the construction of metrics, analysis and modeling, risk prediction, and risk monitoring and control. It mainly uses high-frequency data to update the dynamic factor model, converts the results to low-frequency data to derive the systematic risk indicators; based on the Markov interval transformation model, the unpredictable and uncertain mechanisms are used as stochastic variables to identify the characteristics of the risk changes to cope with the Internet financial risks. The study concludes that the Internet financial risk has a certain trend and periodicity, and the presented market is relatively stable; due to the close connection between Internet finance and traditional financial industry, the resonance effect can bring certain risk to the whole financial market, and it is still necessary to pay attention to the changing risk factors and take corresponding risk management measures.

Risk assessment of man‐machine systems under safety‐critical multitasking situations

AbstractMultitasking is increasingly common in highly complex and safety‐critical systems, especially under abnormal situations. Mental overload (MOL) may occur and result in forgetting/mistaking tasks uncertainly. Such probabilistic errors could have catastrophic consequences and contribute greatly to the multitasking risk of man‐machine systems. In this paper, to better identify the risks of safety‐critical multitasking situations, MOL mechanism is investigated and a risk analysis method considering MOL is proposed. MOL occurs when the demand for resources estimated by Multiple Resources Model exceeds an operator's ability. Then, the operator's performance degrades, and s/he tends to mistake or abandon parts of tasks. Based on the MOL mechanism, a MOL‐performance dependency (MOL‐PDEP) gate is proposed to incorporate MOL into risk analysis. Its inputs are concurrent tasks, and it triggers the related hazardous human behavior events with certain probabilities if MOL occurs. Through this gate, the dependence among these events and their nondeterministic cause relationships to MOL are added to traditional fault tree (FT), which presents a challenge issue to FT analysis. An implicit method is proposed to analyze the FT with MOL‐PDEP gate and calculate the accident probability. A case study on a helicopter crash accident demonstrates the effectiveness of the proposed method.

Numerical simulation of gas diffusion and explosion limit of VOCs in containment integrated leak rate test

CILRT is an important work in the overhaul of nuclear power plants. VOCs from paints and cleaners used in the containment during the overhaul will migrate inside the containment, and the numerous rooms and compartments inside the containment make the air flow impeded, and the VOCs may be enriched to bring combustion risk. The complete fire risk analysis method includes volatilization kinetics of chemicals, mixture explosion limits, and numerical simulation of VOCs diffusion and migration. The volatilization rate at the lowest room temperature of 20°C is used as a conservative input, the complement of CAITA realistic model is used as the flow domain, and the geometry is appropriately simplified, and the steady ventilation process, the internal flow and the laws of diffusion and agglomeration of 12 kinds of VOCs gases in the 9-h pressure-holding process are investigated by Computational Fluid Dynamics. The simulation results of steady ventilation show that the VOCs gases are almost uniformly carried by the air to all spaces inside the containment, and the explosion risk is low. The concentration field of the steady ventilation process was taken as the initial boundary condition and unsteady state simulation of the 9-h holding pressure process was performed. The results show that the gas flow inside the containment basically stops after 3456 s of pressure holding. With the extension of time, the VOCs gases accumulate at the bottoms of the three lower layers of the containment under the effect of laminar diffusion and gravitational settling, where the total concentration of the mixed gases reaches the highest at the bottom of the lowest layer. The total concentration of the VOCs gas mixture was below the lower explosion limit throughout the 9-h pressure-holding process, and the explosion risk was low.

NAVIGATOR PREPARATION DURING SPRAYING BY UAVS

The article presents the results of research on the implementation of navigator preparation duringagricultural spraying, conditioning the safe and precise performance of the task. This assumptionwas confirmed during spraying with unmanned aerial vehicles carried out in 2021–2023. Theexperience gained and conclusions enabled the development of a concept of initial and directnavigational preparation for unmanned aircraft systems performing spraying. It is also possibleto use this algorithm to perform deactivation by drones. The results obtained from the conductedaerial tests (within two scenarios: agricultural spraying and decontamination) have also shown thatthe risk analysis methodology recommended by EASA (SORA) entails a number of limitations andcannot be applied during spraying as it causes gaps in safety management. Therefore, a proprietaryEPEP risk analysis method has been developed specifically for spraying, which allows the pilot,the operator of an unmanned aircraft, to perform a risk analysis and manage it accordinglyimmediately before performing the task, compensating or minimizing the hazards that should beat an acceptable level before spraying.

Modeling the Optimal Distribution of an Enterprise’s Resources

"In the modern economy, optimizing the use of resources is a key factor in ensuring the success of a company. This article optimizes the allocation of enterprise resources to maximize profits, which contributes to the sustainable development of both the enterprise and the economy of the state. To achieve this goal, the authors have developed a model for the optimal allocation of enterprise funds. The article considers various methods to allocate investor funds to maximize profits. It is concluded that it is impossible to increase income without increasing risk or reduce risk without reducing profit. The portfolio that contains the riskiest assets will be the most diversified and bring the best return per unit. To assess the sustainable development of an enterprise with due regard to its possible risks, it is not enough to use only quantitative methods of risk analysis. It is also necessary to develop a comprehensive methodology that would consider all possible risks typical of Russian enterprises."

Analyzing the risk of the ammonia storage facility using extended FMEA model based on probabilistic linguistic GLDS method with consensus reaching

Due to the energy crisis, ammonia stands out as an efficient hydrogen energy carrier. However, liquid ammonia's nature of toxicity, corrosiveness, volatility, flammability, etc., make its storage highly risky. It is essential to analyze the risk of the ammonia storage facility for its safety improvement. Failure mode and effect analysis (FMEA) has been a popular risk analysis method due to its ease of implementation. However, traditional FMEA is insufficient to model the uncertainty of risk assessment information, enhance the consensus among experts, aggregate experts' risk evaluation information, and derive reliable risk analysis results. To address these limitations, we introduce a hybrid probabilistic linguistic FMEA framework to analyze failure risk in the ammonia storage facility. First, the probabilistic linguistic terms (PLTs) are introduced to express uncertain risk evaluation information of failure modes. Second, a risk acceptability-based consensus-reaching process is introduced to measure experts' consensus on each failure mode's risk and improve their consensus. Then, a consensus degree-based ordered weighted averaging operator is introduced to fuse experts' risk evaluation information, where experts' weight is determined by their consensus degree. Furthermore, the gained and lost dominance score method is improved on the basis of the expected value of the PLTs to prioritize failure modes' risk. Finally, a case study of the risk analysis for the ammonia storage facility is performed to show the efficiency of the extended FMEA. The case study indicated that condenser cooling water pump failure and failure of level transfer are the top two failure modes and have risk scores of 0.126 and 0.091, respectively.

Gaidai multivariate risk assessment method for cargo ship dynamics

ABSTRACT Contemporary cargo vessel transport constitutes a vital part of the global trade and economy. Thus, it is of primary engineering and design importance to further develop more efficient novel risk analysis and risk assessment methods for large cargo ships. Classical risk assessment and risk analysis methodsmay not always have advantages of efficiently dealing with dynamic system’s high dimensionality along with cross-correlations between various critical dimensions. Current study benchmarks state-of-art Gaidai spatiotemporal structural risk assessment method, suitable for multivariate structural dynamic systems versus a well-established bivariate risk assessment method. As an example, for this risk assessment study, an operating container vessel has been selected. The vessel hull had been subjected to large deck panel stresses and accelerations during cross-Atlantic sailing. Risks of losing cargo containers are caused by extreme dynamics being one of the primary concerns for vessel cargo transport. Gaidai multivariate risk assessment methodology, advocated here, opens up new possibilities of predicting efficiently, yet simply potential structural damage/failure risks for nonstationary, nonlinear, multivariate cargo ship dynamic systems, as a whole. Note that advocated novel multivariate risk assessment method may be applied to a wide range of complex marine and offshore engineering systems.

Research on Intelligent Control Model of Laboratory Safety Risks in Colleges and Universities Based on Digital Twins

This paper focuses on developing an intelligent management model for safety risks in university laboratories based on digital twin technology to improve safety management efficiency and accuracy. The virtual simulation environment of the laboratory is constructed by using digital twin technology, which is combined with the DEMATEL-ISM method for risk identification and analysis. Fault tree analysis (FTA) method was utilized to construct a laboratory safety accident fault tree to identify and assess potential risk factors. It was found that safety risks in laboratories can be effectively identified and controlled by digital twin technology. The risk assessment showed that unregulated drug storage, lack of monitoring and warning devices, insufficient safety awareness, inadequate systems and unreasonable layout of water, electricity and gas pipelines were the main risk factors. The empirical analysis of 11 university laboratories revealed that most of the laboratories were at a “relatively safe” level. The intelligent management model of safety risk in university laboratories based on digital twins can effectively identify and assess the safety risk, provide a scientific basis for the formulation of safety management measures, and thus improve the efficiency and accuracy of laboratory safety management.

Enhancing Healthcare Worker Well-Being and Patient Safety in the Pediatric Emergency Department: A Comprehensive Hazard and Risk Analysis

Providing a healthy and safe hospital environment improves employee health and prevents occupational diseases and accidents. This increases the motivation and productivity of employees and contributes to the improvement of service quality in hospitals. Healthcare workers have to work meticulously to provide accurate diagnosis, treatment and care services while competing with time. Working under pressure can cause fatigue, stress and burnout in healthcare workers. This can affect their decision-making abilities and lead to malpractice. Errors can cause occupational accidents or occupational diseases, while misunderstanding or misapplication can cause serious damage to the patient's health. In this study, hazards and risks were identified in order to ensure that employees working in the pediatric emergency department of the hospital work in a healthier and safer environment. Fine Kinney method was used as a risk analysis method in the study. It was observed that the high rate (86.7%) of employees' inability to participate in social and cultural activities (86.7%) due to occupational fatigue caused a decrease in the desire to work (70%), as well as the intense feelings of burnout and frustration (70%) caused by stress caused by the profession. As a result of the challenging conditions experienced, it was determined that the desire not to see patients during the day (76.7%) and dissatisfaction increased (46.6%). Healthcare workers need to be vigilant and careful, and occupational health and safety initiatives should be carried out systematically, team-based, and education-focused.

Evaluation of possibilities of fulfillment of customer requirements as an element of end-to-end management of enterprise business processes

Aim. Improvement of the enterprise business processes management by offering methodical tools for assessing the possibilities to fulfill customer requirements before concluding a contract for product delivery / service provision.Objectives. To analyze the existing approaches to the management of enterprise business pro- cesses in the scientific literature; to determine the control points of end-to-end management of business processes; to consider the peculiarities of the application of qualitative and quan- titative types of risk analysis; on the basis of the conducted research to develop a methodology for assessing the possibilities of meeting customer requirements at the enterprise.Methods. The article considers the methodology of assessing the possibilities of fulfillment of customer requirements as an element of end-to-end management of business processes at the enterprise. With the help of general scientific and special economic and statistical methods, such as analysis, synthesis and comparison, the key control points of the business process man- agement system, where different management approaches to risk analysis are applied, are de- termined. The trends characteristic of the current state and development of risk analysis methods are highlighted, their advantages and disadvantages are established. Systemic and complex approaches are applied to the studied phenomena and processes. Results. In the process of the conducted analysis the deficit of attention to the application of methods of business process risk management at the stage of pre-contract work was found out. Within the framework of the concept of risk-oriented thinking, which is at the heart of modern management systems, the article highlights the applied approaches to risk analysis, the algorithm of realization of expert risk analysis at the enterprise is proposed, the types of requirements used for evaluation are defined. The indicator of feasibility of customer require- ments at the enterprise is calculated, the criteria for making a management decision based on the results of the assessment are revealed, The variants of auxiliary documentation developed in the course of the assessment are given. Thus, the developed methodology acts as a control point at the initial stage of realization of the algorithm of end-to-end management of business processes of the enterprise.Conclusions. The proposed methodological toolkit for assessing the ability to fulfill customer requirements is a preventive measure to eliminate risks before the delivery of products / ser- vices. The procedure and peculiarities of the methodology application are given on the example of analyzing the level of feasibility of the customer’s requirements of the gas industry com- pany, Realizing the service of construction of main gas pipelines and compressor stations. The developed methodical toolkit allows to increase the level of quality of realization of business processes and the degree of their transparency, to provide more balanced management decisions, to improve conditions for contract conclusion, to reduce the number of discrepancies in the activity of enterprises of gas and other industrial branches.

Многокритериальная оценка антропогенного риска опасности электроустановок на основе имитационного моделирования

Risk management in a human-machine system is considered. The basic models and methods of decision-making, “man - electrical installation - environment” are presented. The method of risk analysis is considered. An expert software complex is proposed that implements the risk assessment of electrical installations. Keywords: HUMAN-MACHINE SYSTEM, RISK MANAGEMENT, ELECTRICAL INSTALLATION, MULTICRITERIA ANALYSIS, RISK ANALYSIS METHOD, “BOW TIE”, FIRE RISK OF ELECTRICAL INSTALLATIONS, SIMULATION MODEL

Evaluation of Health Risks Attributed to Toxic Trace Elements and Selenium in Farmed Mediterranean Mussels from Türkiye and Bulgaria.

Farmed mussels accumulate contaminants from their production environment rather than releasing them into water. This study reveals potential health risks associated with selenium, cadmium, mercury, and lead resulting from the consumption of mussels (Mytilus galloprovincialis) cultured along the coasts of Türkiye and Bulgaria. The concentrations of Se and toxic trace metals were measured by inductively coupled plasma mass spectrometry (ICP-MS). The detection limits (LOD) were 0.100, 0.015, 0.025, and 0.180µg/kg for Se, Cd, Hg, and Pb, respectively. The mean Se concentrations were between 1.305 and 1.957µg/g, and toxic metals were below the maximum limits. Due to Turkish and Bulgarian consumers' limited mollusk consumption, mussels could only provide a maximum of 7.35% of the daily Se need. THQ and TTHQ of Se, Cd, and methyl-Hg were below 1, indicating that farmed mussels were safe for consumption. Percent PTWI values were calculated only for Cd and MeHg, as the PTWI value for Pb was discarded by the authorities and not determined for Se. Accordingly, weekly mussel consumption did not pose any risks. The margin of exposure approach was used to evaluate Pb intake. MOE-SBP and MOE-NE were significantly higher than 10, designating no significant health risks. Long-term consumption of mussels also does not pose a carcinogenic risk regarding the TR index calculated between 10-5 and 10-6 for Pb. Positive HBVSe (10.13-37.27) indicated that Se in mussels overcame Hg-related potential health concerns. Consequently, mussels grown in Türkiye and Bulgaria did not pose a risk for human consumption, based on current risk analysis methods.

HAZard and OPerability Study Analysis as a Semi-Automatic Approach

Risk analysis is crucial in industrial conception. HAZOP is the top risk analysis method for the oil and gas sector. This paper presents a semi-automatic method to address HAZOP's limitations and produce automatic results. The method uses a knowledge base, initially filled with gas liquefaction data, and is enhanced with subsequent case studies. An inference engine processes this data to conduct a HAZOP study. Propagation rules identify potential deviation paths, enabling risk analysis and consequence prediction based on the knowledge base. This method uniquely illustrates deviation paths and introduces nodes along these paths for further study. The findings derive from dynamic knowledge of each system in the knowledge base and can be reviewed and amended by experts.

Dynamic risk analysis for oil and gas exploration operations based on HFACS model and Bayesian network

Oil and gas exploration (OGE) is an important part of the petroleum industry. How to predict and prevent risks of OGE accidents in a targeted way is still a challenge, while few researchers have focused on this issue because of the lack of data from the worksite. Therefore, the accident cases for decades of years in a globally operated OGE company are collected as a basis, a dynamic risk analysis method combining the human factors analysis and classification system (HFACS) and the Bayesian network (BN) has been proposed in this article. First, identify the accident cases, analysis, and divided the risk factors into four levels and 27 classification categories, and setup a HFACS-OGE model. Then, map the factors to the BN and identify the correlation of the secondary level factors. Finally, setup a BN model with the Genie software. Through posterior probability analysis and sensitivity analysis, we conclude the major and sensitive factors leading to OGE accidents. According to the conclusion, administrators could decide on corresponding management and control methods. This method can hopefully provide an effective quantitative basis for the identification and prediction of the factors that may lead to OGE accidents.

Safety Risk Analysis Optimization Using Fuzzy: A Literature Review

Risk analysis is the procedure to identify risks to the surrounding environment, especially in the workplace. There are several methods for analyzing risk. Nowadays, many risk analysis methods are integrated with optimization methods, such as fuzzy. This approach is used to optimize the results of risk analysis. This study aims to investigate the development of collaboration between risk analysis methods and fuzzy in the industrial sector and research that can be carried out in the future. The authors collected 500 articles from Dimensions.ai between 2018 and 2023 and evaluated the references obtained with the bibliometric analysis tool. The authors analyzed the dataset obtained based on the countries that conducted the most research on safety risk analysis optimization and collaboration, themes that were widely used, the themes distribution, and the relationship between existing themes. The Results show that China has published many studies in collaboration with other countries. Research themes that use risk analysis methods are widely used in human assessment where it can be seen in the keywords. Currently, there has been a lot of research on risk assessment integrated with fuzzy and humans. For future research, fuzzy approaches and risk analysis can be integrated with other accident analysis methods. Keywords: Bibliometric, Fuzzy, Literature Review, Risk Analysis, Risk Assessment