Operational Risk Research Articles

Vibration and pressure pulsation elimination in a reciprocating compressor suction system using an acoustic filter

High vibration poses significant safety and operational risks to compressor components. This study presents a thorough investigation of the root causes analysis and corrective actions to resolve vibration-induced failures faced on the suction system of a reciprocating compressor. Excessive pressure pulsations in the suction bottle and strong mechanical coupling between the cylinders and suction bottle due to high cylinder gas forces were identified as the root causes of vibration-induced failure of the suction system. The proposed solutions to eliminate this problem were implemented by splitting the suction bottle into two parts and making one bottle as an acoustic filter (Helmholtz resonator). The acoustic filter was optimized for the suppression of pressure pulsations above its Helmholtz frequency and also for the avoidance of acoustic and mechanical resonance. After applying the proposed solutions, the modified suction system achieved a 14.3-61.1% reduction in vibration and a 75.56% reduction in peak-to-peak pressure pulsation for the compressor operating at 1000 rpm. The processing capacity of the compressor has been increased by 6.82%. An acoustic filter is an effective low-cost technical measure for reduction of pressure pulsation and fluid-induced vibration, which greatly increases the reliability of the entire compressor system.

Analisis Faktor Yang Mempengaruhi Keselamatan Operasional Kapal di Pelabuhan Merak

The study, titled "Analysis of Factors Affecting Safety at Merak Port," aims to identify and analyze key factors influencing operational safety at Merak Port. This port is a strategic route linking Java and Sumatra, serving millions of passengers and vehicles annually. However, high activity levels and operational complexity present significant safety challenges. This research employs a qualitative case study approach, combining interviews, field observations, and document analysis. Quantitative data were also collected via questionnaires distributed to operators, workers, and passengers. Findings reveal that human factors, weather conditions, and infrastructure are critical to safety. Incidents in 2023, such as the KMP Royce 1 fire and a crane accident, underscore the need for enhanced risk management and infrastructure maintenance. The study concludes that gaps in safety training and compliance with safety procedures are key challenges. Additionally, extreme weather and suboptimal heavy equipment conditions increase operational risks. Recommendations include improving safety management practices, enhancing infrastructure maintenance, and providing regular training for workers to strengthen operational safety at Merak Port.

Corporate Risk Disclosure Practice and Financial Performance of Listed Industrial Goods Firms in Nigeria

In recent years, corporate risk disclosure has gained increasing attention in corporate governance discourse due to its potential impact on financial performance. The need for transparency in reporting risks has become more critical, particularly in the industrial goods sector, which is often characterized by high operational and financial risks. This study examined the influence of corporate risk disclosure on the financial performance of listed industrial goods firms in Nigeria, a sector known for high levels of operational and financial risk. It specifically assessed how financial and operational risk disclosures affect financial performance. This study employed expo-facto research design. The study population consisted of 13 industrial goods firms listed on the Nigerian Exchange Group (NGX) as of 31st December 2023. Census sampling was applied to include the entire population. Data were collected from annual reports and corporate governance disclosures were analysed with descriptive statistics and feasible generalised least squares regression analysis. The findings found that while financial risk disclosure positively and significantly influences financial performance, operational risk disclosure has a negative but significant effect. These outcomes suggest that financial transparency boosts investor trust and confidence, enhancing financial performance, whereas disclosing operational risks may reduce investor confidence due to concerns about operational stability and profitability. This study concluded that corporate risk disclosure demonstrated a significant role in influencing financial outcomes, yet its effect varies based on the type of risk disclosed. In line with empirical findings of this study, it was recommended that firms should balance transparency with discretion by selectively disclosing operational risks that have been mitigated or managed, reducing the potential for investor concerns over operational vulnerabilities.

Impact of Geographic Location on Risks of Fintech as a Representative of Financial Institutions

The activities of contemporary financial institutions require significant geographic expansion. Even the increased level of industry digitalisation does not minimise the importance of the physical assets of financial institutions. The environmental factors specific to each geographic region can significantly influence the efficiency of operations of financial institutions. The goal of the article is to determine the impact of the geographic location of physical assets via environmental risks affecting the other risks of fintech as a representative of financial institutions. The impact is determined by the employment of the PLS-SEM model implemented in SmartPLS 4.0 software. The model determines the impact of environmental risks on governance risks, operational risks, human resources and safety risks, ICT risks, compliance risks, and strategic risks. These groups of risks form the latent variables, which comprise the experts’ estimation of threats and vulnerabilities impacts and their likelihoods. After testing five hypotheses, two of them were supported—environmental risks impact human resources safety risks and operational risks.

Country risk mapping in a changing world—comparative survey on academic research and industrial practices

AbstractIn an era marked by rapid geopolitical shifts, persistent pandemics, and escalating climate threats, the imperative to transcend traditional country risk mapping methodologies has never been more critical. This study embarks on a comprehensive examination of the efficiency of current academic and industrial approaches to mapping the multifaceted country risks. By proposing a structured risk mapping framework that incorporates seven pivotal risk categories as Political Risk, Institutional Risk, War and Armed Conflict Risk, Public Security Risk, Socioeconomic Risk, Ecological Threat Risk, and Infrastructure Risk, the research seeks to foster a more nuanced understanding of how different organizations assess and prioritize these risk factors. Employing a dual approach that includes a thorough literature review and an extensive industry survey, and a detailed analysis of each of the seven risk category by juxtaposing relevant academic insights with industry practices, this study examines the discrepancies between academic theories and practical applications in country risk mapping. It reveals underestimate country risk factors, inadequate risk categorization granularity, inconsistencies in risk prioritization, terminological mismatches, and a need for a more integrated and holistic approach to country risk mapping. The paper concludes by proposing future research directions that aim to refine country risk mapping methodologies. It advocates a forward-looking perspective that adequately addresses the complexity and inter-connectivity of global operational risks.

Evaluating the Role of ISO Standards in Enhancing the Performance of Medical Laboratories

The role of ISO standards in enhancing the performance of medical laboratories has become increasingly significant in ensuring quality and reliability in healthcare services. This review evaluates the impact of ISO standards, particularly ISO 15189, on the operational efficiency, diagnostic accuracy, and risk management of medical laboratories. It highlights the key components of these standards, including quality management systems, personnel competence, and continuous improvement, and examines their contributions to patient safety and institutional credibility. The article also explores the challenges of implementing ISO standards, such as financial constraints and resistance to change, and proposes strategies to overcome these barriers. The findings underscore the importance of ISO standards in promoting a culture of quality and innovation within medical laboratories, ultimately improving healthcare outcomes.

A Roadmap to Systematic Review: Evaluating the Role of Data Networks and Application Programming Interfaces in Enhancing Operational Efficiency in Small and Medium Enterprises

The adoption of Data Networks and Application Programming Interfaces (APIs) has become crucial for small and medium enterprises (SMEs) to streamline operations, improve efficiency, and reduce costs. However, SMEs often face challenges such as resource limitations and security vulnerabilities, which hinder their ability to fully leverage these technologies. This systematic review examines the role of Data Networks and APIs in enhancing operational efficiency within SMEs, focusing on key metrics such as speed, cost reduction, scalability, and security challenges. Following PRISMA 2020 guidelines, we conducted a systematic search across multiple databases including Web of Science, Scopus, IEEE Xplore, and Google Scholar. Studies published between 2014 and 2024, focused on SMEs, and addressing the role of Data Networks and APIs in operational efficiency were included. A total of 49 studies met the inclusion criteria and were analyzed for key outcomes related to operational efficiency, cost-effectiveness, and security risks. The review found that Data Networks and APIs significantly improve operational efficiency by increasing process speed (12% increase), reducing operational costs (8% reduction), and enhancing overall productivity. However, security challenges, particularly related to API vulnerabilities, were a major concern, with cyberattacks on APIs increasing by 400% in Q1 2023 alone. Despite these risks, the benefits of implementing Data Networks and APIs in SMEs, particularly in terms of scalability and real-time data processing, were evident across industries. Data Networks and APIs offer substantial improvements in operational efficiency for SMEs, although security remains a significant challenge. Future efforts should focus on developing security frameworks tailored to SMEs while maintaining the operational benefits of these technologies. Further research is needed to explore scalable and secure API models for SMEs.

Application of Mind Map and TRIZ to an Advanced Air Mobility System for Post-Disaster Response

In this article, an Advanced Air Mobility (AAM) platform focused on search and rescue applications is discussed and analyzed from a systems thinking perspective. By applying two systems thinking tools, namely Mind Map and TRIZ, the strong interactions within the constituent parts that make up the system’s whole are examined with the aim of providing a comprehensive roadmap for a proposed Advanced Air Mobility Post-Disaster Response (AAMPDR) system. Furthermore, two problems are discussed to demonstrate the application of the TRIZ technique. The first is in regards to a clause in the AGL rule that could present operational risks to the AAM’s airframe, while the second relates to a potential conflict ensuing from the advent of the 5G C-band and its effect on the AAM altimetry. The resulting solutions to resolve these conflicts using this same technique are also discussed, firstly by taking into account the mean sea/water level as a reference for vertical height within the provisions of the Federal Aviation Regulation requirements, and secondly by applying segmentation of the mission profile as well as a multi-stage frequency designation for each segment depending on a threshold vertical distance. Finally, this study demonstrated that Mind Map and TRIZ can be effective techniques in the early stages of conceptual model development for an AAM system applied to post–disaster response. Furthermore, that the contradictions tool of TRIZ can also be utilized in resolving those potential conflicts identified in relation to the system of interest. To this end, this paper proposes the amendment of the current Part 107 rule to include the term Above Mean Sea (or Water) Level (AMS/WL), a critical yet missing piece of the system requirements that engineers should take into account in future AAM system designs.

Design and Visual Implementation of a Regional Energy Risk Superposition Model for Oil Tank Farms

Ensuring the safety of oil tank farms is essential to maintaining energy security and minimizing the impact of potential accidents. This paper develops a quantitative regional risk model designed to assess both individual and societal risks in oil tank farms, with particular attention to energy-related risks such as leaks, fires, and explosions. The model integrates factors like day–night operational variations, weather conditions, and risk superposition to provide a comprehensive and accurate evaluation of regional risks. By considering the cumulative effects of multiple hazards, including those tied to energy dynamics, and the stability and validity of the model are researched through Monte Carlo simulations and case application. The results show that the model enhances the reliability of traditional risk assessment methods, making it more applicable to oil tank farm safety concerns. Furthermore, this study introduces a practical tool that simplifies the risk assessment process, allowing operators and decision-makers to evaluate risks without requiring in-depth technical expertise. The methodology improves the ability to safeguard oil tank farms, ensuring the stability of energy supply chains and contributing to broader energy security efforts. This study provides a valuable method for researchers and engineers seeking to enhance regional risk calculation efficiency, with a specific focus on energy risks.

Development of a Machine stereo vision-based autonomous navigation system for orchard speed sprayers

In orchards, radio frequency scintillation caused by high vegetation density can hinder the effectiveness of machinery auto guidance based on the Global Navigation Satellite System (GNSS). Signal interference not only leads to poor quality of machine operation but can also pose operational risks. In this work, we propose an alternative trajectory positioning system to supplement traditional GNSS-based navigation for machinery used in orchards. The aim of this research was to develop a deep learning machine stereo vision guidance system onboard an orchard speed sprayer. The developed system combines a collision avoidance methodology along with deep learning-driven machine vision for interrow positioning and a dead reckoning set of rules for alternating U-turns. The developed methodology was tested in 4 rows of an artificial orchard. The results show that it is possible for the embedded EfficientDet target detection algorithm to guide the equipment at 1, 1.5 and 2 km × h−1 with minimum average root-mean-square errors (RMSEs) of 0.24 m, 0.20 m, and 0.31 m, respectively. When the system navigation was performed using YOLOv7, the minimum average RMSEs for each row were 0.40 m, 0.48 m, and 0.43 m, respectively, for the abovementioned speeds. The U-turn by dead reckoning showed minimum average RMSE values of 0.56 m, 0.22 m, and 0.35 m for row navigation based on EfficientDet at 1, 1.5 and 2 km × h−1, respectively. For YOLOv7-based navigation in rows, the minimum average RMSE values at these speeds were 0.35 m, 0.81 m, and 0.44 m, respectively. This study contributes to the field by proposing an alternative navigation system for orchard machines that operates without the limitations associated with GNSS. In addition, our proposed guidance methodology introduces an RGB-D collision avoidance system with a demonstrated safety capacity for navigation under real scenario conditions.

IoT Integration of Failsafe Smart Building Management System

This research investigates the energy consumption of buildings managed by traditional Building Management Systems (BMSs) and proposes the integration of Internet of Things (IoT) technology to enhance energy efficiency. Conventional BMSs often suffer from significant energy wastage and safety hazards due to sensor failures or malfunctions. These issues arise when building systems continue to operate under unknown conditions while the BMS is offline, leading to increased energy consumption and operational risks. The study demonstrates that integrating IoT systems with existing BMSs can substantially improve energy efficiency in smart buildings. The research involved designing a system architecture prototype, performing MATLAB simulations, and a real-life case study which revealed that IoT devices are effective in reducing energy waste, particularly in Heating, Ventilation, and Air Conditioning (HVAC) systems and lighting. Additionally, an auxiliary bypass system was incorporated in parallel with the IoT system to enhance reliability in the event of IoT system failures. Preliminary findings indicate that the integration of IoT systems with traditional BMSs significantly boosts energy efficiency and safety in smart buildings. Simulation results reveal an hourly average power savings of 36.8 kw with the integrated failsafe model for all scenarios. This integration offers a promising solution for advancing energy management practices and policies, thereby improving both operational performance and sustainability in building management.

Privacy Matters: How Academic Law Libraries Can Mitigate Privacy Risks Associated with Controlled Digital Lending

Academic law libraries are obligated to protect library patron privacy in accordance with professional standards, such as the AALL Ethical Principles, as well as all applicable laws. Because controlled digital lending enables patrons geographically distant from the law library to access library resources, the privacy laws of many jurisdictions can apply. Two laws requiring special consideration are FERPA and the GDPR, and noncompliance with them carries both financial and reputational risk for a law school. Academic law libraries that implement controlled digital lending can mitigate associated privacy risks by incorporating privacy compliance into the design phase of the initiative. The design team should include members with both legal and technical privacy expertise to ensure the program complies with all applicable state, federal, and foreign privacy laws and is designed with privacy in mind, employing data minimization and process automation to reduce operational privacy risk.

Reliable ships: A fuzzy FMEA based risk analysis on four-ram type hydraulic steering system

Hydraulic steering systems are vital for safe and efficient navigation in maritime vessels. Failures in these systems can pose serious operational and safety risks. This study uses fuzzy Failure Modes and Effects Analysis to assess risks in a four-ram hydraulic steering system commonly used in ships. A total of 47 failure modes of the hydraulic system were identified and analyzed using domain expert input to improve the accuracy of the risk assessment. Fuzzy input and output variables are developed, followed by the construction of membership functions, a rule base, and an inference engine to compute the Fuzzy Risk Priority Numbers (FRPN). Based on the calculated FRPN values, all failure modes are ranked, with the top ten highlighted and detailed in the Discussion chapter, which concludes with recommendations for control and prevention. It was found that the most critical failure mode is “insufficient system pressure” due to defective hoses, pipes, and connectors (FRPN 6.59). The results of this study provide practical benefits to the maritime industry by enabling more precise risk identification and mitigation strategies. This approach facilitates effective maintenance scheduling, enhances system reliability, reduces operational downtime and maintenance costs, and ultimately improves the safety and efficiency of ship navigation systems.

Reducing Safety Risks in Construction Tower Crane Operations: A Dynamic Path Planning Model

Tower cranes are the most used equipment in construction projects, and the path planning of tower crane operations directly affects the safety performance of construction projects. Traditional tower crane operations rely on only the driving experience and manual path planning of crane operators. Poor judgement and bad path planning may increase safety risks and even cause severe construction safety accidents. To reduce safety risks in construction tower crane operations, this research proposes a dynamic path planning model for tower crane operations based on computer vision technology and dynamic path planning algorithms. The proposed model consists of three modules: first, a path information collection module preprocessing the video data to capture relevant operational path information; second, a path safety risk evaluation module employing You Only Look Once version 8 (YOLOv8) instance segmentation to identify potential risk factors along the operational path, e.g., potential drop zones and the positions of nearby workers; and finally, a path planning module utilizing an improved Dynamic Window Approach for tower cranes (TC-DWA) to avoid risky areas and optimize the operational path for enhanced safety. A prototype based on the theoretical model was constructed and tested on actual construction projects. Through experimental scenarios, it was found that each tower crane operation poses safety risks to 3–4 workers on average, and the proposed prototype can significantly reduce the safety risks of dropped loads from tower crane operations affecting ground workers and important equipment. A comparison between the proposed model and other regular algorithms was also conducted, and the results show that compared with traditional RRT and APF algorithms, the proposed model reduces the average maximum collision times by 50. This research provides a theoretical model and a preliminary prototype to provide dynamic path planning and reduce safety risks in tower crane operations. Future research will be conducted from the aspects of multiple device monitoring and system optimization to increase the analysis speed and accuracy, as well as on human–computer interactions between tower crane operators and the path planning guidance model.

Sustainable Financial Strategies: Analyzing the Role of ESG in Corporate Financial Performance and Risk Management

The growing emphasis on sustainability in the corporate sector has elevated the importance of Environmental, Social, and Governance (ESG) factors in shaping financial strategies. This study investigates the impact of ESG integration on corporate financial performance and risk management. By analyzing a comprehensive dataset of firms across various industries, the research explores the relationship between ESG practices and key financial metrics, including profitability, market valuation, and risk exposure. The findings reveal that companies with robust ESG strategies exhibit improved financial resilience, enhanced investor confidence, and reduced operational risks. Additionally, the study identifies sector-specific variations in ESG's effectiveness, emphasizing the need for tailored approaches to sustainable financial strategies. This research contributes to the discourse on sustainable finance, offering actionable insights for corporate leaders, investors, and policymakers aiming to align financial objectives with long-term sustainability goals.

Value Research of HYBE Entertainment

Abstract: With the development of economic globalization, Korean entertainment companies occupy an increasingly important position in global entertainment. Under the fierce competition among Korean entertainment companies, HYBE has created several standouts K-pop groups in the past few years, thereby breaking the pattern of the three major entertainment companies, YG, SM, and JYP. HYBE has attracted a predominantly youthful crowd mainly with its unique music aesthetic, versatile group styles, and frequent returns, and has made efforts to expand its presence from the Korean domestic market into the U.S. market, where it has become a major player. It is also trying to expand its sales from the Korean domestic entertainment market to overseas markets, mainly the United States. Despite the controversy surrounding some of HYBE's groups, which has raised the company's operational risk, the company's groups have gradually gained a significant position in global entertainment. This article analyzes the value of HYBE from the perspectives of profitability and business analysis, describes the current state of the company's development, and explores the reasons for its steady growth.

Evaluating the Impact of Technological Innovations on Operational Risk Management in Financial Institutions

This study evaluates the impact of technological innovations on operational risk management in financial institutions, focusing on how emerging technologies influence risk identification, mitigation, and management processes. Employing a qualitative approach through literature review and library research, this study synthesizes recent findings on the integration of technologies such as artificial intelligence (AI), blockchain, big data analytics, and cloud computing within financial risk frameworks. Findings indicate that these technologies offer substantial improvements in risk management by enhancing accuracy in risk detection, increasing response speed, and reducing human error. AI and machine learning models, for instance, are shown to enable real-time monitoring and predictive analytics, allowing institutions to identify potential risks before they materialize. Blockchain technology improves transparency and security in transaction processing, thereby mitigating fraud-related risks. Big data analytics provides insights into customer behavior, which can help detect anomalous activities and improve decision-making. However, the study also highlights challenges, including the need for robust cybersecurity measures, potential regulatory gaps, and skill shortages in handling complex technological systems. This study provides insights for financial institutions aiming to balance technological integration with effective risk management, underscoring the need for comprehensive frameworks that align technological advancements with regulatory compliance and organizational capability. Future research should focus on empirical studies assessing the long-term implications of these technologies on risk management efficacy in diverse financial settings.

Development of an Integrated Surveillance System to Improve Preparedness for Arbovirus Outbreaks in a Dengue Endemic Setting: Descriptive Study.

Dengue fever, transmitted by Aedes aegypti and Aedes albopictus mosquitoes, poses a significant public health challenge in tropical and subtropical regions. Dengue surveillance involves monitoring the incidence, distribution, and trends of infections through systematic data collection, analysis, interpretation, and dissemination. It supports public health decision-making, guiding interventions like vector control, vaccination campaigns, and public education. Herein, we report the development of a surveillance system already in use to support public health managers against dengue transmission in Foz do Iguaçu, a dengue-endemic Brazilian city located in the Triple Border with Argentina and Paraguay. We present data encompassing the fieldwork organization of more than 100 health agents; epidemiological and entomological data were gathered from November 2022 to April 2024, totalizing 18 months of data collection. By registering health agents, we were able to provide support for those facing issues to fill their daily milestone of inspecting 16 traps per working day. We filtered dengue transmission in the city by patient age, gender, and reporting units, as well as according to dengue virus serotype. The entomological indices presented a strong seasonal pattern, as expected. Several longtime established routines in Foz do Iguaçu have been directly impacted by the adoption of Vigilância Integrada com Tecnologia (VITEC). The implementation of VITEC has enabled more efficient and accurate diagnostics of local transmission risk, leading to a better understanding of operational activity patterns and risks. Lately, local public health managers can easily identify hot spots of dengue transmission and optimize interventions toward those highly sensitive areas.

Deep learning-based multilabel compound-fault diagnosis in centrifugal pumps

In this study, the issue of centrifugal pumps used in marine engineering is addressed, as they are susceptible to malfunction owing to long-term operation in highly corrosive seawater and extreme weather conditions, resulting in operational interruptions and safety risks. We propose a high-precision intelligent fault-diagnosis method for multiple fault types based on deep learning. In this method, continuous wavelet transform is firstly employed to extract signal time–frequency domain features. Subsequently, the Swin transformer model is used to process the wavelet time–frequency images converted from signals. Finally, multilabel classification methods are combined to diagnose various complex faults. The effectiveness of the proposed method is validated using a dataset obtained from simulation experiments pertaining to centrifugal-pump faults. The results show that the proposed method achieves 100% accuracy in diagnosing 27 types of faults and provides excellent diagnosis even under limited compound-fault samples, thus offering an efficient and practical method for fault diagnosis in centrifugal pumps used in marine engineering.

FEATURES OF OPERATIONAL RISK MANAGEMENT IN THE REPUBLIC OF ARMENIA

Any type of business activity is not free from the formation of risks. Banking is also no exception. For banking business, it is important not to avoid risks in general, but to anticipate the consequences of risks and minimize their consequences. This article presents the main mechanisms for containing operational risks of banks, taking into account possible scenarios and changes. The goal is to find out how risks are managed and the possible limits of risk indicators. Forecasts of key operational risk indicators are based on banking experience and historical data, which makes it possible to monitor potential risk thresholds. According to the author, with precise management, the latter can help differentiate and limit potential risks.