Safety Risk Management System Research Articles

SAFETY RISK MANAGEMENT AS RELATED TO AIRPORT PASSENGER EXPERIENCE AT MANILA INTERNATIONAL AND DOMESTIC AIRPORTS

This paper analyzed how employee attitudes towards safety risk management, perceived competence of ground staff in dealing with unruly passenger behavior, and perceived waiting time for airport security screening service can influence aviation safety performance and passenger experience at the airports operated by the Manila International Airport Authority. Descriptive survey, descriptive correlation, and thematic analysis methods were used to analyze the data. The results of the analysis showed that there is a weak, positive relationship between employees attitudes towards safety risk management and perceived competence of ground staff in dealing with unruly passenger behavior, however this correlation is not statistically significant. Additionally, there is a weak, positive relationship between perceived airport passenger experience and employee’s attitudes towards safety risk management, but this is not statistically significant. Furthermore, there is a moderate, negative correlation between perceived airport passenger experience and perceived waiting time for security screening service, which is statistically significant. The findings of the study suggest that employee attitudes towards safety risk management have no significant impact on the overall experience of airport passengers. In order to improve the airport passenger experience, the Manila International Airport Authority should implement a comprehensive safety training program for all airport staff, develop a safety risk management system and procedure manual, provide regular training and refresher courses for ground staff, and implement comprehensive customer feedback and satisfaction surveys. KEYWORDS: safety risk management, perceived competence of ground staff in dealing with unruly passenger behavior, perceived waiting time, airport passenger experience

Studi Kasus: Analisis Pengendalian dan Manajemen Risiko Kesehatan dan Keselamatan Kerja di Rumah Sakit (K3RS)

Risk management as a process for analysis, identification, evaluation, control, and overcoming risks faced by organizations or Hospital Agencies. This control is carried out by implementing Hospital Work Safety Health (HWSH). The purpose of this case study is to find out the analysis of occupational health and safety risk control and management in hospitals. The method in the case study is by implementing the Hospital Occupational Health Safety Risk Management system (HOH SRMS). Hospital management system as a whole which includes the organizational structure, planning, responsibilities, implementation, procedures, processes and resources needed for the development, implementation, achievement and maintenance of occupational health and safety policies. The results of the analysis state that the Occupational Safety & Health (OSH) plan in the hospital is the key as a reference for performance in health worker safety with risk identification, risk analysis, risk assessment, implemented solutions, and risk monitoring. It can be concluded that risk management in hospitals is a comprehensive control activity in the form of identification and evaluation to reduce the risk of injury and loss to patients, hospital employees and to improve the quality of health services. Hospital Agencies have the duty and obligation to identify and control thoroughly both in the service area, infectious area and hospital environment area. HOH SMRS as an important aspect designed to prevent negative impacts on business processes or minimize financial loss. It is hoped that the hospital will carry out risk management by identifying weaknesses in the system and correcting these weaknesses.

Security Risk Management System for the Construction and Operation of Smart Port Area Based on BP Neural Network Algorithm

With the construction of smart cities, smart ports are developing rapidly, providing favorable conditions for enhancing port competitiveness, promoting industrial upgrading, and economic transformation. With the continuous progress of society and science and technology, the safety risks of intelligent ports are also increasing. In order to better address these risks, it is necessary to establish a stable and efficient management system. This paper applies data mining and fuzzy control theory technologies for large-volume, high-precision real-time information collection, based on the research of the BP neural network algorithm. By establishing and analyzing a safety risk management system model based on the BP multilayer neuron network, it provides a rationality evaluation method and design concept. After designing the safety risk management system, this paper conducts a performance test on the system. The test results show that through optimization, the accuracy, generalization ability, and reliability of the model can be improved. Its accuracy is as high as 92% or more, fully demonstrating the system's reliability and superiority!

Safety Risk Assessment Using a BP Neural Network of High Cutting Slope Construction in High-Speed Railway

High-speed railway construction is extending to mountainous areas, and the harsh environment and complex climate pose various risks to the slope construction. This seriously threatens human lives and causes huge economic losses. The existing research results on the construction safety risks of high cutting slope construction in HSRs are limited, and a complete set of safety risk assessment processes and methods has not yet been formed. Therefore, in this study, we aimed to develop a safety risk assessment model, including factor identification and classification and assessment data processing, to help project managers evaluate safety risks in high cutting slope construction. In this study, comprehensive identification of high cutting slope construction safety risks was carried out from three dimensions, risk technical specification, literature analysis, and case statistical analysis, and a list of risk-influencing factors was formed. Based on the historical data, a high side slope risk evaluation model was established using a BP neural network algorithm. The model was applied to the risk evaluation of HF high cutting slopes. The results show that the risk evaluation level is II; the main risks are earthwork excavation method, scaffolding equipment, slope height, slope rate, groundwater, personnel safety awareness, and construction safety risk management system. Finally, a case study was used to verify the proposed model, and control measures for safety risks were proposed. Our findings will help conduct effective safety management, add to the knowledge of construction safety risk management in terms of implementation, and offer lessons and references for future construction safety management of HSR.

Model of Decision Making Using Artificial Neural Networks

The article makes theoretical generalizations and provides promising solutions to the scientific and theoretical problem of human factor assessment in the safety management system based on predicting the occurrence of an adverse event that may involve risks in aviation activities. The current state and prospects of developing a proactive approach to the safety risk management system and the place of the human factor in identifying sources of danger are analyzed. Generalization and current prospects for the use of artificial neural networks for forecasting tasks and their place in the decision-making system, which allowed to identify unresolved issues, justify appropriate approaches to its solution, in particular to assess the possibility of adverse events of the cardiovascular system . A method for constructing an artificial neural network for forecasting biological risk objects based on a theoretical approach using a decision-making model has been developed. The use of artificial neural networks allowed to develop a model for predicting the occurrence of a negative event of sudden disruption of the functional state of the cardiovascular system of the operator.

Whole Risk Assessment System and Management System of Urban Road Tunnel Operation Stage

The index system and evaluation method of safety assessment in the operation stage are established to realize the safety risk assessment and management in the operation stage of urban road tunnel. The index scores are obtained from the fuzzy comprehensive evaluation model, and the overall safety risk grade is derived. In view of the index level with an evaluation level greater than or equal to Ⅲ, special risk assessment is conducted, and safety risk solving measures are introduced. A corresponding safety risk management system platform for urban tunnel operation stage is developed on the basis of the results. The results and application of this study have a certain reference value for managing tunnel informatization based on safety risk management.

Efficacy of a proactive health and safety risk management system in the fire service

BackgroundThis study evaluated the efficacy of a fire department proactive risk management program aimed at reducing firefighter injuries and their associated costs.MethodsInjury data were collected for the intervention fire department and a contemporary control department. Workers’ compensation claim frequency and costs were analyzed for the intervention fire department only. Total, exercise, patient transport, and fireground operations injury rates were calculated for both fire departments.ResultsThere was a post-intervention average annual reduction in injuries (13%), workers’ compensation injury claims (30%) and claims costs (21%). Median monthly injury rates comparing the post-intervention to the pre-intervention period did not show statistically significant changes in either the intervention or control fire department.ConclusionsReduced workers’ compensation claims and costs were observed following the risk management intervention, but changes in injury rates were not statistically significant.

Applying Cyber Risk Management To Medical Device Design

Recent U.S. Food and Drug Administration (FDA) guidance recognizes that today’s medical devices face a host of cyberthreats. Medical device manufacturers, in turn, face the need to assess and mitigate cyber risks. By combining the cyber risk framework of the National Institute of Standards and Technology (NIST) with the existing International Organization for Standardization (ISO) 14971 Safety Risk Management (SRM) process, manufacturers can leverage proven best practices to make their devices safer and more effective. The cyberthreat to medical devices is based on two factors. First, increasingly faster and more efficient processors now enable full operating systems to run on small implant devices. Previously, only dedicated firmware could have been used. Second, modern hardware can readily connect to networks using wired and wireless protocols. Both factors offer markedly increased capability for patients, physicians, caregivers, and healthcare technology management (HTM) professionals, at the cost of opening unforeseen and unintended doorways into a device. Opening unintended doorways can compromise medical devices in three major areas of cybersecurity: confidentiality, integrity, and availability. Confidentiality refers to preserving authorized restrictions on information access and disclosure, including means for protecting patient privacy and corporate proprietary information. Integrity means guarding against improper information modification or destruction and includes ensuring information nonrepudiation and authenticity. Availability is ensuring timely and reliable access to and use of information. As embedded medical devices grow in complexity and ability, an end-to-end cybersecurity framework is needed to ensure that they achieve the confidentiality, integrity, and availability required for successful operation. Cybersecurity concerns have factored into medical device design for some time, but additional attention has been focused on the topic by recent FDA communications, including a recent guidance document and a safety communication. These documents, however, lack clear instructions on what needs to be considered and tested—a comprehensive standard could be years away. To ensure safety and effectiveness and reduce exposure to liability, device manufacturers need to be proactive in defining and applying cybersecurity controls for their medical devices. The problem facing medical device development teams is complex; it involves securing a device against an ever-growing number of cybersecurity threats while balancing usability, performance, and safety. A viable approach Applying Cyber Risk Management To Medical Device Design

Rationale of genotoxicity testing of nanomaterials: Regulatory requirements and appropriateness of available OECD test guidelines

The development of an environmental health and safety risk management system for nanoscale particle-types requires a base set of hazard data. Accurate determination of health and environmental risks of nanomaterials is a function of the integration of hazard and exposure datasets. Recently, a nanoparticle risk assessment strategy was promulgated and the components are described in a document entitled “Nanorisk framework” (www.nanoriskframework.com). A major component of the hazard evaluation includes a proposed minimum base set of toxicity studies. Included in the suggested studies were substantial particle characterization, a variety of acute hazard and environmental tests, concomitant with screening-type genotoxicity studies. The implementation of well-accepted genotoxicity assays for testing nanomaterials remains a controversial issue. This is because many of these genotoxicity tests were designed for screening general macroparticle chemicals and might not be suitable for the screening of nanomaterials (even of the same compositional material). Furthermore, no nanoparticle-type positive controls have been established or universally accepted for these tests. Although it is the comparative results of the test material vs. the negative or vehicle control that forms the basis for interpreting the results and potency of test materials in genetic toxicology assays, the lack of a nanoparticle-type positive control questions the suitability of the tests to identify nanomaterials with genotoxic properties. It is also not possible to establish historical positive control ranges that would confirm the sensitivity of the tests. Although several genetic toxicology tests have been validated for chemicals according to the Organisation for Economic Co-operation and Development (OECD) test guidelines, the relevance of these assays for nanoparticulate materials remains to be determined. In an attempt to remedy this issue, the OECD has established current projects designed to evaluate the relevance and reproducibility of safety hazard tests for representative nanomaterials, including genotoxicity assays (i.e., Steering Group 3 – Safety Testing of Representative Nanomaterials). In this article, we discuss our past approaches and experience in conducting genotoxicity assays (1) for a newly developed ultrafine TiO2 particle-type; and (2) in a recent inhalation study, evaluating micronucleus formation in rat erythrocytes following exposures to engineered amorphous nanosilica particles. It seems clear that the development of standardized approaches will be necessary in order to determine whether exposures to specific nanoparticle-types are associated with genotoxic events. The appropriateness of available genotoxicity test systems for nanomaterials requires confirmation and standardization. Accordingly, it seems reasonable to conclude that any specific regulatory testing requirements for nanoparticles would be premature at this time.

Risk assessment modeling in aviation safety management

Safety risk management is important in aviation. This paper develops a quantitative model for assessing aviation safety risk factors as a means of increasing the effectiveness of safety risk management system by integrating the fuzzy linguistic scale method, failure mode, effects and criticality analysis principle, and as low as reasonably practicable approach. The model is developed by evaluating all related estimation factors based on their importance, how hazardous they are, their detectability, probability, criticality, and frequency. An empirical study demonstrates the modeling process.