Safety-related Accidents Research Articles

Exploring the Potential Use of Near-Miss Information to Improve Construction Safety Performance

Construction project management usually has a high risk of safety-related accidents. An opportunity to proactively improve safety performance is with near-miss information, which is regarded as free lessons for safety management. The research status and practice; however, presents a lack of comprehensive understanding on what near-miss information means within the context of construction safety management. The objective of this study is to fill in this gap. The main findings enrich the comprehensive understanding of the near-miss definition, the near-miss causation model, and the process of near-miss management. Considering that near-misses are more tacit and obscure than accidents, the process for near-miss management involves eight stages: discovery, reporting, identification, prioritization, causal analysis, solution, dissemination, and evaluation. The first three stages aim to make near-misses explicit. The other five are adopted to better manage near-miss information, compiled in a well-designed near-miss database (NMDB). Finally, a case study was conducted to show how near-miss information can be utilized to assist in construction safety management. The main potential contributions here are twofold. Firstly, corresponding findings provide a knowledge framework of near-miss information for construction safety researchers who can go on to further study near-miss management. Secondly, the proposed framework contributes to the guidance and encouragement of near-miss practices on construction sites.

Impacts of Lean Construction on Safety Systems: A System Dynamics Approach.

Lean construction has been viewed as an effective management approach for reducing the occurrence of no-value or destructive activities, such as wasting resources and safety-related accidents. However, few studies have systematically addressed how and to what extent lean construction practices influence construction safety. To bridge this gap, a conceptual model is developed and validated using a system dynamics approach. The construction system in this model comprises four sub-systems (i.e., environment system, equipment system, management system, and employee system). Data were collected from 448 projects in China. Simulations were conducted to determine the correlations between five types of lean tools and the four construction sub-systems. The results show that: (a) 5S management has significant positive impacts on the control of key locations and facilities at construction sites, and contributes to the mitigation of environmental impacts; (b) visual management can significantly improve safety compliance and safety management; (c) just-in-time management has significantly positive influences on the safety facilities layout and formulation of the safety plan; and (d) the Last Planner® System and conference management are effective in improving safety training and the implementation of the safety plan. These findings provide new insights into the use of lean construction for improving construction safety through the implementation of a targeted lean approach.

A Data-Driven Misbehavior Detection System for Connected Autonomous Vehicles

In a Connected and Autonomous Vehicle (CAV) system, some malicious CAVs may send out false information in vehicle-to-vehicle communication to gain benefits or cause safety-related accidents. Previous false data detection methods are not sufficient to meet the accuracy and real-time requirements. In this paper, we propose a data-driven misbehavior detection system (MDS) (running by each CAV) that checks the consistency between the estimated and actually reported driving state (i.e., velocity, acceleration, brake status, steering angle) of an alerting CAV. First, MDS predicts the driving state using Gaussian mixture model based Mixture Density Network incorporating Recurrent Neural Network that can catch the driving behavior patterns of a CAV. Second, MDS extends the existing Krauss traffic flow model and uses it to consider the overall traffic flow of the road to make the predicted driving state more accurate. Finally, for a given received alert, a CAV validates the alert by checking the consistency between the predicted and actually reported driving states of the alerting CAV. We conduct extensive simulation studies based on a real driving dataset we collected from 29 participants and the Simulator for Urban MObility (SUMO) traffic simulator. The experimental results show that the false information detection rate of the proposed MDS is higher than other existing systems in different alert scenarios.

Adaptive sparse representation based on circular-structure dictionary learning and its application in wheelset-bearing fault detection

Abstract Wheelset bearings are among the crucial elements of bogie frames used in high-speed trains. Wheelset-bearing fault detection can actively reduce or preclude safety-related accidents and realize condition-based maintenance in high-speed train service. Therefore, it is of great significance to automatically detect wheelset-bearing faults. Sparse representations based on circular-structure dictionary learning (SRCSDL) provide an excellent framework for extracting fault impact trains (FITs) induced by wheelset-bearing faults. However, the performance of SRCSDL on extracting FITs heavily relies on the selection of method-related parameters. A systematic method for selecting such parameters has not been reported in the literature. A novel fault detection method, adaptive SRCSDL (ASRCSDL), is therefore proposed in this paper. The effects of the selection of each SRCSDL parameter on extracting FITs are investigated. It was found that three parameters (the length of single set signals, the number of signal sets, and convergence error) can be fixed according to the characteristics of the SRCSDL algorithm. To adaptively tune the remaining three parameters, main frequency analysis is used to select the number of kernel functions, the number of maximum extreme values is employed to determine the length of the kernel function, and envelope spectra kurtosis-guided self-tuning algorithms are proposed to tune the target sparsity of SRCSDL. The proposed method is then validated using the simulated signals and bench and real-line tests.

SOCIAL ENREPRENEURSHIP: IMPACT OF OCCUPATIONAL HEALTH AND SAFETY (OHS) FACTORS ON WORKERS’ BEHAVIOR IN DIFFERENT CONSTRUCTION SECTORS IN OMAN

PURPOSE
 This paper critically analyzes and assesses the various factors of occupational health and safety (OHS), and elucidate the factors affecting construction workers’ behavior in different construction projects of Oman. It aims to create Occupational Health and Safety awareness in construction workers working for Social Entrepreneurs in Oman.
 DESIGN/METHODOLOGY/APPROACH
 Two hundred and fifty-two construction workers from various projects were selected based on a simple random sampling basis, and the data was collected through a well-defined questionnaire.
 FINDINGS
 The study shows that workers favor communication in the improvement of workers’ behavior in the industrial and infrastructure construction projects.Education and training help in capacity building and skills development and contributes towards sustainable positive OHS result in petrochemical construction projects. Management commitment plays a major part to maintain a sustained hazard free environment in building construction projects. The study also shows that the Occupational Health and Safety (OHS) factors –OHS policies, health care, communication, management commitment, education and training and workers’ behavior, have a direct impact on health and safety results towards social entrepreneurship of creating awareness in the construction sectors of Oman.
 RESEARCH LIMITATIONS/ IMPLICATIONS
 A model named Construction Industries Influencing Factors Framework (CIIFF) Model, has been developed with the orientation of workers’ behavior which can be developed further making improvements in the existing mechanism and the factors influencing can be dealt with wider procedures to ensure improvements.
 SOCIAL IMPLICATIONS
 The model may help in creating tools that are more effective to reduce Occupational Health and Safety related accidents and property damages in a construction project.

A study on the performance assessment of anti-terrorism physical protection systems in chemical plants

The threat originating from deliberate attacks against process and chemical sites where relevant quantities of hazardous substances are stored or processed is a credible one, as confirmed by the attacks carried out in France in the summer of 2015. Although such chemical sites implement multiple layers of protection to address safety-related accidents, they often get behind with providing adequate attention and resources to the protection of assets against external adversaries or, in other words, terrorist threats. The lack of a consolidated practice in the risk-informed implementation of security countermeasures goes hand in hand with the existence of very few rigorous approaches to the effectiveness assessment of security systems, and in particular of physical protection systems (PPSs). The present study addresses the issue of quantitatively assessing the effectiveness of physical security systems adopted to protect process and storage facilities, recognized as high-consequence loss physical assets. To this purpose, the security functions of PPSs were analyzed to guide the selection of performance parameters. Experts from the industry were involved to identify variables and influencing factors relevant to the successful accomplishment of security functions. Experience-based judgments on performance, to be expressed in terms of probabilistic estimates, were also obtained. An insight into the belief that experts hold on the probability of PPSs effectively preventing the success of an external attack and in the identification of critical elements was obtained. The application of the results to the quantitative assessment of the contribution of security controls in reducing vulnerability was also addressed.

AF궤도회로의 전기적 구분 장치 설치이전에 따른 커패시터 보상으로 LC공진 주파수 대역의 전압특성 분석

This paper analyzes the electrical characteristic such as the impedance(Z), inductance(L), and cable resistance(RSUBp/SUB) according to the change of cable length in order to move the electrical sorting device for distinguishing between AF non-insulated track circuits from the center of railway to outside railway. The simulation is performed to check the voltage difference between the voltage of sender and the voltage of receiver and determine the possibility of the voltage restoration availability in the frequency filter band through the capacitor compensation. It was applied to the results of the simulation to the sorting devices installed in the actual field. It is proved the availability by checking the measured voltage characteristic according to the capacitor compensating change of 10 ㎌ and 16 ㎌ before, and after the length of cable is increased with 6 meters. Through this, the prevention of breakdown and damage to facilities and the prevention the safety-related accidents of line workers from the train are expected according to moving the sorting devices of AR non-insulated track circuits to outside railway.

A Game-Theoretical Model to Improve Process Plant Protection from Terrorist Attacks.

The New York City 9/11 terrorist attacks urged people from academia as well as from industry to pay more attention to operational security research. The required focus in this type of research is human intention. Unlike safety-related accidents, security-related accidents have a deliberate nature, and one has to face intelligent adversaries with characteristics that traditional probabilistic risk assessment techniques are not capable of dealing with. In recent years, the mathematical tool of game theory, being capable to handle intelligent players, has been used in a variety of ways in terrorism risk assessment. In this article, we analyze the general intrusion detection system in process plants, and propose a game-theoretical model for security management in such plants. Players in our model are assumed to be rational and they play the game with complete information. Both the pure strategy and the mixed strategy solutions are explored and explained. We illustrate our model by an illustrative case, and find that in our case, no pure strategy but, instead, a mixed strategy Nash equilibrium exists.

Verification of Damage Detection Algorithm by Prototype Building Structure Test

Safety related accidents of buildings and civil engineering structures have been reported all over the world. With the increasing importance of securing the safety of social infrastructure and optimum performance levels to prevent these accidents, a lot of attention has been concentrated on monitoring performance degradation due to structural defects and deterioration. In this study, the algorithm was developed to evaluate the safety of structures by analyzing signals of time domain and frequency domain, and the developed algorithm was verified through a forced vibration test. From the results of time-domain and frequency-domain data analysis, the damage detection results by each sensor location with a high degree of accuracy were derived in both methods.

Implementation Mechanism of the Four-Group Shift System at Yuhan-Kimberly

Research has long reported the difficulty of adopting a new system into an organization. Therefore, we have examined the introduction process of a new system through Yuhan-Kimberly’s case for finding the solution. The new system such as the four-group shift of Yuhan-Kimberly is an effective combination of technological skills and HR management skills respecting human beings. It also generates competitive advantages contributing to the formation of lifelong education, decreased safety-related accidents, and in

Legal Principles of Liability for Safety-Related Accidents in School

Legal Principles of Liability for Safety-Related Accidents in School