scholarly journals The application of simulation (virtual reality) for safety training in the context of mining industry

2017 ◽  
Keyword(s):  
Virtual Reality ◽  
Mining Industry ◽  
Safety Training

A Virtual Reality Safety Training System for Coal Mining Industry

2014 ◽  
Vol 687-691 ◽  
pp. 2371-2374 ◽  
Author(s):  
Hua Ming Li ◽  
Bao Sheng Kang
Keyword(s):  
Virtual Reality ◽  
Coal Mining ◽  
Mining Industry ◽  
Safety Training ◽  
Training System ◽  
Training Methods ◽  
Coal Mining Industry ◽  
Training Quality ◽  
Mining Safety ◽  
Safety Knowledge

The high incidence of accidents and fatalities in the coal mining industry is often attributed to ineffective training methods. To improve the training quality,virtual reality simulation has applied to improve the effectiveness of the training. This paper presents a VR-based system for coal mining safety training. System can provide the intuitive approach for studying of the safety knowledge, and provide the interactive exercises for learning self-rescue and escape in the disasters. An architecture is proposed for customize new training mission quickly. The requirements of functions in the system have been discussed. The implemented system has proved that virtual reality training has the potential to provide more meaningful and effective training to address the identified safety needs in coal mining industry.

Virtual reality safety training using deep EEG-net and physiology data

2021 ◽  
Author(s):  
Dongjin Huang ◽  
Xianglong Wang ◽  
Jinhua Liu ◽  
Jinyao Li ◽  
Wen Tang
Keyword(s):  
Virtual Reality ◽  
Safety Training

Assessment of virtual reality based safety training simulator for electric overhead crane operations

2021 ◽  
Vol 139 ◽  
pp. 105241
Author(s):  
Krantiraditya Dhalmahapatra ◽  
J. Maiti ◽  
O.B. Krishna
Keyword(s):  
Virtual Reality ◽  
Safety Training ◽  
Overhead Crane ◽  
Training Simulator

scholarly journals Analysis of the severity of occupational injuries in the mining industry using a Bayesian network

2019 ◽  
Vol 41 ◽  
pp. e2019017 ◽  
Author(s):  
Mostafa Mirzaei Aliabadi ◽  
Hamed Aghaei ◽  
Omid kalatpuor ◽  
Ali Reza Soltanian ◽  
Asghar Nikravesh
Keyword(s):  
Bayesian Network ◽  
Occupational Injuries ◽  
Control Strategies ◽  
Expectation Maximization Algorithm ◽  
Mining Industry ◽  
Safety Training ◽  
Sensitivity Analyses ◽  
Occupational Accidents ◽  
Activity Type ◽  
Training Courses

OBJECTIVES: Occupational injuries are known to be the main adverse outcome of occupational accidents. The purpose of the current study was to identify control strategies to reduce the severity of occupational injuries in the mining industry using Bayesian network (BN) analysis.METHODS: The BN structure was created using a focus group technique. Data on 425 mining accidents was collected, and the required information was extracted. The expectation-maximization algorithm was used to estimate the conditional probability tables. Belief updating was used to determine which factors had the greatest effect on severity of accidents.RESULTS: Based on sensitivity analyses of the BN, training, type of accident, and activity type of workers were the most important factors influencing the severity of accidents. Of individual factors, workers’ experience had the strongest influence on the severity of accidents.CONCLUSIONS: Among the examined factors, safety training was the most important factor influencing the severity of accidents. Organizations may be able to reduce the severity of occupational injuries by holding safety training courses prepared based on the activity type of workers.

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