Mine Safety, Productivity and Job Design

1984 ◽  
Vol 28 (5) ◽  
pp. 476-477
Author(s):  
Leslie A. Whitaker ◽  
Carol F. Shoptaugh
Keyword(s):  
Safety Information ◽  
Job Design ◽  
Mine Safety ◽  
Severe Accident ◽  
Random Errors ◽  
Contributing Factors ◽  
Safety Hazards ◽  
Productivity Data ◽  
Increase Productivity ◽  
Save Energy

Modern surface mine safety and productivity data were summarized as part of the Bureau of Mines Industrial Hazards/Human Factors program. Safety Information was obtained through mine site visits (observations and interviews), national actuarial statistics, tables, and MSHA accident reports. The examination of 148 accidents showed three specific contributing factors. First, mining is a rugged industry in which the environment is unstable and unpredictable. This unpredictability contributes to both accident incidence and severity. Second, large vehicles (120 ton haulpacks) move, fully loaded among small vehicles and people. This mismatch in size makes a collision a very severe accident. Finally, job design was found to be a contributing factor in accidents. Sixty-seven percent of the sampled accidents involved the misuse of a tool or procedure. These are not random errors, but reflect short cuts the workers take to save energy and increase productivity. It was proposed that correct job procedures would not be followed if the more efficient shortcuts were available. Consequently, the next step in this program is to develop modified job procedures for a few selected tasks. These procedures would be redesigned to improve efficiency and avoid the safety hazards found in the workers' make shift shortcuts. This approach changes the focus from emphasizing safety to emphasizing productivity through the design of safe and efficient job procedures.

Study of effective factors in the design of zero energy buildings in arid climate (case of Isfahan City)

2018 ◽  
Vol 8 (1) ◽  
pp. 211-221
Author(s):  
Negar Aminoroayaei ◽  
Bahram Shahedi
Keyword(s):  
Fossil Fuels ◽  
Arid Climate ◽  
Zero Energy ◽  
Factors Affecting ◽  
Zero Energy Building ◽  
Cost Of Energy ◽  
Current Century ◽  
Increase Productivity ◽  
Save Energy ◽  
Zero Energy Buildings

In the current century, a suitable strategy is concerned for optimal consumption of energy, due to limited natural resources and fossil fuels for moving towards sustainable development and environmental protection. Given the rising cost of energy, environmental pollution and the end of fossil fuels, zero-energy buildings became a popular option in today's world. The purpose of this study is to investigate the factors affecting the design of zero-energy buildings, in order to reduce energy consumption and increase productivity, including plan form, climatic characteristics, materials, coverage etc. The present study collects the features of zero-energy building in Isfahan, which is based on the Emberger Climate View in the arid climate, by examining the books and related writings, field observations and using a descriptive method, in the form of qualitative studies. The results of the research showed that some actions are needed to save energy and, in general, less consumption of renewable energy by considering the climate and the use of natural conditions.

Enrichment and Separation of Coal Mine Ventilation Methane and Engineering Education

2014 ◽  
Vol 1073-1076 ◽  
pp. 2078-2081
Author(s):  
Tao Zhu ◽  
Shuang Jie Du ◽  
Xian Xian He
Keyword(s):  
Coal Mine ◽  
Engineering Students ◽  
Mine Ventilation ◽  
Mine Safety ◽  
Research Progress ◽  
Auxiliary Equipment ◽  
Safety Hazards ◽  
Environmental Technology ◽  
Potential Safety ◽  
High Efficient

Due to the large flow, low concentration, low enrichment efficiency, potential safety hazards and the difficulty of comprehensive utilization, it is a big challenge for the development and application of enrichment and separation technology for coal mine ventilation methane (CMVM) at home and abroad. And many countries paid more and more attentions to resolve this problem. In this paper, we comprehensively introduce the research progress in the field of gas enrichment and separation of CMVM, and analyze the related research and application situation. Then, we put forward the enrichment and separation of CMVM in the future development will focus on high efficient adsorbent and adsorption & separation & enrichment technology and equipment, etc. in order to effectively form the system technology of separation & enrichment of CMVM. So we can provide technical support and auxiliary equipment for the domestic related enterprises, and ensure the mine safety and CMVM utilization. The application of CMVM in the laboratory can make mining engineering students learn how to use environmental technology to realize energy saving and emission reduction in coal mine.

Low Power Wi-Fi(IEEE 802.11) for Mobile Sensing of the Internet of Things of Mine

2012 ◽  
Vol 424-425 ◽  
pp. 1053-1056
Author(s):  
Li Guo Qu ◽  
You Rui Huang ◽  
Chao Li Tang ◽  
Liu Yi Ling
Keyword(s):  
Internet Of Things ◽  
Low Power ◽  
Ieee 802.11 ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Safety Information ◽  
Mobile Sensing ◽  
Mine Safety ◽  
Mobile Ad Hoc ◽  
The Internet Of Things

Sensing Mine is the specific application of internet of things in mine. Through a variety of techniques of sensing, information transmission and processing, Sensing Mine realizes digital, visualization, and intelligent of true mine. Because mine is in the dynamic mining process, only WSN (wireless sensor network) with the characteristics of distributed, mobile, ad hoc network can be employed to realize mine information sensing. In this paper, low power Wi-Fi(IEEE 802.11)is adopted to constitute WSN, and the node of WSN is mainly consist of GS1010 which is WSN solutions of GainSpan company and other external sensor for mobile sensing of the mine information. Experiment results show that WSN based on Wi-Fi enhances the sensing ability of mine safety information, and provides real-time, reliable data for the mine disasters prediction

Mine safety information technology in the framework of Digital Mine

2012 ◽  
Vol 50 (4) ◽  
pp. 846-850 ◽  
Author(s):  
Chunmin Li ◽  
Xin Zhang ◽  
Xin Liu
Keyword(s):  
Information Technology ◽  
Safety Information ◽  
Mine Safety ◽  
Digital Mine

Three Jiaohe Coal Mine Safety Information Management System Design Scheme

2013 ◽  
Vol 734-737 ◽  
pp. 3030-3033 ◽  
Author(s):  
Shu Zhen Li ◽  
Hui Huang
Keyword(s):  
System Design ◽  
Information Management ◽  
Coal Mine ◽  
Management System ◽  
Safety Management ◽  
Safety Information ◽  
Information Management System ◽  
Mine Safety ◽  
Coal Mine Safety ◽  
Safety Production

In order to solve the three JiaoHe coal mine safety production the problems existing in the management and detailed analysis of the safety of this ore information management status, determine the safety information management system design goal, make the system design of the guiding ideology, the advanced nature, adaptability, according to the developmental and reliability of principles in the design, the management system has strong data processing ability can provide the scientific decision of leaders at all levels of the data support, advanced and reliable information means can help enterprise further improve safety management work process optimization and realize the goal of prevention, so as to reduce the number of accidents, ensure the safety of the QuanKuang production.

scholarly journals Justification of the basic algorithms of the mine safety information system

2019 ◽  
Vol 109 ◽  
pp. 00086 ◽  
Author(s):  
Volodymyr Shevchenko ◽  
Anton Slashchov
Keyword(s):  
Information System ◽  
Process Development ◽  
Underground Mining ◽  
Safety Information ◽  
Control Object ◽  
Mine Safety ◽  
Technical Documentation ◽  
Current State ◽  
Information Safety ◽  
Job Safety

This article is devoted to substantiation of basic algorithms for the information system which could provide prompt making of decisions on ensuring safety of underground mining jobs, which are of great importance for the job safety at the mining enterprises. The information safety system architecture and some basic algorithms was developed. The system differs by its methods for prompt predicting and assessing of different scenarios of geomechanical process development, and which includes the following subsystems: a basic client-server subsystem with functions of interaction between the personnel and management of the enterprise; a reference and information subsystem, which supports a decision making process, accumulates data and analyzes technical documentation; a subsystem for analyzing the job safety by geomechanical factors and for assessing of the “support-rocks” system state basing on the risk criteria and mathematical fuzzy logics. Two integral indicators of safety are formed. The first indicator is used to control entering of the control object to the emergency mode and to determine a factor, which requires urgent interruption, and the second indicator is used for the total assessment of the object current state.

scholarly journals Determinants and Prediction of Injury Severities in Multi-Vehicle-Involved Crashes

2021 ◽  
Vol 18 (10) ◽  
pp. 5271
Author(s):  
Xiuguang Song ◽  
Rendong Pi ◽  
Yu Zhang ◽  
Jianqing Wu ◽  
Yuhuan Dong ◽  
...  
Keyword(s):  
Machine Learning ◽  
Traffic Safety ◽  
Statistical Models ◽  
Injury Severity ◽  
Safety Information ◽  
Temporal Stability ◽  
Prediction Performance ◽  
Transportation Safety ◽  
Contributing Factors ◽  
Injury Severities

Multi-vehicle (MV) crashes, which can lead to great damages to society, have always been a serious issue for traffic safety. A further understanding of crash severity can help transportation engineers identify the critical reasons and find effective countermeasures to improve transportation safety. However, studies involving methods of machine learning to predict the possibility of injury-severity of MV crashes are rarely seen. Besides that, previous studies have rarely taken temporal stability into consideration in MV crashes. To bridge these knowledge gaps, two kinds of models: random parameters logit model (RPL), with heterogeneities in the means and variances, and Random Forest (RF) were employed in this research to identify the critical contributing factors and to predict the possibility of MV injury-severity. Three-year (2016–2018) MV data from Washington, United States, extracted from the Highway Safety Information System (HSIS), were applied for crash injury-severity analysis. In addition, a series of likelihood ratio tests were conducted for temporal stability between different years. Four indicators were employed to measure the prediction performance of the selected models, and four categories of crash-related characteristics were specifically investigated based on the RPL model. The results showed that the machine learning-based models performed better than the statistical models did when taking the overall accuracy as an evaluation indicator. However, the statistical models had a better prediction performance than the machine learning models had considering crash costs. Temporal instabilities were present between 2016 and 2017 MV data. The effect of significant factors was elaborated based on the RPL model with heterogeneities in the means and variances.

scholarly journals Relation extraction for coal mine safety information using recurrent neural networks with bidirectional minimal gated unit

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Xiulei Liu ◽  
Shoulu Hou ◽  
Zhihui Qin ◽  
Sihan Liu ◽  
Jian Zhang
Keyword(s):  
Neural Networks ◽  
Coal Mine ◽  
Recurrent Neural Networks ◽  
Practical Importance ◽  
Safety Information ◽  
Relation Extraction ◽  
Mine Safety ◽  
Linguistic Knowledge ◽  
Coal Mine Safety ◽  
Time Accuracy

AbstractThe data of coal mine safety field are massive, multi-source and heterogeneous. It is of practical importance to extract information from big data to achieve disaster precaution and emergency response. Existing approaches need to build more features and rely heavily on the linguistic knowledge of researchers, leading to inefficiency, poor portability, and slow update speed. This paper proposes a new relation extraction approach using recurrent neural networks with bidirectional minimal gated unit (MGU) model. This is achieved by adding a back-to-front MGU layer based on original MGU model. It does not require to construct complex text features and can capture the global context information by combining the forward and backward features. Evident from extensive experiments, the proposed approach outperforms the existing initiatives in terms of training time, accuracy, recall and F value.

Use of Accident Information in The Development of Mining Industry Training Programs

1981 ◽  
Vol 25 (1) ◽  
pp. 553-553
Author(s):  
J. L. Woodward ◽  
G. E. Adkins
Keyword(s):  
Training Programs ◽  
Mining Industry ◽  
Mine Safety ◽  
Mining Equipment ◽  
Contributing Factors ◽  
Fatal Accidents ◽  
Safety And Health ◽  
Serious Injury ◽  
Industry Training

The investigation of serious injury and fatal accidents in the mining industry is mandated by 30 CFR 50 under the Federal Mine Safety and Health Act of 1977. The information derived from investigations can be put to important use in formulating training programs. Analysis of accident reports can result in information that points out contributing factors to accidents which not only can be modified or eliminated via administrative and/or design controls, but which can be addressed through training. This paper describes the use of accident reports to determine the relative necessity for development of training programs for mobile mining equipment operators.

Sign in / Sign up

Export Citation Format

Share Document