DocumentCode :
2550181
Title :
Prediction analysis of human error probability for mine hoisting systems
Author :
Liu, Zhaoxia ; Chen, Lianjun ; Ren, Dawei
Author_Institution :
Coll. of Natural Resources & Environ. Eng., Shandong Univ. of Sci. & Technol., Qingdao, China
fYear :
2009
fDate :
21-23 Oct. 2009
Firstpage :
1184
Lastpage :
1188
Abstract :
Mine hoisting accidents, as common and frequent disasters, the statistics shows 90% of them are caused by human errors. Therefore, studying human reliability of the systems can effectively reduce systems failure due to human errors. Although the significance of human reliability has been widely acknowledged, this technology, currently restricted to aerospace, aviation, nuclear industry, is not prevalent in industrial and mining enterprises. So cognitive reliability and error analysis method which is the typical second generation of human reliability analysis method is utilized to analyze the failure model during mine hoisting operation. It divides the whole process into the basic events which are further divided into basic operation sequences, and analyzes possible failure mode and failure probability of each cognitive activity of operators, and quantitatively calculates the possible failure probability of each basic event. Eventually, according to contribution of each cognitive failure prevention and control measures are put forward from the aspects of management and technology to ensure the reliability of the system by reducing the probability of human error to the minimum acceptable degree.
Keywords :
accident prevention; human factors; mining; occupational safety; probability; reliability; cognitive reliability; error analysis method; human error probability; human reliability analysis; mine hoisting system; prediction analysis; Aerospace accidents; Aerospace industry; Control systems; Error analysis; Error probability; Failure analysis; Humans; Mining industry; Nuclear power generation; Technology management; Cognitive reliability and error analysis method; Hoisting systems; Human error; Quantitative predication;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Engineering and Engineering Management, 2009. IE&EM '09. 16th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-3671-2
Electronic_ISBN :
978-1-4244-3672-9
Type :
conf
DOI :
10.1109/ICIEEM.2009.5344464
Filename :
5344464
Link To Document :
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