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Statistical Analysis and Prediction of Fatal Accidents in the Metallurgical Industry in China

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  • Qingwei Xu

    (College of Information and Management Science, Henan Agricultural University, Zhengzhou 450046, China)

  • Kaili Xu

    (Key Laboratory of Ministry of Education on Safe Mining of Deep Metal Mines, School of Resources and Civil Engineering, Northeastern University, Shenyang 110819, China)

Abstract

The metallurgical industry is a significant component of the national economy. The main purpose of this study was to establish a composite risk analysis method for fatal accidents in the metallurgical industry. We collected 152 fatal accidents in the Chinese metallurgical industry from 2001 to 2018, including 141 major accidents, 10 severe accidents, and 1 extraordinarily severe accident, together resulting in 731 deaths. Different from traffic or chemical industry accidents, most of the accidents in the metallurgical industry are poisoning and asphyxiation accidents, which account for 40% of the total number of fatal accidents. As the original statistical data of fatal accidents in the metallurgical industry have irregular fluctuations, the traditional prediction methods, such as linear or quadratic regression models, cannot be used to predict their future characteristics. To overcome this issue, the grey interval predicting method and the GM(1,1) model of grey system theory are introduced to predict the future characteristics of fatal accidents in the metallurgical industry. Different from a fault tree analysis or event tree analysis, the bow tie model integrates the basic causes, possible consequences, and corresponding safety measures of an accident in a transparent diagram. In this study, the bow tie model was used to identify the causes and consequences of fatal accidents in the metallurgical industry; then, corresponding safety measures were adopted to reduce the risk.

Suggested Citation

  • Qingwei Xu & Kaili Xu, 2020. "Statistical Analysis and Prediction of Fatal Accidents in the Metallurgical Industry in China," IJERPH, MDPI, vol. 17(11), pages 1-20, May.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:11:p:3790-:d:363446
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    Cited by:

    1. Qingwei Xu & Kaili Xu, 2021. "Analysis of the Characteristics of Fatal Accidents in the Construction Industry in China Based on Statistical Data," IJERPH, MDPI, vol. 18(4), pages 1-21, February.
    2. Jeong-Hun Won & Hyeon-Ji Jeong & WonSeok Kim & Seungjun Kim & Sung-Yong Kang & Jong Moon Hwang, 2022. "Mechanisms Analysis for Fatal Accident Types Caused by Multiple Processes in the Workplace: Based on Accident Case in South Korea," IJERPH, MDPI, vol. 19(18), pages 1-23, September.
    3. Jing Guo & Zhen Wei & Jun Ren & Zenghai Luo & Huakun Zhou, 2020. "Early-Warning Measures for Ecological Security in the Qinghai Alpine Agricultural Area," IJERPH, MDPI, vol. 17(24), pages 1-29, December.
    4. Zifeng Liang, 2021. "Assessment of the Construction of a Climate Resilient City: An Empirical Study Based on the Difference in Differences Model," IJERPH, MDPI, vol. 18(4), pages 1-20, February.

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