Other language title :
بررسي و پيش بيني حوادث معدن در پاكستان
Title of article :
Analysis and Forecast of Mining Accidents in Pakistan
Author/Authors :
Hussain, Sajjad Department of Mining Engineering - University of Engineering and Technology Peshawar - Peshawar, Pakistan , Shah, Kausar Sultan Department of Mining Engineering - University of Engineering and Technology Peshawar - Peshawar, Pakistan , Jiskani, Izhar Mithal School of Mines - China University of Mining and Technology - Xuzhou, China , Shahani, Niaz Muhammad School of Mines - China University of Mining and Technology - Xuzhou, China , Rehman, Hafeezur Department of Mining Engineering - Balochistan University of Information Technology - Engineering and Management Sciences - Quetta, Pakistan , Khan, Naseer Muhammad Department of Mining Engineering - Balochistan University of Information Technology - Engineering and Management Sciences - Quetta, Pakistan
Pages :
10
From page :
967
To page :
976
Abstract :
In the mining sector, the barrier to obtain an efficient safety management system is the unavailability of future information regarding the accidents. This paper aims to use the auto-regressive integrated moving average (ARIMA) model, for the first time, to evaluate the underlying causes that affect the safety management system corresponding to the number of accidents and fatalities in the surface and underground mining in Pakistan. The original application of the ARIMA model provides that how the number of accidents and fatalities is influenced by the implementation of various approaches to promote an effective safety management system. The ARIMA model requires the data series of the predicted elements with a random pattern over time and produce an equation. After the model identification, it may forecast the future pattern of the events based on its existing and future values. In this research work, the accident data for the period of 2006-2019-is collected from Inspectorate of Mines and Minerals (Pakistan), Mine Workers Federation, and newspapers in order to evaluate the longterm forecast. The results obtained reveal that ARIMA (2, 1, 0) is a suitable model for both the mining accidents and the workers’ fatalities. The number of accidents and fatalities are forecasted from 2020 to 2025. The results obtained suggest that the policy-makers should take a systematic consideration by evaluating the possible risks associated with an increased number of accidents and fatalities, and develop a safe and effective working platform.
Farsi abstract :
در ﺑﺨﺶ ﻣﻌﺪن در دﺳــﺘﺮس ﻧﺒﻮدن اﻃﻼﻋﺎت آﺗﯽ در ﻣﻮرد ﺣﻮادث، ﻣﺎﻧﻊ دﺳــﺘﯿﺎﺑﯽ ﺑﻪ ﯾﮏ ﺳــﯿﺴــﺘﻢ ﻣﺪﯾﺮﯾﺖ اﯾﻤﻨﯽ ﮐﺎرآﻣﺪ اﺳــﺖ. ﻫﺪف اﯾﻦ ﻣﻘﺎﻟﻪ اﺳــﺘﻔﺎده از ﻣﺪل )ARIMA( ﺑﺮاي اوﻟﯿﻦ ﺑﺎر ﺑﺮاي ارزﯾﺎﺑﯽ ﻋﻠﻞ ا ﺳﺎ ﺳﯽ و ﺗﺎﺛﺮ ﮔﺬار ﺑﺮ ﺳﯿ ﺴﺘﻢ ﻣﺪﯾﺮﯾﺖ اﯾﻤﻨﯽ ﻣﺘﻨﺎﻇﺮ ﺑﺎ ﺗﻌﺪاد ﺗ ﺼﺎدﻓﺎت و ﺗﻠﻔﺎت در ﻣﻌﺪنﻫﺎي ﺳﻄﺤﯽ و زﯾﺮزﻣﯿﻨﯽ در ﭘﺎﮐ ﺴﺘﺎن ا ﺳﺖ. ﮐﺎرﺑﺮد ا ﺻﻠﯽ ﻣﺪل ARIMA ﭼﮕﻮﻧﮕﯽ ﺗﺎﺛﺮ ﺗﻌﺪاد ﺗ ﺼﺎدﻓﺎت و ﻓﻮﺗﯽﻫﺎ را ﺗﺤﺖ ﺗﺄﺛﯿﺮ اﺟﺮاي روﯾﮑﺮدﻫﺎي ﻣﺨﺘﻠﻒ ﺑﺮاي ارﺗﻘﺎ ﯾﮏ ﺳﯿ ﺴﺘﻢ ﻣﺪﯾﺮﯾﺖ اﯾﻤﻨﯽ ﻣﻮﺛﺮ ﻧ ﺸﺎن ﻣﯽدﻫﺪ. ﻣﺪل ARIMA ﺑﻪ ﻣﺠﻤﻮﻋﻪ دادهﻫﺎي ﻋﻨﺎ ﺻﺮ ﭘﯿﺶﺑﯿﻨﯽ ﺷﺪه ﺑﺎ ﯾﮏ اﻟﮕﻮي ﺗ ﺼﺎدﻓﯽ در ﻃﻮل زﻣﺎن ﻧﯿﺎز دارد و ﯾﮏ ﻣﻌﺎدﻟﻪ ﺗﻮﻟﯿﺪ ﻣﯽﮐﻨﺪ. ﭘﺲ از ﺷــﻨﺎﺳــﺎﯾﯽ ﻣﺪل، ﻣﯽﺗﻮان اﻟﮕﻮي آﯾﻨﺪه روﯾﺪادﻫﺎ را ﺑﺮ اﺳــﺎس ﻣﻘﺎدﯾﺮ ﻣﻮﺟﻮد و آﯾﻨﺪه آن ﭘﯿﺶﺑﯿﻨﯽ ﮐﺮد. در اﯾﻦ ﮐﺎر ﺗﺤﻘﯿﻘﺎﺗﯽ، دادهﻫﺎي ﺗﺼــﺎدﻓﺎت ﻣﺮﺑﻮط ﺑﻪ ﺑﺎزهي 2019-2006 از ﺑﺎزرﺳــﯽ ﻣﻌﺎدن و ﻣﻮاد ﻣﻌﺪﻧﯽ )ﭘﺎﮐﺴــﺘﺎن(، ﻓﺪراﺳــﯿﻮن ﮐﺎرﮔﺮان ﻣﻌﺪن و روزﻧﺎﻣﻪﻫﺎ ﺑﻪ ﻣﻨﻈﻮر ارزﯾﺎﺑﯽ و ﭘﯿﺶﺑﯿﻨﯽ ﺑﻠﻨﺪ ﻣﺪت ﺣﻮادث و ﺗﻠﻔﺎت ﺟﻤﻊ آوري ﺷــﺪه اﺳــﺖ. ﻧﺘﺎﯾﺞ ﺑﻪ دﺳــﺖ آﻣﺪه ﻧﺸــﺎن ﻣﯽدﻫﺪ ﮐﻪ اﻟﮕﻮي )2 ، 1 ، 0( ARIMA اﻟﮕﻮي ﻣﻨﺎﺳــﺒﯽ ﺑﺮاي ﭘﯿﺶﺑﯿﻨﯽ ﺗﺼــﺎدﻓﺎت ﻣﻌﺪﻧﮑﺎري و ﻣﺮگ و ﻣﯿﺮ ﮐﺎرﮔﺮان اﺳﺖ. ﻫﻤﭽﻨﯿﻦ در اﯾﻦ ﻣﻘﺎﻟﻪ ﺗﻌﺪاد ﺗﺼﺎدﻓﺎت و ﻓﻮﺗﯽﻫﺎ از ﺳﺎل 2020 ﺗﺎ 2025 ﭘﯿﺶ ﺑﯿﻨﯽ ﺷﺪه اﺳﺖ. ﻧﺘﺎﯾﺞ ﺑﻪ دﺳﺖ آﻣﺪه ﺣﺎﮐﯽ از آن اﺳﺖ ﮐﻪ ﺳﯿﺎﺳﺖ ﮔﺬاران ﺑﺎﯾﺪ ﺑﺎ ارزﯾﺎﺑﯽ ﺧﻄﺮات اﺣﺘﻤﺎﻟﯽ ﻣﺮﺗﺒﻂ ﺑﺎ اﻓﺰاﯾﺶ ﺗﻌﺪاد ﺗ ﺼﺎدﻓﺎت و ﺗﻠﻔﺎت، ﯾﮏ ﺗ ﺼﻤﯿﻢﮔﯿﺮي ﺳﯿ ﺴﺘﻤﺎﺗﯿﮏ را اﺗﺨﺎذ ﮐﻨﻨﺪ و ﯾﮏ ﺑ ﺴﺘﺮ ﮐﺎري اﯾﻤﻦ و ﻣﻮﺛﺮ را اﯾﺠﺎد ﻧﻤﺎﯾﻨﺪ
Keywords :
Mine safety , Safety management system , Forecasting , Fatalities , moving average method , Auto-regressive integrating
Journal title :
Journal of Mining and Environment
Serial Year :
2020
Record number :
2527991
Link To Document :
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