Accident analysis of mining industry in the United States - a retrospective study for 36 years

• Autorzy: Rahimi Elham , Shekarian Younes , Shekarian Naser , Roghanchi Pedram

Identyfikatory

DOI

10.46873/2300-3960.1345

• Języki publikacji: EN

Abstrakty

EN

A retrospective study on accident analysis of the United States mines for 36 years was achieved using statistical analysis on the MSHA's accident databases between 1983 and 2018. A regression model of generalized estimation equation (GEE) was used for unbalanced panel data that provided 95,812 observations for 19,924 mine-ID-year in aggregate, coal, metal, and non-metal mines. The contributions of various parameters, including mine type, injured body part, days lost, age, and experience on the rate of accidents and injuries were investigated across the commodity types. The results showed coal miners in the East region are at a higher risk of accident. The results of regression analysis show that mine-tenured workers have a vital role in accident frequencies. Analysis of the injured body part on the injury rate indicates that the upper body injuries are the most significant among all mine types. Also, the fatality rate is significant in aggregate, and coal mines in comparison with metal and non-metal mines.

Słowa kluczowe

EN

mines; accident; statistical analysis; generalized estimation equation; GEE

PL

kopalnie; wypadek; analiza statystyczna; uogólnione równanie estymacji; GEE

• Wydawca: Elsevier ; Główny Instytut Górnictwa
• Czasopismo: Journal of Sustainable Mining
• Rocznik: 2022
• Tom: Vol. 21, iss. 1
• Strony: 27--44
• Opis fizyczny: Bibliogr. 27 poz.

Twórcy

autor

Rahimi Elham

• Department of Mineral Engineering, New Mexico Institute of Mining and Technology, Socorro, NM, USA and John and Willie Leone Family Department of Energy and Mineral Engineering, University Park, The Pennsylvania State University, State College, PA, USA

• https://orcid.org/0000-0002-2898-0616

autor

Shekarian Younes

• Department of Mineral Engineering, New Mexico Institute of Mining and Technology, Socorro, NM, USA and John and Willie Leone Family Department of Energy and Mineral Engineering, University Park, The Pennsylvania State University, State College, PA, USA

• https://orcid.org/0000-0001-8240-2895

autor

Shekarian Naser

• Department of Information Systems, Business School, University of Colorado Denver, Denver, CO, USA

• https://orcid.org/0000-0001-8225-3631

autor

Roghanchi Pedram

• Department of Mineral Engineering, New Mexico Institute of Mining and Technology, Socorro, NM, USA

• https://orcid.org/0000-0003-4696-8845

Bibliografia

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Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).