An investigation on emergency response system during Anjan hill coal mine disaster using control task analysis – a cognitive approach
DOI:
https://doi.org/10.18311/jmmf/2021/29379Keywords:
ERS, CTA, mine disaster, CWA.Abstract
The accidents due to gas and coal dust explosion are one of the most common and serious accidents in underground coal mines. A lot of different scientific and physical indications and signs alarms before any accidents. Disasters management is both reactive and proactive. The proactive management deals with various steps taken to prevent and eliminate any disaster. Whereas, reactive management, on the other hand, deals with the actions taken to reduce the damage caused by a disaster, mitigate sufferings, take up recovery measures, organize rehabilitation, bring normalcy of different operations in the mine, disseminate prompt information to relatives of the victims, civil authorities, print and electronic media and people living nearby. Therefore, in any emergency situation the emergency response system (ERS) plays the most crucial part. An efficient ERS can potentially save an emergency situation to turn into a disaster or serious accident. In this paper, a case study conducting control task analysis (CTA) to investigate into the emergency response system during Anjan hill coal mine disaster is presented. Inquiry reports of Anjan hill coal mine disaster has been used to identify the problem and know the current state of the system. Results of CTA are used to identify constraints in the system. The analysis has brought out recommendations to improve EMS.Downloads
Metrics
Downloads
Published
How to Cite
Issue
Section
Accepted 2022-01-22
Published 2022-01-24
References
Cattaneo C, Manera M, Scarpa E (2011): Industrial coal demand in China: A provincial analysis. Resour Energy Econ 33:12–35
Dash AK, Bhattacharjee RM, Singh CS, et al (2017): A decision can be a disaster: A descriptive analysis of a case study. Int J Appl Environ Sci 12:1803–1820
Durga S, Swetha R (2015): Disaster Prevention and Control Management. Procedia Earth Planet Sci 11:516–523. https://doi.org/10.1016/j.proeps. 2015.06.052
He Z, Wu Q, Wen L, Fu G (2019): A process mining approach to improve emergency rescue processes of fatal gas explosion accidents in Chinese coal mines. Saf Sci. 111:154–166
Jenkins DP, Stanton NA, Salmon PM, et al (2008): Using cognitive work analysis to explore activity allocation within military domains. Ergonomics 51:798– 815
Kumar D (2010): Emerging tools and techniques for mine safety and disaster management. Nat Anthropog Disasters Vulnerability, Prep Mitig 332–365. https:// doi.org/10.1007/978-90-481-2498-5_15
LI X, HU J (2005): Investigation analysis and simulation verification technology for mine gas explosion accident. Coal Sci Technol 4:
McAteer JD, Beall K, Beck JA, et al (2011): Upper Big Branch, the April 5, 2010, explosion: a failure of basic coal mine safety practices. Rep to Governor, Governor’s Indep Investig Panel 126
Moura No.2 (2AD) Inquiry Task Group No. 4, 1994
Naikar N (2005): Theoretical concepts for work domain analysis, the first phase of cognitive work analysis. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting. SAGE Publications Sage CA: Los Angeles, CA, pp 249–253
Onifade M (2021): Towards an emergency preparedness for self-rescue from underground coal mines. Process Saf Environ Prot.
Rasmussen J, Pejtersen AM, Goodstein LP (1994): Cognitive systems engineering
Rasmussen J, Pejtersen AM, Schmidt K (1990): Taxonomy for cognitive work analysis. Citeseer
Si R, Li R, Huang Z (2012): Material evidence analysis upon accident investigation of gas and coal dust explosion. Procedia Eng 45:458–463
Vicente KJ (1999): Cognitive work analysis: Toward safe, productive, and healthy computer-based work. CRC press
Yuan L (2016): Control of coal and gas outbursts in Huainan mines in China: A review. J Rock Mech Geotech Eng 8:559–567
Zhang L, Chen G (2009): Review on accident investigation and analysis methods. China Saf Sci J 4:
Zhao W, Cheng Y, Pan Z, et al (2019): Gas diffusion in coal particles: A review of mathematical models and their applications. Fuel 252:77–100