ایمنی کارگران در معادن هند: مطالعه، تجزیه و تحلیل و پیش بینی Safety of Workers in Indian Mines: Study, Analysis, and Prediction

. Introduction Mining industry exists with well recognized fact of having most arduous working environment where safety and health of the worker engaged is always a prime concern. Mining safety has always drawn attention of researchers working in the field of health and safety. The metal and mining industry of India has recorded a strong expansion in the recent past with expectation of India to become the second-largest steel producer later 2015. Production volumes have also grown steadily over the years – during the period 2007-2015 [1-8]. Therefore manganese mining and sudden enhancement in its production levels have germinated increased concern with safety scenarios in mines. Nevertheless, adverse working conditions and technological advancements cannot solely be blamed for incidences taking place in the working sites. Patterson [9] conducted study in Queensland, considering accident data for quarry, open cut coal mines, underground coal mines, open cut metal mines and underground metal mines and revealed that irrespective of the mine type skill based errors performed by the operators is the major cause of incidences took place between 2004 to 2008, indicating the need for analyzing the mining accident with human factors perspective in Indian environment also. The accident analysis in the present work is done by the adoption of the modified HFACS framework. HFACS is an adaptation of reasons’ swiss cheese model of accident causation. The Human Factors Analysis and Classification System (HFACS) is a general human error framework originally developed and tested within the U.S. military as a tool for investigating and analyzing the human causes of aviation accidents [10]. One of the major lacuna in the model developed by Reason is less systematic categorization of the errors. HFACS addresses more systematic and detailed classification of human errors in four levels and many sub levels, as shown in figure 1 below. Original model developed by (Wiegmann and Shappell 2003) includes 19 causal categories of errors, but the framework modified by [9] for the Australian mining industry includes 21 causal categories, including outside factors triggering unsafe consequences. This framework is an investigation model which enables the identification of human factors involved in any occurring/recurring unfavorable incidence.