RISK REGRESSION ANALYSIS FOR OPENCAST MINE DUMPER OPERATORS

M. K. Singh, U. K. Dey

Abstract: This regression analysis studies of dumper drivers were conducted for an opencast mine located in one of mine of Jharia Coal field, Jharkhand, India. Statistical tools have been developed in the light of analylitical principles to see whether there is any role of some personal and impersonal factors in the occurrence of coal miners’ injuries. With the progress in exploitation of minerals, safety of persons employed became a matter of concern. Occupational injuries in mines are attributed to many factors. Raw data on personal and organizational factors based on the questionnaire (samples were collected from 113 dumper drivers) and other methods were collected from the mine and thereafter they were analyzed. A logistic regression model is used in this research work. With this model both the prediction of group membership and the analysis were done in the form of an odds ratio. On the basis of binary logistic regression for both injury vs no injury and reportable vs no injury cases, then on the basis of ordinal logistic regression results the factors which were found to be most important among the initial factors were selected. The variables those show distinct relationship and considered to be significant with the degree of injury are the personal factors, environmental condition, machinery condition, job satisfaction and risk taking behavior and their respective adjusted odds ratios were found 12.17, 5.26, 6.35, 5.04 and 9.85 for significant risk factors in relation to injury vs No injury case. Similarly, 9.54, 8.40, 4.86 and 9.28 respectively for reportable vs no injury cases. In other words the above mentioned high risky significant factors are 12.17, 5.26, 6.35, 5.04 and 9.85 times more susceptible to injury in comparison to reference category. Out of the above 5 factors most highly significant categories are personal factor and risk taking behavior.

Keywords: Risk analysis, Statistical tools, Coal, Occupational Injury, Variables, Personal factors, Impersonal factors, Environment, logistic regression

DOI: https://doi.org/10.15623/ijret.2015.0408044