دانلود رایگان مقاله انگلیسی ایمنی کارگران در معادن هند: مطالعه، تجزیه و تحلیل و پیش بینی - نشریه الزویر

Abstract

Background: Mining industry is known worldwide for highly risky and hazardous working environment. Technological advancement in ore extraction techniques, for proliferation of production levels has further enhanced concern towards safety for this industry. Research so far in the area of safety has revealed that majority of incidence in hazardous industry takes place because of human error, which if can be controlled then safety levels in working sites can be enhanced to considerable extent. Method: Present work focuses upon analysis of human factors like unsafe acts, preconditions for unsafe acts, unsafe leadership, organizational influences, adopting modified Human Factor Analysis and Classification System (HFACS) and an accident predictive Fuzzy Reasoning Approach (FRA) based system is developed which can predict chances for occurrence of accidents with analysis of factors like age, experience of worker, shift of work etc., for manganese mines in India. Results: The outcome of analysis indicated that skill based errors are most critical and requires immediate attention for mitigation. FRA based accident prediction system developed gives outcome as indicative risk score associated with identified accident prone situation, based upon which a suitable plan for mitigation can be developed. Conclusion: Unsafe acts of the worker are most critical human factor identified to be controlled on priority basis. Significant association of the factors namely age, experience of the worker and shift of work with unsafe acts performed by the operator is identified based upon which FRA based accident prediction model is proposed.

7. Conclusions

The work presents detailed analysis of mine accidents occurred in underground as well as opencast manganese mines in India. HFACS framework is adopted to perform the analysis and significant findings are obtained. Based upon the findings a FRA model is proposed to assess the risk level with a given situation and modify the same if found critical. The outcome of the research work is highlighted below:

1. Unsafe acts of worker found to be most critical factor in developing accidental scenarios in mining sites with a maximum contribution of skill based errors performed by the workers.

2. Underground mining approach, stopping area, I shift of work, worker within the age group of 33-47 years and with 6-10 years of working experience are most critical to be considered in developing intervention strategies.

3. Faulty behavioral traits, organizational lacunas indicated as outcome of HFACAS analysis can be considered further to develop mitigation plan and intervention strategies for the industry.

4. Age, Experience of the Worker and Shift of Work has a significant correlation with unsafe acts performed ultimately leading to accidents.

5. A Fuzzy Reasoning Approach based risk prediction model proposed can be adopted by the safety analyst to predict the risk associated with a given situation and perform task allocation accordingly to prevent hazardous outcome.

Present work demonstrates a noble approach to risk and safety assessment. So far significant research performed in the area of safety management found to be limited with respect to scope since pro data based, questionnaire and interview based analysis of the data is performed and outcome indicated merely the trend for accidents or reasons behind the mishap. But, the present work is a step further of conventional research performed in this area where the outcome of micro level accident analysis has been utilized to develop accident prediction model to interpret the risk levels associated with a given situation and alter them accordingly. In future, the work can further be extended for other minerals extracted for commercial purpose in India and safety levels in sites can be improved.