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A risk-based decision support framework for selection of appropriate safety measure system for underground coal mines

机译:基于风险的决策支持框架,用于选择地下煤矿的适当安全措施系统

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摘要

In the context of underground coal mining industry, the increased economic issues regarding implementation of additional safety measure systems, along with growing public awareness to ensure high level of workers safety, have put great pressure on the managers towards finding the best solution to ensure safe as well as economically viable alternative selection. Risk-based decision support system plays an important role in finding such solutions amongst candidate alternatives with respect to multiple decision criteria. Therefore, in this paper, a unified risk-based decision-making methodology has been proposed for selecting an appropriate safety measure system in relation to an underground coal mining industry with respect to multiple risk criteria such as financial risk, operating risk, and maintenance risk. The proposed methodology uses interval-valued fuzzy set theory for modelling vagueness and subjectivity in the estimates of fuzzy risk ratings for making appropriate decision. The methodology is based on the aggregative fuzzy risk analysis and multi-criteria decision making. The selection decisions are made within the context of understanding the total integrated risk that is likely to incur while adapting the particular safety system alternative. Effectiveness of the proposed methodology has been validated through a real-time case study. The result in the context of final priority ranking is seemed fairly consistent.
机译:在地下采煤业的背景下,与实施附加安全措施系统有关的日益增加的经济问题,以及日益提高的公众意识以确保工人的高水平安全,给管理人员施加了巨大压力,他们要求他们寻求最佳解决方案以确保安全。以及经济可行的替代选择。基于风险的决策支持系统在针对多个决策标准的候选备选方案中寻找此类解决方案方面发挥着重要作用。因此,在本文中,提出了一种基于风险的统一决策方法,以针对诸如财务风险,运营风险和维护风险等多种风险标准,针对地下煤矿行业选择合适的安全措施系统。所提出的方法使用区间值模糊集理论对模糊风险等级的估计中的模糊性和主观性进行建模,以做出适当的决策。该方法基于总体模糊风险分析和多准则决策。选择决策是在了解特定安全系统替代方案可能产生的总综合风险的前提下做出的。通过实时案例研究验证了所提出方法的有效性。在最终优先级排名的上下文中,结果似乎相当一致。

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