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A hybrid decision-making approach based on FCM and MOORA for occupational health and safety risk analysis

机译:基于FCM和MOORA的混合决策方法,用于职业健康和安全风险分析

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Introduction: With the development of industries and increased diversity of their associated hazards, the importance of identifying these hazards and controlling the Occupational Health and Safety (OHS) risks has also dramatically augmented. Currently, there is a serious need for a risk management system to identify and prioritize risks with the aim of providing corrective preventive measures to minimize the negative consequences of OHS risks. In fact, this system can help the protection of employees' health and reduction of organizational costs. Method: The present study proposes a hybrid decision-making approach based on the Failure Mode and Effect Analysis (FMEA), Fuzzy Cognitive Map (FCM), and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) for assessing and prioritizing OHS risks. After identifying the risks and determining the values of the risk assessment criteria via the FMEA technique, the attempt is made to determine the weights of criteria based on their causal relationships through FCM and the hybrid learning algorithm. Then, the risk prioritization is carried out using the MOORA method based on the decision matrix (the output of the FMEA) and the weights of the criteria (the output of the FCM). Results: The results from the implementation of the proposed approach in a manufacturing company reveal that the score at issue can overcome some of the drawbacks of the traditional Risk Priority Number (RPN) in the conventional FMEA, including lack of assignment the different relative importance to the assessment criteria, inability to take into account other important management criteria, lack of consideration of causal relationships among criteria, and high dependence of the prioritization on the experts' opinions, which finally provides a full and distinct risk prioritization. (C) 2019 National Safety Council and Elsevier Ltd. All rights reserved.
机译:简介:随着行业的发展以及相关危害的多样性增加,识别这些危害和控制职业健康与安全(OHS)风险的重要性也大大提高了。当前,迫切需要一种风险管理系统来识别风险并确定其优先级,以提供纠正性的预防措施,以最大程度地减少OHS风险的负面影响。实际上,该系统可以帮助保护员工的健康并降低组织成本。方法:本研究提出了一种基于故障模式和影响分析(FMEA),模糊认知图(FCM)和基于比率分析(MOORA)的多目标优化的混合决策方法,用于评估和优先考虑OHS风险。在通过FMEA技术识别风险并确定风险评估标准的值之后,尝试通过FCM和混合学习算法基于因果关系确定标准的权重。然后,使用MOORA方法基于决策矩阵(FMEA的输出)和标准权重(FCM的输出)对风险进行优先级排序。结果:在一家制造公司中实施该拟议方法的结果表明,有争议的分数可以克服传统FMEA中传统风险优先级数字(RPN)的一些弊端,包括缺乏对不同优先级的相对重要性评估标准,无法考虑其他重要管理标准,缺乏对标准之间因果关系的考虑以及优先级对专家意见的高度依赖,最终提供了完整而独特的风险优先级。 (C)2019国家安全委员会和Elsevier Ltd.保留所有权利。

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