Change mode and effects analysis by enhanced grey relational analysis under subjective environments
Change mode and effects analysis by enhanced grey relational analysis under subjective environments
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主观环境下增强灰色关联分析的变化模式及影响分析
DOI：
10.1017/s0890060417000099
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发表时间：
2017-05-01
影响因子：
2.1
通讯作者：
Peng，Ying-Hong
中科院分区：
文献类型：
--
作者：
Zhu，Guo-Niu;Hu，Jie;Peng，Ying-Hong
摘要变更模式与影响分析（CMEA）是衡量产品对未来变更的灵活性、降低重新设计成本和缩短产品上市时间的一种有力技术。作为一种系统的方法，它为设计、产品和过程中潜在的变化、原因和影响的调查提供了深入的视角。传统的CMEA通过使用变更潜在数来确定变更模式的风险优先级，这需要精确评估设计灵活性、发生率和准备度等风险因素。然而，由于早期设计阶段的不确定性和主观性，这在真实的应用中并不总是可能的。由于其在风险因素的标准权重、变革潜在数量的计算以及变革模式的风险优先级确定方面存在缺陷，因此受到了广泛的批评。本文提出了一种将熵权法、粗糙数法和灰色关联分析法相结合的系统评价方法，以确定一个较为合理的变化方式排序。采用熵权法计算风险因素的相对重要性。粗糙数被用来聚合个体的权重和偏好，并在评价过程中操纵的一致性。提出了一种粗糙数增强的灰色关联分析方法，对变更模式的风险进行评价排序。最后，通过一个实例验证了该方法的有效性.结果表明，该方法能有效克服传统CMEA方法的不足，增强产品柔性度量的客观性。
Abstract Change mode and effects analysis (CMEA) is a powerful technique for measuring product flexibility toward future changes and diminishing the cost of redesign as well as shortening time to market. As a systematic methodology, it provides an in-depth view for the investigation of potential changes, causes, and effects in designs, products, and processes. Traditional CMEA determines the risk priorities of change modes by using change potential number, which requires the risk factors of design flexibility, occurrence, and readiness to be precisely evaluated. However, this is not always possible in real applications due to the uncertainty and subjectivity involved in the early design stages. It has been criticized much for its deficiencies in criteria weighting of the risk factors, change potential number calculation, and risk priorities determination of the change modes. This paper presents a systematic evaluation approach for determining a more rational rank of change modes by combining with the entropy weight method, rough number, and grey relational analysis. In this study, the entropy weight method is adopted to calculate the relative importance of risk factors. Rough number is presented to aggregate individual weights and preferences, and to manipulate the vagueness in the evaluation process. Then a rough number enhanced grey relational analysis is proposed to evaluate the risk ranking of change modes. Finally, a practical example is put forward to validate the performance of the proposed method. The result shows that the proposed change mode evaluation method can effectively overcome the shortcomings of traditional CMEA and strengthen the objectivity of product flexibility measurement.