Quantification for the importance degree of engineering characteristics with a multi-level hierarchical structure in QFD
Quantification for the importance degree of engineering characteristics with a multi-level hierarchical structure in QFD
复制标题
QFD中多层次层次结构对工程特征重要程度的量化
DOI：
10.1080/00207543.2015.1041574
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发表时间：
2016-03
影响因子：
9.2
通讯作者：
Jianrong Tan
中科院分区：
文献类型：
--
作者：
Weiqiang Jia;Zhenyu Liu;Zhiyun Lin;Chan Qiu;Jianrong Tan
工程特性重要程度的量化是质量功能部署中的一个重要问题。在现实场景中，由于ec过于抽象，有时很难直接评估ec与客户需求之间的关联度。因此，必须将目标ec进一步分解为几个更详细的基本ec，并按多级层次结构组织。本文研究了目标生态系统重要程度的量化问题，并解决了两个关键问题。首先是如何处理评价过程中存在的不确定性，包括模糊性和不完全性。提出了一种基于模糊证据推理算法的方法来解决这一问题，并推导出每个基本ec与整个cr之间的关联度。第二个问题是在聚合过程中如何处理从同一目标EC分解的基本EC之间的相互作用。提出了一种基于λ-模糊测度和模糊离散Choquet积分的方法来解决这一问题，并对这些基本ec进行了聚合。然后可以得到目标ec的最终重要程度。最后，通过一个实例验证了所提方法的可行性和有效性。
Quantification for the importance degree of engineering characteristics (ECs) is an essential problem in quality function deployment. In real-world scenario, it is sometimes difficult to directly evaluate the correlation degree between ECs and customer requirements (CRs) as ECs are too abstract. Thus, the target ECs have to be further decomposed into several more detailed basic ECs and organised by a multi-level hierarchical structure. The paper investigates the quantification problem for the importance degree of such target ECs and tackles two critical issues. The first issue is how to deal with the uncertainties including fuzziness and incompleteness involved during the evaluation process. A fuzzy evidential reasoning algorithm-based approach is proposed to tackle this issue and derive the correlation degree between each of the basic ECs and the whole CRs. The second issue is how to deal with the interactions among the basic ECs decomposed from the same target EC during the aggregation process. A λ-fuzzy measure and fuzzy discrete Choquet integral-based approach is proposed to tackle this issue and aggregate these basic ECs. Final importance degree of the target ECs can then be obtained. At the end of this paper, a case study is presented to verify the feasibility and effectiveness of the method we propose.
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影响因子：
9.2
作者：
Juite Wang
通讯作者：
Juite Wang
DOI：
10.1016/j.eswa.2009.02.070
发表时间：
2009-10
期刊：
Expert Syst. Appl.
影响因子：
--
作者：
Hao-Tien Liu
通讯作者：
Hao-Tien Liu
DOI：
10.1016/j.cie.2011.02.004
发表时间：
2011-08
期刊：
Comput. Ind. Eng.
影响因子：
--
作者：
F. Zandi;M. Tavana
通讯作者：
F. Zandi;M. Tavana
DOI：
10.1002/0470011815.b2a4a002
发表时间：
2005-07
期刊：
--
影响因子：
--
作者：
T. Saaty
通讯作者：
T. Saaty
影响因子：
8.3
作者：
Kwong, CK;Bai, H
通讯作者：
Bai, H