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The quality function deployment method under uncertain environment using evidential reasoning: a case study of compressor manufacturing

机译:基于证据推理的不确定环境下质量函数展开方法:以压缩机制造为例

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摘要

In recent years, the issue of customer satisfaction achieving on the basis of improving service quality has been widely investigated. To achieve this goal, one of well-structured method is quality function deployment (QFD). QFD is an approach defining customer requirements (CRs) and translating them into relevant design requirements (DRs). The successful implementation of QFD requires a significant number of subjective evaluations of both customers and QFD team members. The QFD team members evaluate relationships between DRs and CRs and interrelationships between DRs. The customers evaluate relative importance of each CRs. In the basic QFD, crisp values are used for determining relationships between DRs and CRs, but the mentioned method are not suitable to address the subject of uncertainty, since in most cases QFD team express their opinions with uncertainty and therefore resulting in inappropriate implementation of QFD. This paper aims to apply a QFD method based on evidential reasoning approach to handle uncertain evaluation information provided by QFD team in compressor manufacturing. This method is able to consider uncertainties such as interval, imprecise and incomplete data in utilizing belief structure and then aggregating them to prioritize engineering DRs according to CRs.
机译:近年来,在改善服务质量的基础上实现客户满意度的问题已得到广泛研究。为了实现此目标,结构良好的方法之一是质量功能部署(QFD)。 QFD是一种定义客户需求(CR)并将其转换为相关设计需求(DR)的方法。 QFD的成功实施需要对客户和QFD团队成员进行大量的主观评估。 QFD团队成员评估DR和CR之间的关系以及DR之间的相互关系。客户评估每个CR的相对重要性。在基本QFD中,使用明晰的值来确定DR和CR之间的关系,但是上述方法不适用于解决不确定性问题,因为在大多数情况下,QFD团队会表达不确定性的意见,因此会导致QFD的实施不当。本文旨在应用基于证据推理方法的QFD方法来处理QFD团队在压缩机制造中提供的不确定评估信息。该方法能够在利用置信结构时考虑不确定性,例如区间,不精确和不完整的数据,然后将它们汇总以根据CR优先化工程DR。

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