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A group multi-granularity linguistic-based methodology for prioritizing engineering characteristics under uncertainties

机译：一种基于多粒度的基于语言的方法论，用于在不确定性下确定工程特征的优先级

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摘要

Quality Function Deployment (QFD) is a customer driven tool for product development. Prioritizing Engineering Characteristics (ECs) is a crucial stage in QFD. However, the complex and imprecise factors in QFD present many difficulties for the analysis process of ranking ECs. Even though different techniques have been applied to determine the importance of ECs, they do not fully express all the preferences involved, which could affect the preciseness of results. To address the vague information at the early stage of product development effectively, this paper presents a group multi-granular linguistic-based approach to enable customers or developers to express their preferences using different linguistic label sets. Using different linguistic label sets although makes the process more complicated, it is more meaningful and more practical. Apparently, the proposed method may not only reflect the vague information effectively, but also avoid the risk of information loss. The proposed approach uses a two-phase framework to determine the priority of CRs and evaluate the priority of ECs. A case example is given to illustrate the feasibility and validity of the proposed method. The proposed approach is superior to the existing approach in terms of robustness.
机译：质量功能部署（QFD）是客户驱动的产品开发工具。优先考虑工程特性（EC）是QFD中的关键阶段。然而，QFD中复杂而又不精确的因素给EC的排名分析过程带来了许多困难。即使已采用不同的技术来确定EC的重要性，但它们并未完全表达所有涉及的偏好，这可能会影响结果的准确性。为了有效地解决产品开发初期的模糊信息，本文提出了一种基于多粒度语言的分组方法，使客户或开发人员可以使用不同的语言标签集表达自己的喜好。使用不同的语言标签集虽然会使过程更加复杂，但是却更加有意义和实用。显然，提出的方法不仅可以有效地反映模糊信息，而且可以避免信息丢失的风险。所提出的方法使用两阶段框架来确定CR的优先级并评估EC的优先级。结合算例说明了该方法的可行性和有效性。提出的方法在鲁棒性方面优于现有方法。

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