As a customer-driven quality improvement tool, quality function deployment (QFD) can convert customer requirements (CRs) into appropriate engineering characteristics (ECs) in product design and development. However, the conventional QFD method has been criticized for a variety of drawbacks, which limit its efficiency and potential applications. In this study, a new QFD approach integrating picture fuzzy linguistic sets (PFLSs) and the evaluation based on distance from average solution (EDAS) method is proposed for the determination of ranking order of ECs. The PFLSs are utilized to express the judgements of experts on the relationships among CRs and ECs. Then, the EDAS method is extended under picture fuzzy linguistic environment for the prioritization of the ECs identified in QFD. Moreover, a combined weighing method based on technique for order of preference by similarity to ideal solution (TOPSIS) and maximum entropy theory is established to calculate the weights of experts objectively. Finally, a product-service system design is provided to illustrate the effectiveness of the proposed QFD approach. The result shows that the manufacturer should pay more attention to “Meantime before failure”, “Warning feature” and “Quality of product manual”. Feedback from domain experts indicates that the integrated approach being proposed in this paper is more suitable for assessing and prioritizing ECs in QFD.

作为客户驱动的质量改进工具，质量功能部署（QFD）可以将客户需求（CR）转换为产品设计和开发中的适当工程特征（EC）。但是，传统的QFD方法因存在许多缺点而受到批评，这限制了它的效率和潜在的应用范围。本文提出了一种结合图像模糊语言集（PFLSs）和基于距离平均解法（EDAS）的评估的QFD方法来确定EC的排序顺序。PFLS用于表达专家对CR与EC之间关系的判断。然后，在图像模糊语言环境下扩展了EDAS方法，以便对QFD中确定的EC进行优先级排序。此外，建立了基于与理想解相似度（TOPSIS）和最大熵理论的偏好排序技术的组合加权方法，以客观地计算专家的权重。最后，提供了产品服务系统设计，以说明所提出的QFD方法的有效性。结果表明，制造商应更加注意“故障前平均时间”，“警告功能”和“产品手册质量”。领域专家的反馈表明，本文提出的集成方法更适合评估QFD中的EC并确定其优先级。提供了产品服务系统设计，以说明所提出的QFD方法的有效性。结果表明，制造商应更加注意“故障前平均时间”，“警告功能”和“产品手册质量”。领域专家的反馈表明，本文提出的集成方法更适合评估QFD中的EC并确定其优先级。提供了产品服务系统设计，以说明所提出的QFD方法的有效性。结果表明，制造商应更加注意“故障前平均时间”，“警告功能”和“产品手册质量”。领域专家的反馈表明，本文提出的集成方法更适合评估QFD中的EC并确定其优先级。