# Frontiers of Engineering Management

 Front. Eng    2020, Vol. 7 Issue (2) : 196-203     https://doi.org/10.1007/s42524-019-0038-z
 RESEARCH ARTICLE
Improved approach to quality function deployment based on Pythagorean fuzzy sets and application to assembly robot design evaluation
Huchang LIAO, Yinghan CHANG, Di WU, Xunjie GOU()
Business School, Sichuan University, Chengdu 610064, China
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 Abstract Quality function deployment (QFD) is an effective method that helps companies analyze customer requirements (CRs). These CRs are then turned into product or service characteristics, which are translated to other attributes. With the QFD method, companies could design or improve the quality of products or services close to CRs. To increase the effectiveness of QFD, we propose an improved method based on Pythagorean fuzzy sets (PFSs). We apply an extended method to obtain the group consensus evaluation matrix. We then use a combined weight determining method to integrate former weights to objective weights derived from the evaluation matrix. To determine the exact score of each PFS in the evaluation matrix, we develop an improved score function. Lastly, we apply the proposed method to a case study on assembly robot design evaluation. Corresponding Author(s): Xunjie GOU Just Accepted Date: 29 April 2019   Online First Date: 30 May 2019    Issue Date: 27 May 2020
 Cite this article: Huchang LIAO,Yinghan CHANG,Di WU, et al. Improved approach to quality function deployment based on Pythagorean fuzzy sets and application to assembly robot design evaluation[J]. Front. Eng, 2020, 7(2): 196-203. URL: http://journal.hep.com.cn/fem/EN/10.1007/s42524-019-0038-z http://journal.hep.com.cn/fem/EN/Y2020/V7/I2/196
 Tab.1  Evaluation matrix of expert $e1$ Tab.2  Evaluation matrix of expert $e2$ Tab.3  Evaluation matrix of expert $e3$ Tab.4  Integrated matrix Tab.5  Similarity degrees and deviations of experts Tab.6  Score values of all elements of the integrated matrix Tab.7  Correlation coefficients between each pair of different demands
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