An improved grey quality function deployment approach using the grey TRIZ technique

被引:33
|
作者
Liu, Hao-Tien [1 ]
Cheng, Hung-Sheng [1 ]
机构
[1] I Shou Univ, Dept Ind Management, Kaohsiung 84001, Taiwan
关键词
Product design; Grey QFD; Interval grey number; Grey ranking; Grey TRIZ; SERVICE QUALITY; PRODUCT DESIGN; QFD; MODEL; METHODOLOGY; SELECTION;
D O I
10.1016/j.cie.2015.11.003
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Quality function deployment (QFD) can simultaneously consider both product functions and consumer needs during the product design and manufacturing stages. Traditional QFD often relies on market research or customer questionnaires to collect customer opinions in order to establish customer requirements. However, market research results (or those of customer questionnaires) usually contain a good deal of uncertain and incomplete information. Moreover, there is a practical problem in implementing QFD as experts in specific fields are often rare and difficult to find. In order to resolve these issues, this study integrated interval grey numbers, QFD and TRIZ techniques to develop an improved grey quality function deployment (GQFD) method. GQFD can assist product developers in identifying important engineering characteristics and can provide suggestions for possible improvements in engineering characteristics. Furthermore, this study developed a new grey ranking method to determine the ranking order of interval grey numbers. Finally, a real-world case study in Taiwan was used to explain the research process of the GQFD method and validate the practicality of the proposed method. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:57 / 71
页数:15
相关论文
共 50 条
  • [1] Using grey theory in quality function deployment to analyse dynamic customer requirements
    H.-H. Wu
    A.Y.H. Liao
    P.-C. Wang
    [J]. The International Journal of Advanced Manufacturing Technology, 2005, 25 : 1241 - 1247
  • [2] Using grey theory in quality function deployment to analyse dynamic customer requirements
    Wu, HH
    Liao, AYH
    Wang, PC
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2005, 25 (11-12): : 1241 - 1247
  • [3] Using grey situation decision to analyze the importance of technical measures in quality function deployment
    Wu, Hsin-Hung
    Shieh, Jiunn-I
    [J]. JOURNAL OF STATISTICS & MANAGEMENT SYSTEMS, 2007, 10 (05): : 735 - 742
  • [4] Using grey-quality function deployment to construct an aesthetic product design matrix
    Wang, Nanyi
    Kang, Xinhui
    Wang, Qian
    Shi, Chang
    [J]. Concurrent Engineering Research and Applications, 2023, 31 (1-2): : 49 - 63
  • [5] Applying grey model to prioritise technical measures in quality function deployment
    Wu, Hsin-Hung
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2006, 29 (11-12): : 1278 - 1283
  • [6] Applying grey model to prioritise technical measures in quality function deployment
    Hsin-Hung Wu
    [J]. The International Journal of Advanced Manufacturing Technology, 2006, 29 : 1278 - 1283
  • [7] INTEGRATION OF TRIZ INTO QUALITY FUNCTION DEPLOYMENT
    Tursch, Philipp
    Goldmann, Christine
    Woll, Ralf
    [J]. MANAGEMENT AND PRODUCTION ENGINEERING REVIEW, 2015, 6 (02) : 56 - 62
  • [8] Qality function deployment based on grey relational analysis
    Li, Liang
    Guo, Qi-Sheng
    Li, Yong
    Yang, Yu
    [J]. Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS, 2007, 13 (12): : 2469 - 2472
  • [9] Grey number prediction using the grey modification model with progression technique
    Shih, Chi-Sheng
    Hsu, Yen-Tseng
    Yeh, Jerome
    Lee, Pin-Chan
    [J]. APPLIED MATHEMATICAL MODELLING, 2011, 35 (03) : 1314 - 1321
  • [10] Potential Output Estimate Using a Grey Production Function Approach
    Andrei, Ana Michaela
    Galupa, Angela
    Georgescu, Irina
    [J]. JOURNAL OF GREY SYSTEM, 2017, 29 (01): : 1 - 14