Importance determining method of personalized product attributes based on Kano-QFD integration model

被引:0
作者
Sun, Yuan-Yuan [1 ]
Liu, Fui [1 ]
Li, Li [1 ]
机构
[1] State Key Lab of Mechanical Transmission, Chongqing University, Chongqing
来源
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2014年 / 20卷 / 11期
关键词
Attribute index; Customer satisfaction; Kano model; Personalized product; Quality function deployment;
D O I
10.13196/j.cims201411007
中图分类号
学科分类号
摘要
To analyze the customer requirements qualitatively and quantitatively, and to realize the mapping between demand information and personalized product attributes accurately, a new method integrating Kano model with Quality Function Deployment (QFD) model for solving importance of personalized product attributes was proposed. In this method, customer requirements were analyzed and classified with Kano model. To acquire product's customer satisfaction value, the relationship between requirements performance and customer satisfaction was analyzed with investigation, and the customer satisfaction mathematical models of attractive requirement, expected requirement, basic requirement and reverse requirement were established respectively. An adjustment function was used to adjust the importance of each requirement in QFD, which could obtain the importance of personalized product attributes. A certain personalized portrait-based product's optimized design was taken as an example to demonstrate the rationality and feasibility of the proposed method. ©, 2014, CIMS. All right reserved.
引用
收藏
页码:2697 / 2704
页数:7
相关论文
共 27 条
  • [1] Kwong C.K., Wong T.C., Chan K.Y., A methodology of generating customer satisfaction models for new product development using a neuro-fuzzy approach , Expert Systems with Applications, 36, 8, pp. 11262-11270, (2009)
  • [2] Chan L.K., Wu M.L., Quality function deployment: A literature review , European Journal of Operational Research, 143, 3, pp. 463-470, (2002)
  • [3] Sullivan L.P., Quality function deployment , Quality Progress, 34, 6, pp. 39-50, (1986)
  • [4] Williams P., Naumann E., Customer satisfaction and business performance: A firm-level analysis, Journal of Services Marketing, 25, 1, pp. 20-32, (2011)
  • [5] Li S., Li Y., Pu Y., Group-fuzzy-information based analysis method for customer requirements in product planning , Computer Integrated Manufacturing Systems, 18, 9, pp. 2018-2027, (2012)
  • [6] Kazancoglu Y., Aksoy M., A fuzzy logic-based QFD to identify key factors of e-learning design , Procedia-Social and Behavioral Sciences, 28, pp. 322-327, (2011)
  • [7] Nahm Y.E., Ishikawa H., Inoue M., New rating methods to prioritize customer requirements in QFD with incomplete customer preferences , International Journal of Advanced Manufacturing Technology, 65, 9-12, pp. 1587-1604, (2013)
  • [8] van de Poel I., Methodological problems in QFD and directions for future development , Research in Engineering Design, 18, 1, pp. 21-36, (2007)
  • [9] Xu D., Yan H., Mapping and analysis of product characteristics based on fuzzy measurable house of quality , Computer Integrated Manufacturing Systems, 10, 6, pp. 693-698, (2004)
  • [10] Guo Q., Li Y., Pu Y., Et al., Importance determining method of customer requirements based on group semmantic information , Computer Integrated Manufacturing Systems, 18, 4, pp. 840-848, (2012)