The Evaluation Model of Product Satisfaction Based on Cloud Model


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Traditional methods such as scoring method, Likert scale method, etc, suffer from uncertainness, randomness and inaccuracy. To solve these problems, a cloud model is presented in this paper. Based on fuzzy mathematics and statistics, the cloud model can convert the qualitative evaluation of the product to quantitative scores. It’s a better way to overcome the disadvantages of direct scoring method that cause more inaccuracies. A prouct satisfaction evaluation model with three dimensions (i.e., evaluation index, product sets and estimator) is then constructed, which combines the cloud model and the grey relational analysis. Finally, the effectivity of the presented model is demonstrated by a case study.



Key Engineering Materials (Volumes 467-469)

Edited by:

Dehuai Zeng




Y. L. Fei et al., "The Evaluation Model of Product Satisfaction Based on Cloud Model", Key Engineering Materials, Vols. 467-469, pp. 1193-1199, 2011

Online since:

February 2011




[1] Hu Qi-guo, Zhang Peng, Zhang Fu-ren. Study on indices system of customer satisfaction degree for manufacture industry[J]. Machinery Design & Manufacture, 2009, 9(9): 263-265.

[2] Hua Ertian, Huang Fengli, Pei Renqing. Study on Product Satisfaction Index Prediction and Error Controlling Mode[J]. Mechanical & Electrical Engineering Magazine, 2003, 20(4): 75-77.

[3] Hua Ertian, Li Guofu, Mao Mingjie, Gao Jianhua, Pei Renqing, Ye Feifan. Product Customer Satisfaction Predictive Model Based on LS[J]. China Mechanical Engineering, 2005, 16(20): 1831-1834.

[4] Huang Feng-Li, Lin Jian-Ping, Zhang Wei. A clustering method of extension based on customer satisfaction applied in the innovative design of product[J]. Machinery Design & Manufacture, 2008, 1(1): 212-214.

[5] Liang Ji, Zhang Peng, Han Xia. Customer satisfaction-oriented improved I-Kano model of decision-making[J]. Statistics and Decision, 2009, 20: 152-153.

[6] Li Yanlai, Luo Xinggang, Yao Jianming, Jiao Minghai. Method for Determining the Final Importance Ratings of Engineering Characteristics in House of Quality Based on the Competitive Evaluations[J]. China Mechanical Engineering, 2009, 20(19): 2362-2386.

[7] Sun Changsen. The evaluation research on customer satisfaction to individual requirement products under the mode of mass customization[J]. Science Research and Management, Vol 30, March, 2009: 203-212.

[8] Li Deyi, Du Yi. Artificial Intelligence with Uncertainty[M]. Beijing: National Defense Industry Press, (2005).

[9] Li Fengping, Zhou Yuqing, Fu Peihong, Xue Wei. Research on Three-dimensional Hierarchy Evaluation Model of Customer Satisfaction Based on Grey Relational Analysis[J]. China Mechanical Engineering, 2009, 20(12): 1445-1449.

[10] Inge Brechan. The different effect of primary and secondary product attributes on customer satisfaction[J]. Journal of Economic Psychology, 27 (2006) 441–458.


[11] Shan Ren-Liang, Huang Bao-Long, Li Guang-Jing. Comprehensive evaluation model based on gray correlative analysis and its application to selecting blasting scheme[J]. Rock and Soil Mechanics, Vol. 30 Supp, Aug, 2009: 206-210.

[12] Zhang Xianhong, Wang Jinlei, Peng Yinghong. Improved Analysis of Hierarchy Process and Its Application to Cold Extrusion Process Planning CBR System[J]. China Mechanical Engineering, 2002, 13(16): 1361-1364.

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