Product Functional Degradation Assessment Based on Interval Number Prediction

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  • 1. School of Mines, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China; 2. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Received date: 2019-05-15

  Online published: 2020-12-04

Abstract

The dynamics of customer requirement makes product evolution inevitable. The essence of product evolution is the divergence between the function of present product and customer requirements expectation, which is defined as product functional degradation. The identification of degraded function is the precondition for product redesign and evolution. Therefore, a method for assessing the degradation of product function is proposed. First, customer requirements are converted into function requirements based on quality function deployment, and the importance rate of function requirement is calculated by using the rough set theory and Kano index. Then, the predicted value of the value range of future product engineering characteristics is used to represent the expected design range. The difference between the value range of engineering characteristics of existing products and the design range of customer expectation is calculated by using the projection method. The functional degradation index is obtained based on the importance of functional requirements, the difference degree between engineering characteristics, and the weight of engineering characteristics. Finally, a crawler crane is taken as the research object for case analysis. The results show that the functional degradation evaluation obtained by the proposed method is consistent with the actual analysis results, which indicates that the proposed method has a certain effectiveness and practical feasibility.

Cite this article

ZHAO Zhihua,LI Yupeng,CHU Xuening . Product Functional Degradation Assessment Based on Interval Number Prediction[J]. Journal of Shanghai Jiaotong University, 2020 , 54(11) : 1172 -1181 . DOI: 10.16183/j.cnki.jsjtu.2020.99.016

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