Product Requirements Cluster Analysis Based on K-Means

Yu-guang Li () and Yong-sheng Huang
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Yu-guang Li: Hebei United University
Yong-sheng Huang: Hebei United University

A chapter in Proceedings of 20th International Conference on Industrial Engineering and Engineering Management, 2013, pp 455-461 from Springer

Abstract: Abstract Mass customization is a new production mode, which is product-family-oriented instead of a single product-oriented, compared with traditional modes. It focuses much more on the group needs of the customer in the phase of product requirements analysis, and cluster analysis becomes a key technology to implement mass customization successfully. K-means as an efficient method and adapted to the large sample of data clustering in the analysis and is widely used. Its number of clusters is determined by way of enumerations, and it is difficult to determine the optimal number of clusters. As the target number of clusters K gradually increases and with combination of research of characteristics of product requirement cluster analysis, a new method for determining the optimal number of clusters based on K-means algorithm is given in this paper.

Keywords: K-means; Mass customization; Product requirement analysis (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-40063-6_46

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DOI: 10.1007/978-3-642-40063-6_46

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