Title

Planning product configurations based on sales data

Document Type

Article

Peer Reviewed

1

Publication Date

1-1-2007

Journal/Book/Conference Title

IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews

Abstract

Manufacturing companies are currently focusing on mass customization. Delivering products that meet the requirements of individual customers complicates the production process, and diminishes the benefits of the economy of scale. By exploring commonality among products, this complexity can be significantly reduced. To determine product configurations sought by the customers and to produce them in large quantities, a new approach is proposed. The proposed approach uses a modified k-means clustering algorithm to analyze past sales data for capturing prime product configurations. The most suitable configurations are selected by solving an integer-programming model or using a sorting-based algorithm. The proposed approach was tested with an industrial case study involving sales data of large trucks collected over a period of one year. 2007 IEEE.

Keywords

Sustainability

Published Article/Book Citation

IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews, 37:4 (2007) pp.602-609.

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URL

http://ir.uiowa.edu/mie_pubs/154