Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICICS.2007.4449767
Title: Deriving configuration knowledge and evaluating product variants through intelligent techniques
Authors: Liu, H.
Huang, Y.
Ng, W.-K.
Song, B.
Li, X.
Lu, W.-F. 
Issue Date: 2007
Source: Liu, H.,Huang, Y.,Ng, W.-K.,Song, B.,Li, X.,Lu, W.-F. (2007). Deriving configuration knowledge and evaluating product variants through intelligent techniques. 2007 6th International Conference on Information, Communications and Signal Processing, ICICS : -. ScholarBank@NUS Repository. https://doi.org/10.1109/ICICS.2007.4449767
Abstract: Mass customization has become a crucial business strategy for product manufacturers that aims at satisfying individual customer needs with near mass production efficiency. Companies must develop the necessary infrastructure to derive valid product configurations that satisfy the requirements of lifecycle cost along with customer's constraints. In this paper, to overcome the drawback of current product configurators, we apply a rule mining approach to automatically generate configuration knowledge, and present a hybrid approach based on Activity Based Costing (ABC) and machine learning techniques to estimate LCC of derived product variants from a constraint-based configurator at the design stage. The proposed intelligent techniques would benefit companies in enhancing product development capability in a shorter lifecycle. © 2007 IEEE.
Source Title: 2007 6th International Conference on Information, Communications and Signal Processing, ICICS
URI: http://scholarbank.nus.edu.sg/handle/10635/73313
ISBN: 1424409837
DOI: 10.1109/ICICS.2007.4449767
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