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A fuzzy CBR technique for generating product ideas
(2008-01-01)
Wu, Muh-Cherng
;
Lo, Ying-Fu
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Hsu, Shang-Hwa
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工業工程與管理學系
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Department of Industrial Engineering and Management
This paper presents a fuzzy CBR (case-based reasoning) technique for generating new product ideas from a product database for enhancing the functions of a given product (called the baseline product). In the database, a product is modeled by a 100-attribute vector, 87 of which are used to model the use-scenario and 13 are used to describe the manufacturing/recycling features. Based on the use-scenario attributes and their relative weights - determined by a fuzzy AHP technique, a fuzzy CBR retrieving mechanism is developed to retrieve product-ideas that tend to enhance the functions of the baseline product. Based on the manufacturing/recycling features, a fuzzy CBR mechanism is developed to screen the retrieved product ideas in order to obtain a higher ratio of valuable product ideas. Experiments indicate that the retrieving-and-filtering mechanism outperforms the prior retrieuing-only mechanism in terms of generating a higher ratio of valuable product ideas. (c) 2006 Elsevier Ltd. All rights reserved.