A fuzzy CBR technique for generating product ideas

  • Authors:

  • Muh-Cherng Wu;Ying-Fu Lo;Shang-Hwa Hsu

  • Affiliations:

  • Department of Industrial Engineering and Management, National Chiao Tung University, Hsin-Chu, Taiwan, ROC;Department of Industrial Engineering and Management, National Chiao Tung University, Hsin-Chu, Taiwan, ROC;Department of Industrial Engineering and Management, National Chiao Tung University, Hsin-Chu, Taiwan, ROC

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2008

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Abstract

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 retrieving-only mechanism in terms of generating a higher ratio of valuable product ideas.