Development of a fuzzy-rule based system for product development in the garment industry

The garment industry has been in a transformation since the emergence of the fast fashion trend. For business survival, garment manufacturers are required to shorten the time to market and develop products which can meet the changing expectations of customers. This exerts a great pressure on fashion designers who are urged to consider customers´ preferences in their designs and develop new products efficiently. Historical data related to product design and customer purchasing behavior thus serves as important information for effective new product development (NPD). In this paper, a fuzzy-rule based system (FBS) is developed to discover relationships between product styles and customer preferences from historical data. The knowledge discovered can help the industry design products which are not only fashionable, but are also saleable in the market. To evaluate the proposed system, a case study is conducted in which a real-set of data are tested to generate fuzzy decision rules. The results reveal that the FBS can provide knowledge support to NPD in the garment industry.