Soliciting customer requirements for product redesign based on picture sorts and ART2 neural network

Author(s): Chen, H-C. | Shieh, M.D. | Yan, W. |

Year: 2008

Citation: EXPERT SYSTEMS WITH APPLICATIONS Volume: 34 Issue: 1 Pages: 194-204

Abstract: Design knowledge acquisition plays an extremely important role in new product conceptualization and product redesign. This study aims at facilitating the effectiveness of product redesign activities. It involves two interrelated phases, namely customer requirements elicitation and customer requirements evaluation. Sorting techniques, picture sorts in particular, have been employed for customer requirements acquisition during product redesign process. By applying such a systematic knowledge or requirements acquisition technique, some objectives and constraints of product redesign can then be identified. Furthermore, it has become an imperative to quantitatively and automatically analyze the elicited customer requirements so as to simplify and optimize the subsequent product conceptualization and selection of conceptual design alternatives. For this purpose, the adaptive resonance theory, especially ART2, neural network has been utilized for the preliminary design decisions, such as customer segmentation, in terms of customer requirements evaluation. A case study on the mobile hand phone redesign is used to demonstrate and validate this approach.

Topics: Machine Learning, Applications: Market Research, Models: ART 2 / Fuzzy ART,

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Cross References

  1. ART 2: Self organization of stable category recognition codes for analog input patterns
    Adaptive resonance architectures are neural networks that self-organize stable pattern recognition codes in real-time in response to arbitrary sequences of input patterns. This article introduces ART 2, a class of adaptive ... Article Details