Analysis of user preference is among the crucial tasks at early stages of new product development (NPD). In order to satisfy diversified user preferences in the market, product companies have struggled to design a variety of products to address different customer voices. In this context, product family design (PFD) is a widely adopted strategy to deal with such product realization needs. Besides preference diversity, uncertainty of user preference is another important aspect that can greatly affect product design and offerings especially when customer preferences are not clear, not fully identified, or have drifted overtime. Previously, we have studied an ontology-based information representation for PFD, which offers a modeling scheme to assist multi-faceted product variant derivation. In this paper, we explore how ontology can be further extended to handle user preference uncertainty by using a Bayesian network representation. Customer preference uncertainty is expressed as a probability of preference towards certain product attributes. An approach to construct a Bayesian network that harnesses the existing knowledge modeling from product family ontology is proposed. Based on such a network representation and preference modeling, we have derived several probabilistic measures to assess the propagation and impact of user preference uncertainty towards platform preference. A case study of platform analysis using four laptop computer families is reported to illustrate how preference uncertainty can affect the suitability and selection of existing product platform.
- Design Engineering Division
- Computers and Information in Engineering Division
An Exploratory Study of Ontology-Based Platform Analysis Under User Preference Uncertainty
Lim, SCJ, Liu, Y, & Loh, HT. "An Exploratory Study of Ontology-Based Platform Analysis Under User Preference Uncertainty." Proceedings of the ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 2: 32nd Computers and Information in Engineering Conference, Parts A and B. Chicago, Illinois, USA. August 12–15, 2012. pp. 519-528. ASME. https://doi.org/10.1115/DETC2012-70756
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