Abstract
Pre-existing knowledge buried in manufacturing enterprises can be reused to help decision-makers develop good judgements to make decisions about the problems in new product development, which in turn speeds up and improves the quality of product innovation. This paper presents a graph-based approach to knowledge reuse for supporting knowledge-driven decision-making in new product development. The paper first illustrates the iterative process of knowledge-driven decision-making in new product development. Then, a novel framework is proposed to facilitate this process, where knowledge maps and knowledge navigation are involved. Here, OWL ontologies are employed to construct knowledge maps, which appropriately capture and organise knowledge resources generated at various stages of product lifecycle; the Personalised PageRank algorithm is used to perform knowledge navigation, which finds the most relevant knowledge in knowledge maps for a given problem in new product development. Finally, the feasibility and effectiveness of the proposed approach are demonstrated through a case study and two performance evaluation experiments.
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