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Graph-based knowledge reuse for supporting knowledge-driven decision-making in new product development

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  • Chao Zhang
  • Guanghui Zhou
  • Qi Lu
  • Fengtian Chang

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.

Suggested Citation

  • Chao Zhang & Guanghui Zhou & Qi Lu & Fengtian Chang, 2017. "Graph-based knowledge reuse for supporting knowledge-driven decision-making in new product development," International Journal of Production Research, Taylor & Francis Journals, vol. 55(23), pages 7187-7203, December.
    • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:23:p:7187-7203
    DOI: 10.1080/00207543.2017.1351643
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    References listed on IDEAS

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    1. Jonathon N. Cummings, 2004. "Work Groups, Structural Diversity, and Knowledge Sharing in a Global Organization," Management Science, INFORMS, vol. 50(3), pages 352-364, March.
    2. Paula Andrea Potes Ruiz & Bernard Kamsu-Foguem & Daniel Noyes, 2013. "Knowledge reuse integrating the collaboration from experts in industrial maintenance management," Post-Print hal-00861829, HAL.
    3. Aven, Terje & Zio, Enrico, 2011. "Some considerations on the treatment of uncertainties in risk assessment for practical decision making," Reliability Engineering and System Safety, Elsevier, vol. 96(1), pages 64-74.
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    Cited by:

    1. Salvatore F. Pileggi, 2019. "Is the World Becoming a Better or a Worse Place? A Data-Driven Analysis," Sustainability, MDPI, vol. 12(1), pages 1-24, December.
    2. Wang, Qun & Jia, Guozhu & Jia, Yuning & Song, Wenyan, 2021. "A new approach for risk assessment of failure modes considering risk interaction and propagation effects," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    3. Xiaolin Shi & Xitian Tian & Jianguo Gu & Fan Yang & Liping Ma & Yun Chen & Tianyi Su, 2022. "Knowledge Graph-Based Assembly Resource Knowledge Reuse towards Complex Product Assembly Process," Sustainability, MDPI, vol. 14(23), pages 1-16, November.

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