Enhancing novel product iteration: An integrated framework for heuristic ideation via interpretable conceptual design knowledge graph

Yangfan Cong, Suihuai Yu, Jianjie Chu, Yuexin Huang, Ning Ding, Cong Fang, Stephen Jia Wang

Research output: Contribution to journalArticlepeer-review

Abstract

Novel products emerge over time to survive the competitive landscape as no existing product can perpetually satisfy all evolving customer expectations. These products are often characterized by groundbreaking solutions previously unavailable on the market. However, the swift imitation of successful novel products by competitors underscores the need for sustained iteration and continuous improvement. Designers increasingly face challenges in keeping up to date with the growing volume and fragmented nature of design information from diverse sources. While knowledge graphs show promise in structuring and organizing complex design information, their effective application in the ideation process remains limited due to difficulties in automatic knowledge extraction and the lack of interpretability aligned well with designers’ cognitive processes. This study proposes an integrated method to construct an interpretable conceptual design knowledge graph (I-CDKG) that features both inherent and acquired interpretability for heuristic product ideation. First, the schema layer models product design knowledge and governs the semantic connection of design information reinforced by design cognition principles to create a reasonable organizational framework to foster intuitive knowledge exploration. Second, the data layer mainly fulfills automatic and smooth design knowledge extraction for I-CDKG construction through the deep learning ERNIE-BiGRU-CRF model combined with BIESO labeling mode and triple-extracting algorithm. Third, the application layer empowers designers to visually delve into interpretable design knowledge to locate inspiration from cluster, relation, and nest levels and enable constant I-CDKG expansion as design schemes proliferate. A case study on the smart cat litter box demonstrates the feasibility of the proposed methodology. The evaluation results confirm the I-CDKG's advantages as a productive design tool for inspiring creative, practical, and cost-effective product ideations, thereby empowering the iterative development of competitive novel products.

Original languageEnglish
Article number103131
JournalAdvanced Engineering Informatics
Volume65
DOIs
StatePublished - May 2025

Keywords

  • Conceptual product design
  • Design knowledge
  • Heuristic product ideation
  • Interpretable knowledge graph
  • Novel product iteration

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