A multi-type product design knowledge recommendation method for product conceptual design process

The product conceptual design (PCD) process involves the integration, reasoning and reuse of multi-type product design knowledge (MTPDK) such as semantics, patents and case studies. To fully exploit the motivating potential of MTPDK, this paper proposes a recommendation method, which achieves a deeper integration between knowledge resources and the PCD process. First, a product design knowledge graph (PDKG) is constructed to represent semantic and patent knowledge through inter-entity relationships, while historical cases are encoded by connecting entities across layers via hyperedges. Next, the PCD process is formalized through the integration of Axiomatic Design (AD) and the Theory of Inventive Problem Solving (TRIZ), enabling a systematic analysis of knowledge requirements across different design stages. Based on the mapping of design problems across different dimensions, relevant MTPDK is recommended to designers. Specifically, a semantic activation diffusion algorithm is employed to support the zigzag mapping mechanism within AD, ensuring the rationality of the analysis and transformation processes. In parallel, patent knowledge novelty is evaluated to guide the application of TRIZ principles during the design matrix decoupling process. Furthermore, the case-matching degree is calculated to identify historical cases most relevant to the current design scenario, thereby facilitating adaptive design support. Subsequently, the proposed method is applied to the weeding equipment design process. The F₁ value of the knowledge recommendation result reaches 0.83, which verifies the feasibility and effectiveness of the proposed method. Finally, the comparative analyses demonstrate the superior performance of the proposed method.