<p>With the rise of mass individualized customization, the increase in customer-specific requirement data has significantly complicated product configuration design. Traditional configuration methods often simplify the complexity of configuration contents, but this approach fails to deliver solutions that fully meet customer requirements. To address this, this paper proposes an intelligent guided configuration design method based on a knowledge graph. The method begins by constructing a multi-domain product knowledge graph from enterprise design resources. Knowledge fusion across domains is then achieved using operators from C-K theory, which facilitate conceptual expansion and innovative reasoning. Through interactive mapping between customer requirements and the knowledge graph, customized requirement nodes and components are identified to generate configuration solutions. The proposed method demonstrates superior capability in handling complex, multi-domain knowledge and dynamic requirement reasoning compared to traditional approaches, as preliminarily validated through a case study on air purifier configuration.</p>