In order to enhance the quality of customized furniture panel processing, avoid information silos between workstations, and promote intelligent manufacturing in customized furniture enterprises, this study constructs a knowledge graph focused on the full lifecycle data of customized furniture panel production. Firstly, the data from the production department of the enterprise is organized and preprocessed, including tokenization, annotation, and other preprocessing techniques, to establish the data layer of the knowledge graph. Secondly, based on real enterprise data, an ontology model is constructed to complete the pattern layer construction of the knowledge graph. Finally, the GPLinker model is utilized for highprecision knowledge extraction of entity relationships. The research results demonstrate that by constructing a knowledge graph focused on the full lifecycle data of customized furniture panel production, interconnectivity and interoperability of data throughout the entire lifecycle of a customized furniture enterprise can be achieved, providing a scientific basis for decision-making in addressing processing anomalies.