Abstract: Efficient reuse of process knowledge is the key to alleviate the high dependence of remanufacturing process planning on manual labor. However, due to the multi-source heterogeneous characteristics of remanufacturing process entities and the low efficiency of knowledge retrieval, the reuse of remanufacturing process knowledge still faces great challenges. Based on this, this paper proposes an efficient reuse method for remanufacturing process knowledge based on multi-source heterogeneous entity alignment and key node matching. Firstly, based on the BERT-BiLSTM-CRF model and rule-based knowledge extraction, an entity alignment method based on attribute similarity and embedding similarity is proposed to solve the problems of inconsistent triples extracted from different sources and knowledge redundancy; further, a remanufacturing process planning method based on key node fault similarity matching is proposed to achieve efficient reuse of knowledge. Finally, the feasibility and superiority of this method are verified by the crankshaft remanufacturing case. The results show that the construction of the knowledge graph in this paper not only realizes the structured storage and unified management of remanufacturing case data, but the proposed fusion algorithm is significantly better than the commonly used attribute similarity and TransE-based entity alignment methods in the entity alignment task. The key node similarity retrieval accuracy is better than the global similarity and the retrieval time is reduced by 19%, which provides a new idea and solution for the efficient reuse of remanufacturing process knowledge.