The growing number of waste mobile phones (WMPs) have made recycling an urgent issue. Different disassembly schemes demonstrate varying effectiveness in the large-scale disassembly of WMPs. It is necessary to consider both economic benefits and efficiency improvement comprehensively. This paper applies knowledge reuse and disassembly line balancing to the automated disassembly of multiple types of WMPs. In this regard, descriptive standards for mobile phone disassembly knowledge at different workstations are established based on the theory of knowledge reuse. In light of mobile phone disassembly characteristics, workstation thresholds, threshold intervals, and excessively small thresholds are introduced to improve the selection of disassembly line schemes. Based on a quantitative analysis of disassembly line balancing, the selection schemes for disassembling different batches of phones have been optimized. Case studies are conducted on Android and iOS system smartphones to verify the proposed method. The experimental results demonstrate that our proposed method, which incorporates disassembly knowledge, judgment thresholds, and selection schemes, substantially enhances the accuracy of disassembly line selection. For iOS system phones, designing two lines can disassemble all models of WMPs. For Android system phones, the retirement time of mobile phones influences the selection of lines in the disassembly process. Phones with earlier retirement times are more likely to be selected for simpler disassembly lines. Based on disassembly line balancing, two proposed cases for disassembling different batches of phones increase the overall disassembly efficiency by 48.4 % and 46.7 %, respectively.