A novel method of optimized selective assembly for remanufactured products

The assembly of remanufactured machine tools is crucial for ensuring their accuracy. Poor assembly accuracy, low remanufacturing resource utilization, and inefficient assembly have become common issues in remanufacturing processes. This limitation is addressed in the study, wherein Taguchi’s mass loss function (QLF) and a cost function for the remaining parts are employed. Both assembly accuracy and minimum cost are ensured through the establishment of a comprehensive matching model with closed-loop dimensional chains as constraints. The solution process of the PSO-GA model is outlined, effectively reducing uncertainty and resource waste associated with impractical matching schemes. Practical results from the CAK6163 headstock demonstrate that not only is the low success rate issue in matching remanufactured parts resolved by the proposed method, but resource utilization is also significantly enhanced, and costs are reduced.