Some prior research adopts advanced

Some prior research adopts advanced searching algorithms to discover the best sequences ofproduct disassembly. Aguinaga et al. [55] employ a method using fast-growing random trees to find the best product disassembly sequences. Kara et al. [56] propose an approach to derive reversed assembly sequences, and utilize a liaison diagram to evaluate geometric connections in order to find the optimal disassembly sequences of a product. However, this method requires a lot of computing resources to generate sequence diagrams, and the infeasible sequences must be removed in the process. Shyamsundar and Gadh [57] present a regressive approach that takes into account both the separating direction and decomposing direction to disassemble the components of the target product. However, these approaches lead to many paths, so it takes a lot of time to find a solution. Moreover, neither thetime needed nor outcomes obtained can be guaranteed. Furthermore, the resulting sequences are often not optimal solutions and usually include interfering elements. Most of the studies discussed above address the problem of product disassembly by considering all geometric limitations and evaluating each disassembly order to discover the best solution