Multi-Objective Optimization Selection Method for the Reconfigurable Machine Tool

The modular reconfigurable machine tool(RMT) enables the reconfigurable manufacturing system(RMS) to produce part families efficiently, which has a significant effect on the reconfigurability and responsiveness of the RMS. To design an RMS with a low cost and high reconfigurable capability, a multi-objective optimization method for the RMT based on the cuckoo search algorithm is proposed. First, the mapping relationship between operations and RMTs is established by machining direction. Second, considering that reconfiguration is required in a manufacturing system to produce the different parts in a part family, the RMT is identified to clearly describe the change in the RMT in the reconfiguration process of the RMS. Third, the reconfiguration cost and reconfiguration index in the reconfiguration process are quantified from the machine level and system level, respectively. Based on this analysis, two objective functions are proposed: minimizing the design cost of the RMS and maximizing the reconfiguration index. Finally, the effectiveness of the method is verified using an engineering example. The case results show that the lowest design cost is 316.7, while the best reconfiguration index is 27.4. In addition, compared with NSGA-Ⅱ, a commonly used multi-objective optimization algorithm, the multi-objective cuckoo search(MOCS) can quickly converge and obtain the global Pareto optimal solution after 200 iterations, and it is proved that the proposed method can quickly screen out the RMT selection solution with a more economical and higher reconfiguration index. The proposed multi-objective optimization method can provide guidance for subsequent research and production practice. © 2021, Editorial Board of Journal of Tianjin University(Science and Technology). All right reserved.