王太勇 ,孙熙冉 ,田松龄 ,张 雷 ,马明珠
AuthorsHTML:王太勇 ^{1, 2}，孙熙冉 ¹ ，田松龄 ^{3, 4}，张 雷 ⁵ ，马明珠 ¹
AuthorsListE:Wang Taiyong,Sun Xiran,Tian Songling,Zhang Lei,Ma Mingzhu
AuthorsHTMLE:Wang Taiyong^{1, 2}，Sun Xiran¹，Tian Songling^{3, 4}，Zhang Lei⁵，Ma Mingzhu¹
Unit:1. 天津大学机械工程学院，天津 300350；
2. 天津大学仁爱学院，天津 301636；
3. 天津城建大学控制与机械工程学院，天津 300384；
4. 天津市泰森数控科技有限公司，天津 300392；
5. 天津商业大学机械工程学院，天津 300134

Unit_EngLish:1. School of Mechanical Engineering，Tianjin University，Tianjin 300350，China；
2. Tianjin University Ren’ai College，Tianjin 301636，China；
3. School of Control and Mechanical Engineering，Tianjin Chengjian University，Tianjin 300384，China；
4. Tianjin TSNC Science and Technology Co.，Ltd.，Tianjin 300392，China；
5. School of Mechanical Engineering，Tianjin University of Commerce，Tianjin 300134，China

Abstract_Chinese:模块化的可重构机床使可重构制造系统具备高效生产零件族的能力，对可重构制造系统的可重构能力和响 应能力有着显著影响．为设计一个低成本、高可重构能力的可重构制造系统，提出了一种基于布谷鸟搜索算法的可 重构机床多目标优选方法．首先，通过加工方向建立加工工序与可重构机床的映射关系．其次，考虑到制造系统生 产零件族中不同零件时需进行重构，对可重构机床进行标识以清晰地表述可重构制造系统重构过程中可重构机床的 变化．再次，从设备级和系统级两个层级分别量化了重构过程中的重构成本和重构指数，并基于此提出了两个目标 函数：最小化可重构制造系统设计总成本和最大化总重构指数．最后，通过工程实例来验证该方法的有效性和高效 性．案例结果表明：得到的设计成本最低的方案值为 316.7，最佳的重构指数方案的值为 27.4．此外，与解决此类 问题常用的多目标优化算法 NSGA-Ⅱ比较，多目标布谷鸟搜索(MOCS)算法能快速收敛并在 200 次迭代后取得全局 的 Pareto 最优解，证明了提出的方法能够高效地筛选出更经济、更高重构指数的可重构机床选择方案．所提出的多 目标优选方法可为后续的相关研究和生产实践提供指导．
Abstract_English: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 reconfigurationindex. 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.
Keyword_Chinese:可重构机床；可重构制造系统；机器选择；多目标布谷鸟算法
Keywords_English:reconfigurable machine tool；reconfigurable manufacturing system；machine selection；multi-objective cuckoo search(MOCS) algorithm

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