1. Yalong Intelligent Equipment Group Company Limited, Wenzhou 325105, China
2. School of Mechanical Engineering, North University of China, Taiyuan 030051, China
| Abstract: | In order to improve the quality and efficiency of intelligent design of manufacturing procedure, a identification and optimal correction for manufacturing procedure design defects based on resource limited immune network is proposed. In this immune identification and correction method, the processing process of the parts to be processed and its processing accuracy requirements are taken as antigens, and the process design of a specific production resource is used as an antibody. Firstly, on the basis of four-layer real coding of the manufacturing procedure represented by the antibody, a defect identification factor and a heuristic local mutation rule of manufacturing procedure were designed. Secondly, the defect identification factor and the heuristic local mutation rule were respectively used for intelligent identification and automatic correction of antibodies with design defects, and the modified results are verified by defect identification factors. Finally, three immunological operations, namely selection, mutation and crossover, are used to optimize the antibody, so as to obtain the optimal antibody without processing design defects. Moreover, to realize the correction of nondestructive optimal for machining design defects, the introduction of energy function and penalty factor to ensure the fact that the optimal manufacturing procedure can satisfy all the constraints, and the effectiveness and rationality of the algorithm are verified by numerical examples. |
| Keywords: | Machinability; Design Defect; Resource Limited Immune Network; Identification and Correction |
| DOI: | 10.57237/j.mse.2022.01.002 |
| 1. | 2021年度温州市科协服务科技创新项目 (kjfw40) |
| [1] | 邱清盈, 冯培恩. 制造资源有限情况下产品可加工性定量评价方法研究[J], 计算机辅助设计与图形学学报, 2003, 15 (4): 463-466, 474. |
| [2] | ZHANG H P, GEN M. Multistage-based genetic algorithm for flexible job-shop scheduling problem [J]. Complexity International, 2005, 11: 223-232. |
| [3] | MASTROLILLI M, GAMBARDELLA L M. Effective neighborhood functions for the flexible job shop problem [J]. Journal of Scheduling, 2000, 3 (1): 3-20. |
| [4] | MOHAMMAD S M, PARVIZ F. Flexible job shop scheduling with tabu search algorithms [J]. The International Journal of Advanced Manufacturing Technology (S0268-3768), 2007, 32 (5): 563-570. |
| [5] | 张长泽, 李引珍, 尹胜男, 等. 多目标模糊柔性作业车间调度问题优化 [J]. 科学技术与工程, 2020, 20 (3): 1099-1106. |
| [6] | GAO L, PENG C Y, ZHOU C, et al. Solving flexible job-shop scheduling problem using general particle swarm optimization [C] // Proceedings of The 36th International Conference on Computers & Industrial Engineering, Taipei, China. 2006: 3018-3027. |
| [7] | 张国辉, 高亮, 李培根, 等. 改进遗传算法求解柔性作业车间调度问题 [J]. 机械工程学报, 2009, 45 (7): 145-151. |
| [8] | 刘爱军, 杨育, 邢青松, 等. 多目标模糊柔性车间调度中的多种群遗传算法 [J]. 计算机集成制造系统, 2011, 17 (9): 1954-1961. |
| [9] | 刘璐, 宋海草, 姜天华, 等. 基于改进生物迁徙算法的双资源 柔性作业车间节能调度问题 [J/OL]. 计算机集成制造系统. https://kns.cnki.net/kcms/detail/11.5946.TP.20220711.1504.002.html. |
| [10] | 孙爱红, 宋豫川, 杨云帆, 等. 考虑关键件加工质量的双资源约束柔性作业车间调度算法 [J/OL]. 中国机械工程https://kns.cnki.net/kcms/detail/42.1294.TH.20220104.0839.002.html. |
| [11] | 杨帆, 方成刚, 吴伟伟. 基于遗传-粒子群混合算法的柔性作业车间多资源调度问题 [J]. 制造技术与机床, 2020 (2): 138-142, 146. |
| [12] | 张守京, 杜昊天, 侯天天. 求解多目标双资源柔性车间调度问题的改进NSGA-Ⅱ算法 [J]. 机械科学与技术, 2022, 41 (05): 771-778. |
| [13] | 史峰, 王辉, 胡斐, 等. MATLAB智能算法30个案例分析[M]. 北京: 北京航空航天大学出版社, 2011. |
| [14] | 何斌, 张接信, 张富强. 一种求解作业车间调度问题的改进遗传算法 [J]. 制造业自动化, 2018, 40 (8): 113-117. |
| [15] | 邹泽桦, 曾九孙, 蔡晋辉. 改进遗传算法求解柔性作业车间调度问题 [J]. 计算机测量与控制, 2017, 25 (4): 167-171. |
| [16] | 安璐, 张鹏, 聂宇晨. 改进遗传算法解决带有机器恶化效应的柔性作业车间调度问题 [J]. 大连交通大学学报, 2020, 41 (6): 112-116. |
We invite active, qualified and high profile scientists and researchers to join as Editorial Board Members.
Join UsScholars with a strong interest in reviewing are invited to join the reviewer panel to ensure the quality of the research to be published.
Join Us