基于高斯鸽群优化算法的典型工艺知识发现方法
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摘要
针对离散制造系统中典型工艺发现以及知识重用问题,提出了基于高斯鸽群算法的典型工艺知识发现方法.在对工艺路线进行统一编码的基础上,同时考虑了相同工序信息以及工序的排序信息,提出了一种新的综合指标来描述工艺路线之间的相似度,并由此构建了相异度矩阵;同时为了优化聚类分析过程,将高斯项引入鸽群优化算法(Pigeon-inspired Optimization Algorithm,PIO),提出了高斯鸽群优化算法(Gaussian Pigeon-inspired Optimization Algorithm,GPIO),改善了聚类效果,实现了工艺路线的智能聚类并重用工艺知识来优化零件加工过程.最后以企业实际生产制造过程为例,验证了相似度计算方法以及高斯鸽群优化算法(GPIO)的合理性和实用性.
To discover a typical knowledge discovery and reuse process in discrete manufacturing systems,we propose a method of knowledge discovery based on Gaussian pigeon-inspired optimization algorithm. Based on the uniform encoding of process routes,we propose a new comprehensive indexto describe the similarity between process routes using the information of same process and the ordering information. Based on the comprehensive index,we construct the dissimilarity matrix. In addition,to optimize the clustering result,we propose the Gaussian pigeon-inspired optimization algorithm introduced by a Gauss term to achieve an intelligent clustering of process routes,and retrieve process knowledge from the clustering results to optimize the part machining process. Finally,we take a real manufacturing process as an example to verify the rationality and practicability of the similarity calculation method and Gaussian pigeon-inspired optimization algorithm.
To discover a typical knowledge discovery and reuse process in discrete manufacturing systems,we propose a method of knowledge discovery based on Gaussian pigeon-inspired optimization algorithm. Based on the uniform encoding of process routes,we propose a new comprehensive indexto describe the similarity between process routes using the information of same process and the ordering information. Based on the comprehensive index,we construct the dissimilarity matrix. In addition,to optimize the clustering result,we propose the Gaussian pigeon-inspired optimization algorithm introduced by a Gauss term to achieve an intelligent clustering of process routes,and retrieve process knowledge from the clustering results to optimize the part machining process. Finally,we take a real manufacturing process as an example to verify the rationality and practicability of the similarity calculation method and Gaussian pigeon-inspired optimization algorithm.
引文
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[2] Hu J,Li T,Wang H,et al. Hierarchical cluster ensemble model based on knowledge granulation[J]. Knowledge-Based Systems,2016,91(C):179-188.
[3] Liu S,Zhang Z,Tian X. A typical process route discovery method based on clustering analysis[J]. The International Journal of AdvancedManufacturing Technology,2007,35(1):186-194.
[4] Li L,Fuh J Y H,Zhang Y F,et al. Application of genetic algorithm to computer-aided process planning in distributed manufacturing environ-ments[J]. Robotics&Computer Integrated Manufacturing,2005,21(6):568-578.
[5]刘伟,刘振宇,谭建荣.基于工艺相似性的产品模块构建方法及其应用[J].计算机辅助设计与图形学学报,2010,22(10):1647-1654.Liu W,Liu Z Y,Tan J R. Construction of product modules based on process similarity[J]. Journal of Computer-Aided Design&Computer Graphics,2010,22(10):1647-1654.
[6]龙红能,殷国富,成尔京,等.基于实例推理的相似工艺度量算法[J].四川大学学报(工程科学版),2004,36(1):77-82.Long H N,Yin G F,Cheng E J,et al. Algorithm of process similarity analysis from case-based Reasoning[J]. Journal of Sichuan University:Engineering Science Edition,2004,36(1):77-82.
[7]张英杰,屈满仓,李俊民.大型零部件的复杂工艺并行设计方法的研究[J].计算机集成制造系统,2007,13(12):2339-2344.Zhang Y J,Qu M C,Li J M. Concurrent process planning for large parts with complex manufacturing processes[J]. Computer Integrated Manufacturing Systems,2007,13(12):2339-2344.
[8]张辉,裘乐淼,张树有,等.基于智能聚类分析的产品典型工艺路线提取方法[J].计算机集成制造系统,2013,19(3):490-498.Zhang H,Qiu L M,Zhang S Y,et al. Typical product process route extraction method based on intelligent clustering analysis[J]. Computer Integrated Manufacturing Systems,2013,19(3):490-498.
[9] Rekha S B,Muthukumarasamy S,Thanigaivelu K. Balanced clustering in mobile ad hoc networks using route cluster[C]//Proceedings of the IEEE International Conference on Information Communication and Embedded Systems. Piscataway,NJ,USA:IEEE,2016:1-5.
[10]Zhang S,Duan H. Gaussian pigeon-inspired optimization approach to orbital spacecraft formation reconfiguration[J]. Chinese Journal of Aeronautics,2015,8(1):200-205.
[11]He S,Wu Q H,Saunders J R. Group search optimizer:An optimization algorithm inspired by animal searching behavior[J]. IEEE Transactions on Evolutionary Computation,2009,13(5):973-990.
[12]段海滨,叶飞.鸽群优化算法研究进展[J].北京工业大学学报,2017,43(1):1-7.Duan H B,Ye F. Progresses in pigeon-inspired optimization algorithms[J]. Journal of Beijing University of Technology,2017,43(1):1-7.
[13]Kaminski P C,Oliveira A C D,Lopes T M. Knowledge transfer in product development processes:A case study in small and medium enterprises(SMEs)of the metal-mechanic sector from S2o Paulo,Brazil[J]. Technovation,2008,28(1):29-36.
[14]Tam K Y. An operation sequence based similarity coefficient for part families formations[J]. Journal of Manufacturing Systems,1990,9(1):55-68.
[15]Ho Y C,Lee C E,Moodie C. Two sequence-pattern,matching-based,flow analysis methods for multi-flowlines layout design[J]. International Journal of Production Research,1993,31(7):1557-1578.
[16]Askin R G,Zhou M. Formation of independent flow-line cells based on operation requirements and machine capabilities[J]. Iie Transactions,1998,30(4):319-329.
[17]Irani S A,Huang H. Custom design of facility layouts for multiproduct facilities using layout modules[J]. IEEE Transactions on Robotics&Automation,2000,16(3):259-267.
[18]Huang H. Facility layout using layout modules[J]. Dissertation Abstracts International,2003,64-10(B):5153.
[19]Zhou D,Dai X. Integrating granular computing and bioinformatics technology for typical process routes elicitation:A process knowledge acquisition approach[J]. Engineering Applications of Artificial Intelligence,2015,45(1):46-56.
[20]Luan S,Kong X,Wang B,et al. Silhouette coefficient based approach on cell-phone classification for unknown source images[C]//Proceedings of the IEEE International Conference on Communications. Piscataway,NJ,USA:IEEE,2012:6744-6747.
[21]Dey D,Solorio T,G? mez M M,et al. Instance selection in text classification using the silhouette coefficient measure[M]. Berlin,Germnay:Springer,2011:357-369.
[22]刘浩阳. MS SQL数据库在线取证研究[J].信息网络安全,2016(9):26-30.Liu H Y. Research on online forensic of MS SQL database[J]. Netinfo Security,2016(9):26-30.