[1]YANG Dong-sheng,KANG Qi,LIU Bo,et al.Swarm intelligence analysis of primary and secondary causes of defective products for manufacturing system[J].CAAI Transactions on Intelligent Systems,2009,4(6):502-507.[doi:10.3969/j.issn.1673-4785.2009.06.006]
Copy

Swarm intelligence analysis of primary and secondary causes of defective products for manufacturing system

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 4 Number of periods: 2009 6 Page number: 502-507 Column: 学术论文—智能系统 Public date: 2009-12-25
Title:
Swarm intelligence analysis of primary and secondary causes of defective products for manufacturing system
Author(s):
YANG Dong-sheng1; 3;  KANG Qi1; 2;  LIU Bo1;  WANG Lei1; 2;  WU Qi-di1; 2
1. College of Electronics and Information Engineering, Tongji University, Shanghai 201804， China; 2. Key Laboratory of Embedded System and Computerservice of Ministry of Education, Tongji University, Shanghai 201804， China; 3. Shanghai Economic and Information Committee, Shanghai 200040， China
Keywords:
swarm intelligence;  semiconductor manufacturing;  primary and secondary causes;  intelligent analysis
CLC:
TP18
DOI:
10.3969/j.issn.1673-4785.2009.06.006
Abstract:
Understanding and reducing both primary and secondary causes of defective products is an important part of quality control in semiconductor manufacturing. By applying a swarm intelligence optimization concept to the bump reflow process, the authors were able to formulate a novel analytical method for analyzing the primary and secondary causes of defective products. Their method used swarm heuristic information to reduce computational complexity when processing large amounts of production data. Numerical simulations based on actual production data were performed to verify the proposed method. The results showed its validity.
References:
［1］KENNEDY J, EBERHART R C. Swarm intelligence［M］. San Francisco: Morgan Kaufmann,2001:18-32.
［2］REYNOLDS C. Flocks, herds, and schools: a distributed behavioral model［J］. Computer Graphics,1987,21(4):25-34.
［3］吴启迪，汪    镭．群体智能计算模式及应用［M］．南京：江苏教育出版社，2006：28-34.
［4］CARLOS A C, GREGORIO T P，MAXIMINO S L. Handling multiple objectives with particle swarm optimization［J］. IEEE Trans on Evolutionary Computation,2004,8(3):256-279.
［5］YOSHIDA H， KAWATA K， FUKUYAMA Y. A particle swarm optimization for reactive power and voltage control considering voltage security assessment［J］. IEEE Transaction on Power Systems, 2000,15(4):1232-1240.
［6］SIM K M, SUN Wenghong. Ant colony optimization for routing and loadbalancing: survey and new directions［J］. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, 2003,33(5):560-572.
［7］ZHANG Z X, LU C W. Application of the improved particle swarm optimizer to vehicle routing and scheduling problems ［C］//IEEE Int Conf on Grey Syst Intell Services. Nanjing, China, 2007：150-152.
［8］GERASIMOS G. Multirobot motion planning using swarm intelligence［J］. International Journal of Advanced Robotic Systems, 2008,5(2):139-144.
［9］LIU B, WANG L, JIN Y H. An effective PSObased memetic algorithm for flow shop scheduling［J］.IEEE Transactions on Systems, Man, and CyberneticsB,2007,37(1):18-27.
Similar References:

Memo

-

Last Update: 2010-02-22

Copyright © CAAI Transactions on Intelligent Systems