Reliability optimisation method for intelligent manufacturing systems based on particle swarm optimisation algorithm

被引:0
|
作者
Ren, Li [1 ]
Li, Juchen [1 ,2 ]
机构
[1] Intelligent Manufacturing College, Anhui Wenda University of Information Engineering, Hefei
[2] Faculty of Engineering, Technology and Built Environment, UCSI University, Kuala Lumpur
关键词
allocation criteria; decision model; fuzzy logic; intelligent manufacturing system; particle swarm optimisation;
D O I
10.1504/IJMIC.2024.144028
中图分类号
学科分类号
摘要
This paper proposes a reliability optimisation method for intelligent manufacturing systems based on particle swarm optimisation algorithm in order to improve the reliability and accuracy of resource allocation in intelligent manufacturing systems. Firstly, reliability assignment criteria for intelligent manufacturing systems are designed, subjective factors are evaluated through experts, and the fuzzy logic method is used to calculate the weight of the influencing factors; then, the reliability problem of intelligent manufacturing system is described, and the reliability decision model of intelligent manufacturing system is constructed; finally, the particle swarm optimisation algorithm is used to obtain the optimal resource allocation for the intelligent manufacturing system, maximising its reliability. The experimental results show that the resource allocation reliability of our method can reach 99.5%, and the resource allocation accuracy can reach 99.8%. Our method can improve the resource allocation efficiency of intelligent manufacturing systems. © 2024 Inderscience Enterprises Ltd.
引用
收藏
页码:200 / 210
页数:10
相关论文
共 50 条
  • [1] A particle swarm optimisation algorithm for cloud-oriented workflow scheduling based on reliability
    Jian, Chengfeng
    Tao, Meng
    Wang, Yekun
    INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY, 2014, 50 (3-4) : 220 - 225
  • [2] Intelligent colour selection method for product packaging design based on particle swarm optimisation
    Fan J.
    International Journal of Manufacturing Technology and Management, 2023, 37 (02) : 162 - 172
  • [3] AHPSO: Altruistic Heterogeneous Particle Swarm Optimisation Algorithm for Global Optimisation
    Varna, Fevzi Tugrul
    Husbands, Phil
    2021 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI 2021), 2021,
  • [4] Distributed resource allocation optimisation algorithm based on particle swarm optimisation in wireless sensor network
    Hao, Xiaochen
    Yao, Ning
    Wang, Jiaojiao
    Wang, Liyuan
    IET COMMUNICATIONS, 2020, 14 (17) : 2990 - 2999
  • [5] Particle swarm optimisation algorithm with forgetting character
    Yuan, Dai-lin
    Chen, Qiu
    INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION, 2010, 2 (01) : 59 - 64
  • [6] FUZZY CONTROL ROBOT ENERGY SAVING METHOD BASED ON PARTICLE SWARM OPTIMISATION ALGORITHM
    Long, Zuqiang
    Wang, Yunmeng
    Luo, Zelong
    INTERNATIONAL JOURNAL OF ROBOTICS & AUTOMATION, 2024, 39 (06) : 482 - 489
  • [7] Particle swarm optimisation algorithm for radio frequency identification network topology optimisation
    Zhang, Li
    Lu, Jin-gui
    Chen, Lei
    Zhang, Jian-de
    INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING, 2011, 6 (1-2) : 16 - 23
  • [8] A hybrid particle swarm based method for process planning optimisation
    Wang, Y. F.
    Zhang, Y. F.
    Fuh, J. Y. H.
    INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2012, 50 (01) : 277 - 292
  • [9] Deep learning-driven particle swarm optimisation for additive manufacturing energy optimisation
    Qin, Jian
    Liu, Ying
    Grosvenor, Roger
    Lacan, Franck
    Jiang, Zhigang
    JOURNAL OF CLEANER PRODUCTION, 2020, 245
  • [10] Wireless sensor networks routing algorithm based on particle swarm optimisation
    Yang, Junhan
    INTERNATIONAL JOURNAL OF INTERNET PROTOCOL TECHNOLOGY, 2018, 11 (03) : 159 - 164