Application of an improved Spider Monkey Optimization algorithm for component assignment problem in PCB assembly

被引:7
|
作者
Wang, Zhengya [1 ]
Mumtaz, Jabir [2 ]
Zhang, Li [3 ]
Yue, Lei [2 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Software Engn, Wuhan 430074, Hubei, Peoples R China
[2] Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, HUST SANY Joint Lab Adv Mfg, Wuhan, Peoples R China
[3] Huazhong Univ Sci & Technol, Sch Mech Sci & Engn, Wuhan 430074, Hubei, Peoples R China
基金
中国国家自然科学基金;
关键词
Printed circuit board assembly; component assignment; Spider Monkey Optimizaton algorithm; Product Services; TRAVELING SALESMAN; FEEDER ASSIGNMENT;
D O I
10.1016/j.procir.2019.04.075
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper presents a new optimization method for printed circuit board assembly (PCBA) process based on improved spider monkey optimization (SMO) algorithm, and a production model for PCBA is created. The proposed method proves to be suitable for product-service system(PSS). PCBA process mainly consists of three parts. First is the assignment of PCB, second is the assignment of machines, the last is the component assignment problem. In this research, the SMO algorithm is applied on optimization of component assignment which is divided into two stages: local leader phase (LLP) and global leader phase (GLP). In the first stage, the electronic components are assigned to the feeders by GLP. In the second stage, the component placement sequence, which is apparently known as a travelling salesman problem (TSP), is determined by LLP. Numerical experiments are performed to compare the performance of SMO algorithm with others under various experimental settings, the results show that the proposed method is more effective than other traditional methods. A production model is created with the proposed method, which is calimed to be able to increase the efficiency of the product services. (C) 2019 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 11th CIRP Conference on Industrial Product-Service Systems
引用
收藏
页码:266 / 271
页数:6
相关论文
共 50 条
  • [1] An improved spider monkey optimization algorithm for multi-objective planning and scheduling problems of PCB assembly line
    Chen, Yarong
    Zhong, Jingyan
    Mumtaz, Jabir
    Zhou, Shengwei
    Zhu, Lixia
    EXPERT SYSTEMS WITH APPLICATIONS, 2023, 229
  • [2] Modeling the component assignment problem in PCB assembly
    Sze, MT
    Ji, P
    Lee, WB
    ASSEMBLY AUTOMATION, 2001, 21 (01) : 55 - 60
  • [3] Mathematical formulation of the component assignment problem in PCB assembly lines
    Ji, P
    Sze, MT
    FLEXIBLE AUTOMATION AND INTELLIGENT MANUFACTURING, 1998, 1998, : 345 - 353
  • [4] A tabu search heuristic for the component assignment problem in PCB assembly
    Wan, YF
    Ji, P
    ASSEMBLY AUTOMATION, 2001, 21 (03) : 236 - 240
  • [5] Spider Monkey Optimization algorithm for numerical optimization
    Jagdish Chand Bansal
    Harish Sharma
    Shimpi Singh Jadon
    Maurice Clerc
    Memetic Computing, 2014, 6 : 31 - 47
  • [6] Spider Monkey Optimization algorithm for numerical optimization
    Bansal, Jagdish Chand
    Sharma, Harish
    Jadon, Shimpi Singh
    Clerc, Maurice
    MEMETIC COMPUTING, 2014, 6 (01) : 31 - 47
  • [7] IMPROVED ANTLION OPTIMIZATION ALGORITHM FOR QUADRATIC ASSIGNMENT PROBLEM
    Kilic, Haydar
    Yuzgec, Ugur
    MALAYSIAN JOURNAL OF COMPUTER SCIENCE, 2021, 34 (01) : 34 - 60
  • [8] Hyperbolic spider monkey optimization algorithm
    Kumar S.
    Nayyar A.
    Nguyen N.G.
    Kumari R.
    Kumari, Rajani (rajanikpoonia@gmail.com), 1600, Bentham Science Publishers (13): : 35 - 42
  • [9] Ageist Spider Monkey Optimization algorithm
    Sharma, Avinash
    Sharma, Akshay
    Panigrahi, B. K.
    Kiran, Deep
    Kumar, Rajesh
    SWARM AND EVOLUTIONARY COMPUTATION, 2016, 28 : 58 - 77
  • [10] Spider monkey optimization algorithm for constrained optimization problems
    Gupta, Kavita
    Deep, Kusum
    Bansal, Jagdish Chand
    SOFT COMPUTING, 2017, 21 (23) : 6933 - 6962