Optimisation process for robotic assembly of electronic components

被引:12
作者
Andrzejewski, K. T. [1 ]
Cooper, M. P. [1 ]
Griffiths, C. A. [1 ]
Giannetti, C. [1 ]
机构
[1] Swansea Univ, Coll Engn, Swansea, W Glam, Wales
关键词
Sequencing optimisation; Electronics assembly; KUKA robotics; Flexible manufacture; Genetic algorithm; SURFACE MOUNTING MACHINE; GENETIC-ALGORITHM; PLACE MACHINES; ASSIGNMENT; GENERATION; OPERATIONS; HEURISTICS; PICK;
D O I
10.1007/s00170-018-2645-y
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Adoption of robots in the manufacturing environment is a way to improve productivity, and the assembly of electronic components has benefited from the adoption of highly dedicated automation equipment. Traditionally, articulated 6-axis robots have not been used in electronic surface mount assembly. However, the need for more flexible production systems that can be used for low to medium production builds means that these robots can be used due to their high degrees of flexibility, excellent repeatability and increasingly lower investment costs. This research investigated the application of an articulated robot with six degrees of freedom to assemble a multi-component printed circuit board (PCB) for an electronic product. A heuristic methodology using a genetic algorithm was used to plan the optimal sequence and identify the best location of the parts to the assembly positions on the PCB. Using the optimised paths, a condition monitoring method for cycle time evaluation was conducted using a KUKA KR16 assembly cell together with four different robot path motions. The genetic algorithm approach together with different assembly position iterations identified an optimisation method for improved production throughput using a non-traditional but highly flexible assembly method. The application of optimised articulated robots for PCB assembly can bridge the gap between manual assembly and the high-throughput automation equipment.
引用
收藏
页码:2523 / 2535
页数:13
相关论文
共 33 条
  • [1] Routing heuristics for automated pick and place machines
    Ahmadi, RH
    Mamer, JW
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1999, 117 (03) : 533 - 552
  • [2] SEQUENCING OF INSERTIONS IN PRINTED-CIRCUIT BOARD ASSEMBLY
    BALL, MO
    MAGAZINE, MJ
    [J]. OPERATIONS RESEARCH, 1988, 36 (02) : 192 - 201
  • [3] Broad K, 1996, J OPER RES SOC, V47, P1343, DOI 10.1057/palgrave.jors.0471102
  • [4] Production planning problems in printed circuit board assembly
    Crama, Y
    van de Klundert, J
    Spieksma, FCR
    [J]. DISCRETE APPLIED MATHEMATICS, 2002, 123 (1-3) : 339 - 361
  • [5] The assembly of printed circuit boards: A case with multiple machines and multiple board types
    Crama, Y
    Flippo, OE
    vandeKlundert, J
    Spieksma, FCR
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1997, 98 (03) : 457 - 472
  • [6] Multiple setup PCB assembly planning using genetic algorithms
    Deo, S
    Javadpour, R
    Knapp, GM
    [J]. COMPUTERS & INDUSTRIAL ENGINEERING, 2002, 42 (01) : 1 - 16
  • [7] Optimizing the performance of a surface mount placement machine
    Ellis, KP
    Vittes, FJ
    Kobza, JE
    [J]. IEEE TRANSACTIONS ON ELECTRONICS PACKAGING MANUFACTURING, 2001, 24 (03): : 160 - 170
  • [8] Optimized joint motion planning for redundant industrial robots
    Erdos, Gabor
    Kovacs, Andras
    Vancza, Jozsef
    [J]. CIRP ANNALS-MANUFACTURING TECHNOLOGY, 2016, 65 (01) : 451 - 454
  • [9] An improved A* algorithm for the industrial robot path planning with high success rate and short length
    Fu, Bing
    Chen, Lin
    Zhou, Yuntao
    Zheng, Dong
    Wei, Zhiqi
    Dai, Jun
    Pan, Haihong
    [J]. ROBOTICS AND AUTONOMOUS SYSTEMS, 2018, 106 : 26 - 37
  • [10] García-Nájera A, 2005, IEEE C EVOL COMPUTAT, P1485