Injection moulding optimisation of multi-class design variables using a PSO algorithm

International Journal of Advanced Manufacturing Technology

Volumn 39, Issue 7-8, 2008, Pages 690-698

  Deng, Y M ^a   Zheng, D ^a   Lu, X J ^a  

^a NINGBO UNIVERSITY   (China)

Author keywords

Elite achieving method; Injection moulding optimisation; Moldflow simulation; Particle swarm optimisation (PSO)

Indexed keywords

ALGORITHMS; CONVERGENCE OF NUMERICAL METHODS; DESIGN; FORMING; INJECTION MOLDING; MOLDING; MOLDS; PARAMETER ESTIMATION;

AIR TRAPS; AND GATES; CAE SOFTWARES; CASE STUDIES; COMPUTER PROGRAMS; CONVERGENCE SPEEDS; COOLING CHANNELS; DESIGN VARIABLES; ELITE ACHIEVING METHOD; GATE LOCATIONS; INJECTION MOULDING OPTIMISATION; INJECTION MOULDINGS; INJECTION TIMES; MELT TEMPERATURES; MOLDFLOW SIMULATION; MOULD DESIGNS; MOULD TEMPERATURES; OBJECTIVE FUNCTIONS; OPTIMISATION; PART GEOMETRIES; PARTICLE SWARM OPTIMISATION; PARTICLE SWARM OPTIMISATION (PSO); PROCESS PARAMETERS; PSO ALGORITHMS; SEARCH PROCESSES; SIMULATION RESULTS; WARPAGE; WELD LINES;

PROCESS ENGINEERING;

EID: 56749184271     PISSN: 02683768     EISSN: 14333015     Source Type: Journal    
DOI: 10.1007/s00170-007-1258-7     Document Type: Article

References (20)

1. I Pandelidis Q Zou 1990 Optimisation of injection moulding design. Part 1: gate location optimisation Polym Eng Sci 30 15 873 882
2. YC Lam S Jin 2001 Optimisation of gate location for plastic injection moulding J Inj Moulding Technol 5 3 180 192
3. Lee BH, Kim BH (1995) Automated selection of gate location based on desired quality of injection moulded part. In: SPE Annual Technical Conference, pp 554-560
4. YC Lam GA Britton DS Liu 2004 Optimisation of gate location with design constraints Int J Adv Manuf Technol 24 7-8 560 566
5. M Zhai YC Lam CK Au 2005 Algorithms for two gate optimization in injection molding Int Polym Process 20 1 14 18
6. RK Irani BH Kim JR Dixon 1995 Towards automated design of the feed system of injection moulds by integrating CAE, iterative redesign and features J Eng Ind 117 72 77
7. I Pandelidis Q Zou 1990 Optimisation of injection moulding design. Part 2: moulding conditions optimisation Polym Eng Sci 30 15 883 892
8. Y-M Deng YC Lam GA Britton 2004 Optimisation of injection moulding conditions with user-definable objective functions based on a genetic algorithm Int J Prod Res 42 7 35 88
9. YC Lam Y-M Deng CK Au 2006 A GA/gradient hybrid approach for injection moulding conditions optimisation Eng Comput 21 3 193 202
10. LW Seow YC Lam 1997 Flow optimization in plastic injection molding J Mater Process Technol 72 333 341
11. YC Lam LW Seow 2000 Cavity balance for plastic injection moulding Polym Eng Sci 40 6 1273 1280
12. YC Lam LY Zhai K Tai SC Fok 2004 An evolutionary approach for cooling system optimization in plastic injection moulding Int J Prod Res 42 10 2047 2061
13. Lee BH, Kim BH (1996) Optimisation of part wall thickness to reduce warpage in injection moulded part based on the modified complex method. In: SPE Annual Technical Conference, pp 692-697
14. Y-M Deng D Zheng 2007 Minimizing thicknesses of injection moulded plastic parts based on Moldflow simulation J Mech Eng (Slovenia) 53 7-8 503 518
15. Y-M Deng GA Britton YC Lam 2006 Towards automatic shape modification in injection-moulded-plastic-part design Int J Adv Manuf Technol 28 495 503
16. Kennedy J, Eberhart RC (1995) Particle swarm optimization. In: Proc. IEEE International Conference on Neural Networks, vol. 4, pp 1942-1948
17. Hu X, Particle swarm optimization. Website: http://www.swarmintelligence. org/index.php (effective as in June 2007)
18. KH Tan MMF Yuen 2000 A Fuzzy multiobjective approach for minimization of injection moulding defects Polym Eng Sci 40 4 956 971
19. L Wang Y Liu Y Xu 2006 Multi-objective PSO algorithm based on fitness sharing and online elite archiving Lect Notes Comput Sci 4113 964 974
20. Goldberg DE, Richardson JJ (1987) Genetic algorithms with sharing for multimodal function optimization. In: Genetic Algorithms and Their Application: Proceedings of the Second International Conference on Genetic Algorithms, pp 41-49