Optimization of flexible fixture layout using N-M principle

ORIGINAL ARTICLE
  • 15 Downloads

Abstract

Fixture layout has a direct impact on the machining quality of thin-walled parts. However, there are few studies on the flexible fixture of automotive interior decoration, especially for car dashboards. With the development of individualized demand, the production trend of car dashboards is changing from large-quantity to multi-variety and small-batch, which makes the demand for flexible fixture of car dashboards. Therefore, a kind of flexible fixture for car dashboards based on a new N-M principle was proposed in this paper. With the scientific problem illustrated, this paper put forward a method by coupling genetic algorithm and finite element analysis to deal with the flexible fixture layout optimization. The optimization model of fixture layout based on the N-M principle was set up by taking the maximum deformation of car dashboards as the optimization objective and setting constraints. Finite element model was established to calculate the deformation by setting the boundary conditions, the equivalent cutting force. Genetic algorithm was used to search the optimal solution of the fixture layout. A case was studied to verify the method, and the result showed that the maximum deformation was reduced by 56.5% and the stiffness was increased by 0.77 times, which fully demonstrated the effectiveness of the method.

Keywords

Car dashboard Flexible fixture Layout optimization Genetic algorithm Finite element analysis 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.

References

  1. 1.
    Liao YG (2016) Non-linear and explicit finite element analysis in dynamic responses of handling sheet-metal parts. Proc Inst Mech Eng B J Eng Manuf 221(6):1021–1030.  https://doi.org/10.1243/09544054jem768 CrossRefGoogle Scholar
  2. 2.
    Qian X, Yang L, Lou P (2015) The autonomous detection of sheet metal parts using image processing. Int J Adv Manuf Technol 85(1–4):469–479.  https://doi.org/10.1007/s00170-015-7946-9 Google Scholar
  3. 3.
    Jie L, Jianhua M, Shuhuai H (2004) Sheet metal dieless forming and its tool path generation based on STL files. Int J Adv Manuf Technol 23:696–699.  https://doi.org/10.1007/s00170-003-1783-y CrossRefGoogle Scholar
  4. 4.
    Wu H, Lu B, Guo C, Wang Y (2014) Impact analysis of geometric characteristics and boundary conditions on the stiffness of sheet metal parts. Mater Sci 20.  https://doi.org/10.5755/j01.ms.20.4.5955
  5. 5.
    Dietrich L, Socha G, Kowalewski ZL (2014) Anti-buckling fixture for large deformation tension-compression cyclic loading of thin metal sheets. Strain 50:174–183.  https://doi.org/10.1111/str.12078 CrossRefGoogle Scholar
  6. 6.
    Zhang Q, Liu Y, Zhang Z (2015) A new optimization method for sheet metal forming processes based on an iterative learning control model. Int J Adv Manuf Technol 85(5–8):1063–1075.  https://doi.org/10.1007/s00170-015-7975-4 Google Scholar
  7. 7.
    Cai W, Hu SJ, Yuan JX (1996) Deformable sheet metal fixturing: principles, algorithms, and simulations. J Manuf Sci Eng 118:318.  https://doi.org/10.1115/1.2831031 CrossRefGoogle Scholar
  8. 8.
    Xiong L, Molfino R, Zoppi M (2013) Fixture layout optimization for flexible aerospace parts based on self-reconfigurable swarm intelligent fixture system. Int J Adv Manuf Technol 66:1305–1313.  https://doi.org/10.1007/s00170-012-4408-5 CrossRefGoogle Scholar
  9. 9.
    Wang Y, Chen X, Gindy N, Xie J (2006) Elastic deformation of a fixture and turbine blades system based on finite element analysis. Int J Adv Manuf Technol 36(3–4):296–304.  https://doi.org/10.1007/s00170-006-0841-7 Google Scholar
  10. 10.
    Siebenaler SP Melkote SN (2006) Prediction of workpiece deformation in a fixture system using the finite element method. Int J Mach Tools Manuf 46:51–58.  https://doi.org/10.1016/j.ijmachtools.2005.04.007 CrossRefGoogle Scholar
  11. 11.
    Ratchev S, Phuah K, Liu S (2007) FEA-based methodology for the prediction of part–fixture behaviour and its applications. J Mater Process Technol 191:260–264.  https://doi.org/10.1016/j.jmatprotec.2007.03.020 CrossRefGoogle Scholar
  12. 12.
    Ni J, Tang WC, Xing Y (2016) Performance of reducing the dimensional error of an assembly by the rivet upsetting direction optimization. Proc Inst Mech Eng B J Eng Manuf 231:2133–2144.  https://doi.org/10.1177/0954405415625918 CrossRefGoogle Scholar
  13. 13.
    Ni J, Tang WC, Xing Y, Xing Y, Ben KC, Li M (2016) A local-to-global dimensional error calculation framework for the riveted assembly using finite-element analysis. J Manuf Sci Eng 138:031004.  https://doi.org/10.1115/1.4031101 CrossRefGoogle Scholar
  14. 14.
    Huang X, Sun J, Li J (2014) Finite element simulation and experimental investigation on the residual stress-related monolithic component deformation. Int J Adv Manuf Technol 77(5–8):1035–1041.  https://doi.org/10.1007/s00170-014-6533-9 CrossRefGoogle Scholar
  15. 15.
    Kim DM, Bajpai V, Kim BH, Park HW (2015) Finite element modeling of hard turning process via a micro-textured tool. Int J Adv Manuf Technol 78(9–12):1393–1405.  https://doi.org/10.1007/s00170-014-6747-x CrossRefGoogle Scholar
  16. 16.
    Lu C, Zhao HW (2014) Fixture layout optimization for deformable sheet metal workpiece. Int J Adv Manuf Technol 78:85–98.  https://doi.org/10.1007/s00170-014-6647-0 CrossRefGoogle Scholar
  17. 17.
    Kulankare KK, Melkote SN (2000) Machining fixture layout optimization using the genetic algorithm. Int J Mach Tools Manuf 40:579–598.  https://doi.org/10.1016/S0890-6955(99)00072-3 CrossRefGoogle Scholar
  18. 18.
    Vallapuzha S, Meter ECD, Choudhuri S, Khetan RP (2002) An investigation of the effectiveness of fixture layout optimization methods. Int J Mach Tools Manuf 42:251–263.  https://doi.org/10.1016/S0890-6955(01)00114-6 CrossRefGoogle Scholar
  19. 19.
    Prabhaharan G, Padmanaban KP, Krishnakumar R (2006) Machining fixture layout optimization using FEM and evolutionary techniques. Int J Adv Manuf Technol 32:1090–1103.  https://doi.org/10.1007/s00170-006-0441-6 CrossRefGoogle Scholar
  20. 20.
    Padmanaban KP, Arulshri KP, Prabhakaran G (2009) Machining fixture layout design using ant colony algorithm based continuous optimization method. Int J Adv Manuf Technol 45:922–934.  https://doi.org/10.1007/s00170-009-2035-6 CrossRefGoogle Scholar
  21. 21.
    Kaya N (2006) Machining fixture locating and clamping position optimization using genetic algorithms. Comput Ind 57:112–120.  https://doi.org/10.1016/j.compind.2005.05.001 CrossRefGoogle Scholar
  22. 22.
    Kulankara K, Satyanarayana S, Melkote SN (2002) Iterative fixture layout and clamping force optimization using the genetic algorithm. J Manuf Sci E: T ASME 124:119–125.  https://doi.org/10.1115/1.1414127 CrossRefGoogle Scholar
  23. 23.
    Chen W, Ni L, Xue J (2007) Deformation control through fixture layout design and clamping force optimization. Int J Adv Manuf Technol 38:860–867.  https://doi.org/10.1007/s00170-007-1153-2. CrossRefGoogle Scholar
  24. 24.
    Liu Z-H, Wang MY, Wang KD, Mei XC (2013) Fixture performance improvement by an accelerated integral method of fixture layout and clamping force plan. Proc Inst Mech Eng B J Eng Manuf 227:1819–1829.  https://doi.org/10.1177/0954405413494194 CrossRefGoogle Scholar
  25. 25.
    Abedini V, Shakeri M, Siahmargouei MH, Baseri H (2014) Analysis of the influence of machining fixture layout on the workpiece’s dimensional accuracy using genetic algorithm. Proc Inst Mech Eng B J Eng Manuf 228:1409–1418.  https://doi.org/10.1177/0954405413519605 CrossRefGoogle Scholar
  26. 26.
    Rex FMT, Ravindran D (2015) An integrated approach for optimal fixture layout design. Proc Inst Mech Eng B J Eng Manuf 231:1217–1228.  https://doi.org/10.1177/0954405415590991 CrossRefGoogle Scholar
  27. 27.
    Xin J, Dou J, Zhu L, Wang X, Wang L, Wang Z (2010) Machining fixture layout optimization using particle swarm optimization algorithm. 7997: 79970S.  https://doi.org/10.1117/12.885289.
  28. 28.
    Xing Y, Wang Y (2012) Fixture layout design based on two-stage method for sheet metal components. Proc Inst Mech Eng B J Eng Manuf 227:162–172.  https://doi.org/10.1177/0954405412463132 CrossRefGoogle Scholar
  29. 29.
    Liu P, Li Y, Zhang K-F, Cheng H (2012) Based on region division setup planning for sheet metal assembly in aviation industry. Proc Inst Mech Eng B J Eng Manuf 227:153–161.  https://doi.org/10.1177/0954405412462656. CrossRefGoogle Scholar
  30. 30.
    Yang B, Wang Z, Yang Y, Kang Y, Li C (2017) Optimization of fixture locating layout for sheet metal part by cuckoo search algorithm combined with finite element analysis. Adv Mech Eng 9:168781401770483.  https://doi.org/10.1177/1687814017704836 CrossRefGoogle Scholar
  31. 31.
    Cheng H, Li Y, Zhang KF, Luan C, Xu YW, Li MH (2012) Optimization method of fixture layout for aeronautical thin-walled structures with automated riveting. Assem Autom 32:323–332.  https://doi.org/10.1108/01445151211262384 CrossRefGoogle Scholar
  32. 32.
    Wang Z, Yang Y, Yang B, Kang Y (2016) Optimal sheet metal fixture locating layout by combining radial basis function neural network and bat algorithm. Adv Mech Eng 8:168781401668190.  https://doi.org/10.1177/1687814016681905 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Mechanical EngineeringNanjing University of Science and TechnologyNanjingChina

Personalised recommendations