DOI QR코드

DOI QR Code

Design Optimization of Cleaning Blade for Minimizing Stress

응력 최소화를 위한 클리닝 블레이드 최적설계

  • 박창현 (한양대학교 기계공학과) ;
  • 이준희 (삼성전자(주)) ;
  • 최동훈 (한양대학교 최적설계신기술연구센터)
  • Received : 2010.12.15
  • Accepted : 2011.02.21
  • Published : 2011.05.01

Abstract

A cleaning blade is an attachment installed in the toner cartridge of a laser printer for removing the residual toner from an organic photo-conductive drum. There have been many studies on the performance and life of the rubber blade. We focus on optimally designing the blade shape parameters to minimize the maximum stress of the blade while satisfying design constraints on the cleaning performance and part interference. The blade is optimally designed using a design of experiments, meta-models and an optimization algorithm implemented in PIAnO (process integration, automation, and optimization), a commercial PIDO (process integration and design optimization) tool. We integrate the CAE tools necessary for the structural analysis of the cleaning blade, automate the analysis procedure, and optimize the solution using PIAnO. We decreased the maximum stress by 32.6% in comparison with that of the initial design.

Keywords

Laser Printer;Cleaning Blade;Cleaning Performance;Design of Experiments;Metamodel;Design Optimization

References

  1. Takahasi, T., 1977, Cleaning Device for Use in Electrophotographic Copying Apparatus, U.S Patent 4026648.
  2. Schein, L. B., 2003, Electrophtography and Development Physics, Laplacian Press.
  3. Royka, L. B. and Emerald, R. L, 1971, Lubricated Blade Cleaning of Imaging Photoconductive Member, U.S Patent 3552850.
  4. Gerbasi, D. P., 1972, Cleaning Apparatus, U.S Patent 3660863.
  5. Till, H. R., 1973, Wiper Blade Cleaning for Xerographic Machines, U.S Patent 3724220.
  6. Till, H. R. and Lindblad, N. R., 1976, "Parametric Study of a Xerographic Cleaning Blade," Conf. Rec., Annu. Meet. IEEE Ind.., Vol. 20, No. 5, pp. 449-464.
  7. Harpavat, G. L., 1979, "A Theoretical Study of the Mechanics of a Xerographic Cleaning Blade," IEEE Transactions on Industry Applications, Vol. IA-15, No. 6, pp. 681-687. https://doi.org/10.1109/TIA.1979.4503730
  8. Meyer, R. J., 2000, "Theory of Blade Cleaning," Int. Conf. on Digital Printing Technologies, pp. 846-850.
  9. Seino, K. and Yuge, S., 1985, "Wear Characteristics and Cleaning Ability of Cleaning Blades," JIST, Vol. 47, No. 5, pp. 424-433.
  10. Park, J. S., 1994, "Optimal Latin-Hypercube Designs for Computer Experiments," J. Statist. Plann. Inference, Vol. 39, pp. 95-111. https://doi.org/10.1016/0378-3758(94)90115-5
  11. Krige, D. G., 1951, "A Statistical Approach to Some Basic Mine Valuation Problems on the Witwatersrand," J. of the Chem., Metal. and Mining Soc. of South Africa, Vol. 52, No. 6, pp. 119-139.
  12. Holland, J. H., 1975, Adaptation in Natural and Artificial Systems, The University of Michigan Press.
  13. Simpson, T. W., Korte, J. J., Mauery, T. M. and Mistree, F., 1998, "Comparisons of Response Surface and Kriging Models for Multidisciplinary Design Optimization," Proc. 7th AIAA/USAF/NASA/ ISSMO Symposium on Multidisciplinary Analysis & Optimization, Vol. 1, pp. 381-391.
  14. Haupt, R. L. and Haupt, S. E., 1998, Practical Evolutionary Algorithms, Wiley.