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Journal of Mechanical Science and Technology

, Volume 31, Issue 4, pp 1673–1681 | Cite as

A study on improving bone conduction speaker performance by electromagnetic prediction and performance distribution by statistical analysis method

  • Dong Shin Ko
  • Deog Jae Hur
  • Tae Won Park
  • Jai Hyuk Lee
Article
  • 60 Downloads

Abstract

The present paper is focused on the stochastic characteristics of the electromagnetic force, one of the performance parameters for the bone conduction speaker which is one of the devices in the “smart glass”. The design parameters were taken as significant, affecting the electromagnetic force. Characteristic analysis of significant parameters was considered by using the factorial design method. Significant factor of main effect was selected via fractional factorial design method. Main effect and interaction of selected factor were analyzed applying the full factorial design method. The independency of the selected parameter and their significant interaction were examined by using the F-test method. Linear and non-linear characteristics for the selected parameters and performance were examined by creation of the median point within the analysis results for significance analysis. Therefore, prediction model derived non-linear regression model from the central composite design of response surface method. For probability distribution of the electromagnetic characteristics, related prediction model and Monte Carlo simulation method were applied. Electromagnetic performance prediction result showed 98.5 % level and improved maximum 99.8 % reliability level under 3σ level of dimensional management. In view of this, such stochastic design approach could improve design efficiency via verification of individual design parameters’ effect on the performance levels, thereby proving design reliability based on the object levels.

Keywords

Bone conduction speaker Design of experiments Electromagnetic analysis Monte Carlo simulation 

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References

  1. [1]
    T. K. Kim and T. H. Lee, Reliability-based design optimization using enhanced pearson system, Transactions of The Korean Society of Mechanical Engineering-A, 35 (2) (2011) 125–130.CrossRefGoogle Scholar
  2. [2]
    C. S. Kim, H. Y. Jung, M. S. Kang and J. K. Kim, A stochastic analysis in steam turbine blade steel using monte carlo simulation, Transactions of The Korean Society of Mechanical Engineering-A, 26 (11) (2002) 2421–2428.CrossRefGoogle Scholar
  3. [3]
    J. Y. Lee, Tolerance analysis of automobile steering system, Journal of The Korean Society for Precision Engineering, 28 (12) (2011) 1397–1402.Google Scholar
  4. [4]
    J. H. Shin and C. M. Lee, A study on spindle shape design using design experiments, Journal of The Korean Society for Precision Engineering, 26 (4) (2009) 120–127.Google Scholar
  5. [5]
    C. H. Kim, Y. H. Ju and J. P. Park, Vibration analysis of a generator-stator core under electromagnetic excitation, Transactions of The Korean Society for Noise and Vibration Engineering, 9 (4) (1999) 747–753.Google Scholar
  6. [6]
    Abaqus User's Manual, Magnetic pulse forming of a metallic tube, Dassault System, Workshop 4.Google Scholar
  7. [7]
    J. H. Song, Y. H. Lee and H. S. Bae, Numerical analysis of the magnetic fluid velocity and pressure distribution according to the various magnetic field, Journal of The Korean Society of Manufacturing Process Engineering, 7 (2) (2008) 31–37.Google Scholar
  8. [8]
    M. R. Ryu, Y. H. Kim and H. S. Park, Thermal stress prediction of motorcycle disk brake using full factorial design, Proceedings of The Korean Society of Manufacturing Process Engineering Conference, 11 (2008) 318–324.Google Scholar
  9. [9]
    H. S. Han, T. Y. Kim and T. W. Park, Optimal design of a washing using response surface method, Transactions of The Korean Society of Mechanical Engineering-A, 23 (11) (1999) 1871–1877.Google Scholar
  10. [10]
    Y. D. Lee and S. J. Chu, Development of program for predicting GBD to improve canning process capability for catalytic converter, Transactions of The Korean Society of Mechanical Engineering-A, 37 (3) (2013) 419–427.CrossRefGoogle Scholar

Copyright information

© The Korean Society of Mechanical Engineers and Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Dong Shin Ko
    • 1
  • Deog Jae Hur
    • 2
  • Tae Won Park
    • 1
  • Jai Hyuk Lee
    • 2
  1. 1.School of Mechanical EngineeringAjou UniversityKyeonggi-doKorea
  2. 2.Institute for Advanced EngineeringKyeonggi-doKorea

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