IDEAS home Printed from https://ideas.repec.org/a/ibn/masjnl/v11y2017i10p123.html
   My bibliography  Save this article

Sensitivity-Based Reliability Analysis of MEMS Acceleration Switch

Author

Listed:
  • Prashank Kansal
  • Pramod Kasturi
  • Nam H. Kim
  • Seung-gyo Jang

Abstract

MEMS acceleration switches have been used in many engineering applications. In this paper, the reliability of MEMS switch is evaluated under various uncertainties from materials and manufacturing process. First, the performance of MEMS switch is modeled using 1D mass-spring-damper-contact system. Different from conventional lumped element methods, the model includes the effect of geometric parameters as well as contact conditions. The parameters of 1D models are calibrated using a high-fidelity finite element model. For reliability assessment, four different methods are used in order to compare computational cost as well as accuracy in predicting reliability. It turned out that sensitivity-based reliability method has several benefits, such as computational time and identifying important parameters that contribute significantly to reliability. The sensitivity analysis showed that the cross-sectional height and the length of folded-beam contribute most significantly to the reliability of switch-on condition. After changing the length of the beam, the probability of failure was improved from 0.168 to 0.0003.

Suggested Citation

  • Prashank Kansal & Pramod Kasturi & Nam H. Kim & Seung-gyo Jang, 2017. "Sensitivity-Based Reliability Analysis of MEMS Acceleration Switch," Modern Applied Science, Canadian Center of Science and Education, vol. 11(10), pages 123-123, October.
    • Handle: RePEc:ibn:masjnl:v:11:y:2017:i:10:p:123
    as

    Download full text from publisher

    File URL: https://ccsenet.org/journal/index.php/mas/article/download/70898/38693
    Download Restriction: no
    File URL: https://ccsenet.org/journal/index.php/mas/article/view/70898
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kleijnen, Jack P. C., 2005. "An overview of the design and analysis of simulation experiments for sensitivity analysis," European Journal of Operational Research, Elsevier, vol. 164(2), pages 287-300, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wen-Shiung Lee, 2013. "Merger and acquisition evaluation and decision making model," The Service Industries Journal, Taylor & Francis Journals, vol. 33(15-16), pages 1473-1494, December.
    2. Lu, Xuefei & Borgonovo, Emanuele, 2023. "Global sensitivity analysis in epidemiological modeling," European Journal of Operational Research, Elsevier, vol. 304(1), pages 9-24.
    3. Shi, Wen & Liu, Zhixue & Shang, Jennifer & Cui, Yujia, 2013. "Multi-criteria robust design of a JIT-based cross-docking distribution center for an auto parts supply chain," European Journal of Operational Research, Elsevier, vol. 229(3), pages 695-706.
    4. Y. Yang & L. Wang, 2010. "A Review of Modelling Tools for Implementation of the EU Water Framework Directive in Handling Diffuse Water Pollution," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(9), pages 1819-1843, July.
    5. Jack P. C. Kleijnen & Susan M. Sanchez & Thomas W. Lucas & Thomas M. Cioppa, 2005. "State-of-the-Art Review: A User’s Guide to the Brave New World of Designing Simulation Experiments," INFORMS Journal on Computing, INFORMS, vol. 17(3), pages 263-289, August.
    6. Wen Shiung Lee & Ya Ting Yang, 2013. "Valuation and choice of convertible bonds based on MCDM," Applied Financial Economics, Taylor & Francis Journals, vol. 23(10), pages 861-868, May.
    7. Zengqing Wu & Run Peng & Xu Han & Shuyuan Zheng & Yixin Zhang & Chuan Xiao, 2023. "Smart Agent-Based Modeling: On the Use of Large Language Models in Computer Simulations," Papers 2311.06330, arXiv.org, revised Dec 2023.
    8. Kleijnen, Jack P.C., 2017. "Regression and Kriging metamodels with their experimental designs in simulation: A review," European Journal of Operational Research, Elsevier, vol. 256(1), pages 1-16.
    9. Happe, Kathrin & Kellermann, Konrad, 2007. "DIESE MODELLE SIND ZU KOMPLEX!-ODER DOCH NICHT?: EXPERIMENTELLES DESIGN UND METAMODELLIERUNG ALS MOGLICHER WEG, DAS KOMMUNIKATIONSPROBLEM AGENTENBASIERTER MODELLE IN DER POLITIKANALYSE ZU LOSEN (Germa," 47th Annual Conference, Weihenstephan, Germany, September 26-28, 2007 7613, German Association of Agricultural Economists (GEWISOLA).
    10. Tian, Wei, 2013. "A review of sensitivity analysis methods in building energy analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 411-419.
    11. Strang, Kenneth David, 2012. "Importance of verifying queue model assumptions before planning with simulation software," European Journal of Operational Research, Elsevier, vol. 218(2), pages 493-504.
    12. Scott L. Rosen & Christopher P. Saunders & Samar K Guharay, 2015. "A Structured Approach for Rapidly Mapping Multilevel System Measures via Simulation Metamodeling," Systems Engineering, John Wiley & Sons, vol. 18(1), pages 87-101, January.
    13. Parviz Mohamadzadeh & Samereh Pourmoradian & Bakhtiar Feizizadeh & Ayyoob Sharifi & Mathias Vogdrup-Schmidt, 2020. "A GIS-Based Approach for Spatially-Explicit Sustainable Development Assessments in East Azerbaijan Province, Iran," Sustainability, MDPI, vol. 12(24), pages 1-16, December.
    14. Marrel, Amandine & Iooss, Bertrand & Van Dorpe, François & Volkova, Elena, 2008. "An efficient methodology for modeling complex computer codes with Gaussian processes," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4731-4744, June.
    15. Happe, Kathrin & Kellermann, Konrad & Balmann, Alfons, 2006. "Agent-based analysis of agricultural policies: An illustration of the agricultural policy simulator AgriPoliS, its adaptation and behavior," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 11(1).
    16. Pengfei Wei & Zhenzhou Lu & Jingwen Song, 2014. "Moment‐Independent Sensitivity Analysis Using Copula," Risk Analysis, John Wiley & Sons, vol. 34(2), pages 210-222, February.
    17. Borgonovo, E., 2007. "A new uncertainty importance measure," Reliability Engineering and System Safety, Elsevier, vol. 92(6), pages 771-784.
    18. Hamad, Husam & Al-Hamdan, Sami, 2007. "Discovering metamodels' quality-of-fit for simulation via graphical techniques," European Journal of Operational Research, Elsevier, vol. 178(2), pages 543-559, April.
    19. Daniel J Klein & Michael Baym & Philip Eckhoff, 2014. "The Separatrix Algorithm for Synthesis and Analysis of Stochastic Simulations with Applications in Disease Modeling," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-10, July.
    20. Edward Radosiński & Łukasz Radosiński, 2018. "Verification of a model as a scientific tool of operations research – a methodological approach," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 28(3), pages 45-62.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ibn:masjnl:v:11:y:2017:i:10:p:123. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.