IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v138y2015icp145-153.html
   My bibliography  Save this article

Enhancing product robustness in reliability-based design optimization

Author

Listed:
  • Zhuang, Xiaotian
  • Pan, Rong
  • Du, Xiaoping

Abstract

Different types of uncertainties need to be addressed in a product design optimization process. In this paper, the uncertainties in both product design variables and environmental noise variables are considered. The reliability-based design optimization (RBDO) is integrated with robust product design (RPD) to concurrently reduce the production cost and the long-term operation cost, including quality loss, in the process of product design. This problem leads to a multi-objective optimization with probabilistic constraints. In addition, the model uncertainties associated with a surrogate model that is derived from numerical computation methods, such as finite element analysis, is addressed. A hierarchical experimental design approach, augmented by a sequential sampling strategy, is proposed to construct the response surface of product performance function for finding optimal design solutions. The proposed method is demonstrated through an engineering example.

Suggested Citation

  • Zhuang, Xiaotian & Pan, Rong & Du, Xiaoping, 2015. "Enhancing product robustness in reliability-based design optimization," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 145-153.
  • Handle: RePEc:eee:reensy:v:138:y:2015:i:c:p:145-153
    DOI: 10.1016/j.ress.2015.01.026
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832015000368
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2015.01.026?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Shan, Songqing & Wang, G. Gary, 2008. "Reliable design space and complete single-loop reliability-based design optimization," Reliability Engineering and System Safety, Elsevier, vol. 93(8), pages 1218-1230.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Awad, Mahmoud, 2017. "Analyzing sensitivity measures using moment-matching technique," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 90-99.
    2. Liu, Wang-Sheng & Cheung, Sai Hung, 2017. "Reliability based design optimization with approximate failure probability function in partitioned design space," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 602-611.
    3. Yoon, Joung Taek & Youn, Byeng D. & Yoo, Minji & Kim, Yunhan, 2017. "A newly formulated resilience measure that considers false alarms," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 417-427.
    4. Keshtegar, Behrooz & Chakraborty, Souvik, 2018. "Dynamical accelerated performance measure approach for efficient reliability-based design optimization with highly nonlinear probabilistic constraints," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 69-83.
    5. Wang, Guodong & Shao, Mengying & Lv, Shanshan & Kong, Xiangfen & He, Zhen & Vining, Geoff, 2022. "Process parameter optimization for lifetime improvement experiments considering warranty and customer satisfaction," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    6. Jiang, Chen & Qiu, Haobo & Yang, Zan & Chen, Liming & Gao, Liang & Li, Peigen, 2019. "A general failure-pursuing sampling framework for surrogate-based reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 47-59.
    7. Nan, Hang & Liang, Hao & Di, Haoyuan & Li, Hongshuang, 2024. "A gradient-assisted learning strategy of Kriging model for robust design optimization," Reliability Engineering and System Safety, Elsevier, vol. 244(C).

    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. Li, Xiaoke & Zhu, Heng & Chen, Zhenzhong & Ming, Wuyi & Cao, Yang & He, Wenbin & Ma, Jun, 2022. "Limit state Kriging modeling for reliability-based design optimization through classification uncertainty quantification," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    2. Yang, Hezhen & Zhu, Yun & Lu, Qijin & Zhang, Jun, 2015. "Dynamic reliability based design optimization of the tripod sub-structure of offshore wind turbines," Renewable Energy, Elsevier, vol. 78(C), pages 16-25.
    3. Yang, Meide & Zhang, Dequan & Jiang, Chao & Han, Xu & Li, Qing, 2021. "A hybrid adaptive Kriging-based single loop approach for complex reliability-based design optimization problems," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    4. Rocchetta, Roberto & Crespo, Luis G., 2021. "A scenario optimization approach to reliability-based and risk-based design: Soft-constrained modulation of failure probability bounds," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    5. Liu, Zhitao & Tan, CherMing & Leng, Feng, 2015. "A reliability-based design concept for lithium-ion battery pack in electric vehicles," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 169-177.
    6. Van Huynh, Thu & Tangaramvong, Sawekchai & Do, Bach & Gao, Wei & Limkatanyu, Suchart, 2023. "Sequential most probable point update combining Gaussian process and comprehensive learning PSO for structural reliability-based design optimization," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    7. Torii, A.J. & Lopez, R.H. & Miguel, L.F.F., 2019. "A second order SAP algorithm for risk and reliability based design optimization," Reliability Engineering and System Safety, Elsevier, vol. 190(C), pages 1-1.

    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:eee:reensy:v:138:y:2015:i:c:p:145-153. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.