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Optimal number of tests to achieve and validate product reliability

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  • Ahmed, Hussam
  • Chateauneuf, Alaa

Abstract

The reliability validation of engineering products and systems is mandatory for choosing the best cost-effective design among a series of alternatives. Decisions at early design stages have a large effect on the overall life cycle performance and cost of products. In this paper, an optimization-based formulation is proposed by coupling the costs of product design and validation testing, in order to ensure the product reliability with the minimum number of tests. This formulation addresses the question about the number of tests to be specified through reliability demonstration necessary to validate the product under appropriate confidence level. The proposed formulation takes into account the product cost, the failure cost and the testing cost. The optimization problem can be considered as a decision making system according to the hierarchy of structural reliability measures. The numerical examples show the interest of coupling design and testing parameters.

Suggested Citation

  • Ahmed, Hussam & Chateauneuf, Alaa, 2014. "Optimal number of tests to achieve and validate product reliability," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 242-250.
  • Handle: RePEc:eee:reensy:v:131:y:2014:i:c:p:242-250
    DOI: 10.1016/j.ress.2014.04.014
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    References listed on IDEAS

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    Cited by:

    1. Sonal, S.D. & Ammanagi, S & Kanjilal, O & Manohar, C.S., 2018. "Experimental estimation of time variant system reliability of vibrating structures based on subset simulation with Markov chain splitting," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 55-68.
    2. Rufo, M.J. & Martín, J. & Pérez, C.J., 2016. "A Bayesian negotiation model for quality and price in a multi-consumer context," Reliability Engineering and System Safety, Elsevier, vol. 147(C), pages 132-141.
    3. Khalil, Y.F., 2019. "New statistical formulations for determination of qualification test plans of safety instrumented systems (SIS) subject to low/high operational demands," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 196-209.
    4. Shashank Gupta & Srinivas Kota & Rajesh P. Mishra, 2016. "Modeling and evaluation of product quality at conceptual design stage," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 7(1), pages 163-177, December.
    5. Nafissa Jibet & Pascal Le Masson & Benoit Weil & Blandine Chazelle & Dominique Laousse, 2023. "Renovating engineering departements' creation heritage to meet contemporary challenges: frugal validation patterns and constructive proof logics for new engineering rules," Post-Print hal-04074841, HAL.
    6. Mobin, Mohammadsadegh & Li, Zhaojun & Cheraghi, S. Hossein & Wu, Gongyu, 2019. "An approach for design Verification and Validation planning and optimization for new product reliability improvement," Reliability Engineering and System Safety, Elsevier, vol. 190(C), pages 1-1.
    7. Gongyu Wu & Zhaojun (Steven) Li & Pan Liu, 2022. "Risk-informed reliability improvement optimization for verification and validation planning based on set covering modeling," Journal of Risk and Reliability, , vol. 236(2), pages 357-370, April.
    8. Sohoin, Rodrigue & El Hami, Abdelkhalak & Guerin, Fabrice & Riahi, Hassen & Attaf, Djelali, 2021. "A novel approach based on meta-modeling technique and time transformation function for reliability analysis of upgraded automotive components," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    9. Kim, Kyungmee O. & Roh, Taeseong & Lee, Jae-Woo & Zuo, Ming J., 2016. "Derating design for optimizing reliability and cost with an application to liquid rocket engines," Reliability Engineering and System Safety, Elsevier, vol. 146(C), pages 13-20.

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