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A physics-of-failure based reliability and maintenance modeling framework for stent deployment and operation

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  • Keedy, Elias
  • Feng, Qianmei

Abstract

Reliability study of stents becomes extremely important due to the high demand on these devices to counteract the effects of atherosclerosis. Based on the physics-of-failure mechanisms, we propose a probabilistic reliability and maintenance modeling framework for stent deployment and operation. The fracture-mechanics-based approach in literature provides a rational basis for quantitative evaluation of damaging effects from two dominating failure modes of stents: (1) delayed failures or fatigue crack growth due to cyclic stresses, and (2) instantaneous failures due to single-event overloads. We develop the system reliability function using probabilistic degradation and random shock models. The developed system reliability model of stents is then incorporated in the optimization of a unique two-phase maintenance policy for achieving persistent patient outcomes. A numerical example is used to illustrate the results, where data in literature are used to analyze the reliability and optimize the maintenance schedule for stents. The developed reliability and maintenance models and analysis tools for stents provide fundamentally new perspectives on the application of reliability concepts to evolving medical devices.

Suggested Citation

  • Keedy, Elias & Feng, Qianmei, 2012. "A physics-of-failure based reliability and maintenance modeling framework for stent deployment and operation," Reliability Engineering and System Safety, Elsevier, vol. 103(C), pages 94-101.
    • Handle: RePEc:eee:reensy:v:103:y:2012:i:c:p:94-101
    DOI: 10.1016/j.ress.2012.03.005
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    References listed on IDEAS

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    6. Li, Ying Yi & Chen, Ying & Yuan, Zeng Hui & Tang, Ning & Kang, Rui, 2017. "Reliability analysis of multi-state systems subject to failure mechanism dependence based on a combination method," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 109-123.
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    10. Sakurahara, Tatsuya & O'Shea, Nicholas & Cheng, Wen-Chi & Zhang, Sai & Reihani, Seyed & Kee, Ernie & Mohaghegh, Zahra, 2019. "Integrating renewal process modeling with Probabilistic Physics-of-Failure: Application to Loss of Coolant Accident (LOCA) frequency estimations in nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 190(C), pages 1-1.
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