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Hidden Markov Models approach used for life parameters estimations

Author

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  • Fort, A.
  • Mugnaini, M.
  • Vignoli, V.

Abstract

In modern electronics and in electrical applications design is very important to be able to predict the actual product life or, at least, to be able to provide the end user with a reasonable estimate of such parameter. It is important to be able to define the availability as a key parameter because, although other performance indicators (as the mean time before failures MTBF or mean time to failure MTTF) exist, they are often misused.

Suggested Citation

  • Fort, A. & Mugnaini, M. & Vignoli, V., 2015. "Hidden Markov Models approach used for life parameters estimations," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 85-91.
    • Handle: RePEc:eee:reensy:v:136:y:2015:i:c:p:85-91
    DOI: 10.1016/j.ress.2014.11.017
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    References listed on IDEAS

    as
    1. Li, Y.F. & Peng, R., 2014. "Availability modeling and optimization of dynamic multi-state series–parallel systems with random reconfiguration," Reliability Engineering and System Safety, Elsevier, vol. 127(C), pages 47-57.
    2. P Vrignat & M Avila & F Duculty & S Aupetit & M Slimane & F Kratz, 2012. "Maintenance policy: degradation laws versus hidden Markov model availability indicator," Journal of Risk and Reliability, , vol. 226(2), pages 137-155, April.
    3. Zamalieva, Daniya & Yilmaz, Alper & Aldemir, Tunc, 2013. "Online scenario labeling using a hidden Markov model for assessment of nuclear plant state," Reliability Engineering and System Safety, Elsevier, vol. 110(C), pages 1-13.
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    Cited by:

    1. Mugnaini, Marco & Addabbo, Tommaso & Fort, Ada & Elmi, Alessandro & Landi, Elia & Vignoli, Valerio, 2020. "Magnetic brakes material characterization under accelerated testing conditions," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    2. Gámiz, María Luz & Limnios, Nikolaos & Segovia-García, María del Carmen, 2023. "Hidden markov models in reliability and maintenance," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1242-1255.
    3. Chen, Gaige & Chen, Jinglong & Zi, Yanyang & Miao, Huihui, 2017. "Hyper-parameter optimization based nonlinear multistate deterioration modeling for deterioration level assessment and remaining useful life prognostics," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 517-526.
    4. Fort, Ada & Mugnaini, Marco & Vignoli, Valerio & Gaggii, Vittorio & Pieralli, Moreno, 2015. "Fault tolerant design of a field data modular readout architecture for railway applications," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 456-462.
    5. Chen, Zhen & Li, Yaping & Xia, Tangbin & Pan, Ershun, 2019. "Hidden Markov model with auto-correlated observations for remaining useful life prediction and optimal maintenance policy," Reliability Engineering and System Safety, Elsevier, vol. 184(C), pages 123-136.
    6. Addabbo, Tommaso & Fort, Ada & Mugnaini, Marco & Vignoli, Valerio & Simoni, Enrico & Mancini, Mario, 2016. "Availability and reliability modeling of multicore controlled UPS for datacenter applications," Reliability Engineering and System Safety, Elsevier, vol. 149(C), pages 56-62.

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