Research on health state assessment and prediction for complex equipment based on the improved FMECA and GM (1,1)
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DOI: 10.1007/s13198-023-01884-6
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References listed on IDEAS
- Alaswad, Suzan & Xiang, Yisha, 2017. "A review on condition-based maintenance optimization models for stochastically deteriorating system," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 54-63.
- Eryilmaz, Serkan, 2016. "A reliability model for a three-state degraded system having random degradation rates," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 59-63.
- Hossein Safari & Zahra Faraji & Setareh Majidian, 2016. "Identifying and evaluating enterprise architecture risks using FMEA and fuzzy VIKOR," Journal of Intelligent Manufacturing, Springer, vol. 27(2), pages 475-486, April.
- Rabiei, Masoud & Modarres, Mohammad, 2013. "A recursive Bayesian framework for structural health management using online monitoring and periodic inspections," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 154-164.
- Tamilselvan, Prasanna & Wang, Pingfeng, 2013. "Failure diagnosis using deep belief learning based health state classification," Reliability Engineering and System Safety, Elsevier, vol. 115(C), pages 124-135.
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Keywords
Health state assessment; Health state prediction; Failure; FMECA; GM (1; 1); Complex equipment; FRD; Circulating water pump;All these keywords.
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