Residual life predictions in the absence of prior degradation knowledge

IEEE Transactions on Reliability

Volumn 58, Issue 1, 2009, Pages 106-117

  Gebraeel, Nagi ^a   Elwany, Alaa ^a   Pan, Jing ^b  

^a Georgia Institute of Technology   (United States)

^b UNIVERSITY OF IOWA   (United States)

Author keywords

Bernstein distribution; Degradation modeling; Prognostics; Random coefficients models

Indexed keywords

AMBER; FORECASTING; JET ENGINES; MACHINERY; RANDOM PROCESSES; STOCHASTIC MODELS;

BERNSTEIN DISTRIBUTION; DEGRADATION MODELING; DEGRADATION MODELS; FAILURE TIME; FAILURE TIME DATUM; HISTORICAL DATABASE; PRIOR DISTRIBUTIONS; PROGNOSTICS; RANDOM COEFFICIENTS MODELS; RESIDUAL LIFE DISTRIBUTIONS; RESIDUAL LIFE PREDICTIONS; SENSORY SIGNALS; STOCHASTIC PARAMETERS;

DEGRADATION;

EID: 63149182784     PISSN: 00189529     EISSN: None     Source Type: Journal    
DOI: 10.1109/TR.2008.2011659     Document Type: Article

References (23)

1. W. Nelson, Accelerated Testing Statistical Models, Test Plans, and Data Analysis. New York: Wiley, 1990.
2. K. A. Doksum and A. Hoyland, "Models for variable-stress accelerated life testing experiments based on Wiener processes and the inverse Gaussian distribution," Technometrics, vol. 34, pp. 74-82, 1992.
3. G. Whitmore, "Estimating degradation by a Wiener diffusion process subject to measurement error," Lifetime Data Analysis, vol. 1, pp. 307-319, 1995.
4. C. Lu and W. Meeker, "Using degradation measures to estimate a time-to-failure distribution," Technometrics, vol. 35, no. 2, pp. 161-174, 1993.
5. N. Gebraeel, M. Lawley, R. Li, and J. K. Ryan, "Life distributions from component degradation signals: A Bayesian Approach," IIE Trans., vol. 37, no. 6, pp. 543-557, 2005.
6. W. Wang, "A model to determine the optimal critical level and the monitoring intervals in condition-based maintenance," International Journal of Production Research, vol. 38, pp. 1425-1436, 2000.
7. D. W. Coit and T. Jin, "Gamma distribution parameter estimation for field reliability data with missing failure times," IIE Trans., vol. 32, no. 12, pp. 1161-1166, 2000.
8. E. A. Elsayed, "Perspectives and challenges for research in quality and reliability engineering," International Journal of Production Research, vol. 38, no. 9, pp. 1953-1976, 2000.
9. E. A. Elsayed, H. Liao, and X. Wang, "An extended linear hazard regression model with application to time-dependent dielectric breakdown of thermal oxides," IIE Trans., vol. 38, pp. 329-340, 2006.
10. W. Huang and R. G. Askin, "A generalized SSI reliability model considering stochastic loading and strength aging degradation," IEEE Trans. Reliability, vol. 53, no. 1, pp. 77-82, 2004.
11. S. Tseng, M. Hamada, and C. Chiao, "Using degradation data to improve fluorescent lamp reliability," Journal of Quality Technology, vol. 27, pp. 363-369, 1995.
12. K. Yang and A. Jeang, "Statistical surface roughness checking procedure based on a cutting tool wear model," Journal of Manufacturing Systems, vol. 13, pp. 1-8, 1994.
13. K. Yang and G. Yang, "Degradation reliability assessment using severe critical values," International Journal of Reliability, Quality and Safety Engineering, vol. 5, pp. 85-95, 1998.
14. K. Goode, B. Roylance, and J. Moore, "Development of a predictive model for monitoring condition of a hot strip mill," Ironmaking and Steelmaking, vol. 25, pp. 42-46, 1998.
15. D. C. Swanson, "A general prognostic tracking algorithm for predictive maintenance," in IEEE Aerospace Conference Proceedings, 2001, vol. 6, pp. 62971-62977.
16. N. Z. Gebraeel, "Sensory updated residual life distribution for components with exponential degradation patterns," IEEE Trans. Automation Science and Engineering, vol. 3, no. 4, pp. 382-393, 2006.
17. A. H. Elwany and N. Z. Gebraeel, "Sensory-based Prognostic Models for equipment replacement and spare parts inventory," IIE Trans., vol. 40, pp. 629-639, 2008.
18. A. H. Christer and W. Wang, "A model of condition monitoring of a production plant," International Journal of Production Research, vol. 30
19. Y. Shao and K. Nezu, "Prognosis of remaining bearing life using neural networks," Proceedings of the Institute of Mechanical Engineer, Part I, Journal of Systems and Control Engineering, vol. 214, no. 3, pp. 217-230, 2000.
20. M. Ahmad and A. Sheikh, "Bernstein reliability model: Derivation and estimation of parameters," Reliability Engineering, vol. 8, pp. 131-148, 1984.
21. M. P. Blake and W. S. Mitchel, Vibration & Acoustic Measurement Handbook. New York: Spartan Books, 1972.
22. T. A. Harris, Rolling Bearing Analysis. New York: Wiley, 2001.
23. C. F. Wu and M. Hamada, Experiments: Planning, Analysis, and Parameter Design Optimization. : John Wiley & Sons, Inc., 2002.