Building a data-driven vital sign indicator for an economically optimized component replacement policy

PHM 2014 - Proceedings of the Annual Conference of the Prognostics and Health Management Society 2014

Volumn , Issue , 2014, Pages 664-675

  Ahn, Hyung Il ^a   Leung, Ying Tat ^b   Hochstein, Axel ^a  

^a GE GLOBAL RESEARCH   (United States)

^b IBM ALMADEN RESEARCH CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COSTS; EQUIPMENT; MACHINERY;

COMPONENT REPLACEMENT; COMPUTATIONAL FRAMEWORK; INDUSTRIAL EQUIPMENT; MAINTENANCE SCHEDULES; NORMAL OPERATING CONDITIONS; PERIODIC MAINTENANCE; TRADITIONAL APPROACHES; WORKING ENVIRONMENT;

MAINTENANCE;

EID: 84920545135     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. Bair, E., Hastie, T., Paul, D., & Tibshirani, R. (2006). Prediction by supervised principal components. Journal of the American Statistical Association, 101(473).
2. Banjevic, D., Jardine, A., Makis, V., & Ennis, M. (2001). A control-limit policy and software for condition-based maintenance optimization. INFOR-OTTAWA-, 39(1), 32-50.
3. Cristianini, N., & Shawe-Taylor, J. (2000). An introduction to support vector machines and other kernel-based learning methods. Cambridge university press.
4. Fox, J. (2002). Cox proportional-hazards regression for survival data. See Also.
5. Hastie, T., Tibshirani, R., Friedman, J., & Franklin, J. (2005). The elements of statistical learning: data mining, inference and prediction. The Mathematical Intelligencer, 27(2), 83-85.
6. Jardine, A., Banjevic, D., Montgomery, N., & Pak, A. (2008). Repairable system reliability: Recent developments in CBM optimization. International Journal of Performability Engineering, 4(3), 205.
7. Jardine, A. K., & Tsang, A. H. (2013). Maintenance, replacement, and reliability: theory and applications. CRC press.
8. Scholkopf, B., & Smola, A. (2002). Learning with kernels. MIT press Cambridge.
9. Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis: Modeling change and event occurrence. Oxford university press.
10. Therneau, T. M. (2000). Modeling survival data: extending the Cox model. Springer.
11. Wu, X., & Ryan, S. M. (2011). Optimal replacement in the proportional hazards model with semi-markovian covariate process and continuous monitoring. Reliability, IEEE Transactions on, 60(3), 580-589.
12. Zaki, M. J. (2001). SPADE: An efficient algorithm for mining frequent sequences. Machine Learning, 42(1-2), 31-60.