Access the full text.
Sign up today, get DeepDyve free for 14 days.
D. Banjevic, A. Jardine (2006)
Calculation of reliability function and remaining useful life for a Markov failure time processIma Journal of Management Mathematics, 17
D. Banjevic, A. Jardine, V. Makis, M. Ennis (2001)
A Control-Limit Policy And Software For Condition-Based Maintenance OptimizationINFOR: Information Systems and Operational Research, 39
D. Cox (1972)
Regression models and life tables (with discussion
D. Oakes, T. Dasu (1990)
A note on residual lifeBiometrika, 77
P. Vlok (2006)
Dynamic residual life estimation of industrial equipment based on failure intensity proportions
V. Makis, A. Jardine (1991)
Computation of optimal policies in replacement modelsIma Journal of Management Mathematics, 3
A. Jardine, Daming Lin, D. Banjevic (2006)
A review on machinery diagnostics and prognostics implementing condition-based maintenanceMechanical Systems and Signal Processing, 20
P. Vlok, M. Wnek, M. Zygmunt (2004)
Utilising statistical residual life estimates of bearings to quantify the influence of preventive maintenance actionsMechanical Systems and Signal Processing, 18
F. Coolen, Per Andersen, Ørnulf Borgan, Richard Gill, Niels Keiding (1996)
Statistical Models Based on Counting Processes.The Statistician, 45
M. Crowder (1991)
Statistical Analysis of Reliability Data
F. Guess, F. Proschan (1988)
Mean Residual Life: Theory and ApplicationsHandbook of Statistics, 7
R. Reinertsen (1996)
Residual life of technical systems ; diagnosis, prediction and life extensionReliability Engineering & System Safety, 54
R. Barlow, A. Marshall, F. Proschan (1963)
Properties of Probability Distributions with Monotone Hazard RateAnnals of Mathematical Statistics, 34
E. Deevey (1947)
Life Tables for Natural Populations of AnimalsThe Quarterly Review of Biology, 22
J. Noortwijk (2009)
A survey of the application of gamma processes in maintenanceReliab. Eng. Syst. Saf., 94
W. Nelson (1998)
Statistical Methods for Reliability Data
Hassan Zahedi (1991)
Proportional mean remaining life modelJournal of Statistical Planning and Inference, 29
Purpose – The purpose of this paper is to predict the remaining useful life of a natural gas export compressor, in order to assist decision making of the next planned work order. Design/methodology/approach – Extraction and aggregation of information from rapid developing condition‐monitoring systems has given rise to the Technical Condition Index (TCI) methodology. The trends of aggregated TCIs at compressor level and historical work orders were used as the basis for remaining useful life estimation. Findings – The model is merging several condition‐related measurements and quantifying belief in aging versus belief in condition monitoring. This is important information in, for example, maintenance policy selection, and for the choice of a remaining useful life approach. Practical implications – The model requires historical failure data and well documented condition‐related measurements. Investigation of the physics of failure at the component level also seems important for prognostic theory development. Originality/value – The proposed methodology combines the TCI methodology, the survival analysis (PHM) methodology, and the general maximum‐likelihood theory to estimate and validate parameters and remaining useful life.
Journal of Quality in Maintenance Engineering – Emerald Publishing
Published: Jun 1, 2010
Keywords: Indexing; Hazards; Natural gas
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.