By Topic

Condition-based predictive maintenance by multiple logistic function

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
K. S. Park ; Korea Adv. Inst. of Sci. & Technol., Seoul, South Korea

For complex systems, the system failures exhibit an exponential nature, negating the benefit of traditional, time-based preventive maintenance. Under this circumstance, the condition-based predictive maintenance (CbPM) is more appropriate where the system condition can be monitored from the surface of running machinery, and maintenance is performed only when needed as the failure prognosis dictates. The author presents a cost optimal prognostic criterion for CbPM using a multiple logistic function of risk variables to be monitored, which fluctuate randomly according to a certain probability distribution. A numerical example demonstrates the procedure and utility of the method

Published in:

IEEE Transactions on Reliability  (Volume:42 ,  Issue: 4 )