Defeating CBM

The following slide presentation on the importance of distinguishing failures from suspensions on work orders,  refers to the Proportional Hazard Model (PHM) and the shape parameter β. The shape parameter is calculated from a good sample of condition monitoring and age data by using the EXAKT CBM optimizing system. EXAKT uses PHM by including CBM (i.e. condition monitoring) data in an extended Weibull equation. The equation for the PHM (extended Weibull) that relates the failure rate to both age t, and condition monitoring data Zi is:

h(t,\mathbf{Z}(t);\beta,\eta,\gamma)=\frac{\beta}{\eta}(\frac{t}{\eta})^{\beta-1}exp(\sum_{i=1}^{m}\gamma_{i}Z_{i}(t))

where β>0 is the shape parameter, η>0 is the scale parameter, and γ =( γ12,… γm,) is the coefficient vector for the condition monitoring variable (covariate) vector Z(t). The parameters β, η, and γ, will be estimated by the numerical algorithm in EXAKT.

© 2011 – 2016, Murray Wiseman. All rights reserved.

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[…] and a small of condition indicator influence CBM will have been defeated. See the article Defeating CBM. […]

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[…] For more information on the effect of misidentifying suspensions see the article “Defeating CBM“ […]

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[…] See for example here and here. […]