The inverse Gamma process: A family of continuous stochastic models for describing state-dependent deterioration phenomena

M. Guida and G. Pulcini

Reliability Engineering and System Safety, 2013, vol. 120, issue C, 72-79

Abstract: This paper proposes the family of non-stationary inverse Gamma processes for modeling state-dependent deterioration processes with nonlinear trend. The proposed family of processes, which is based on the assumption that the “inverse†time process is Gamma, is mathematically more tractable than previously proposed state-dependent processes, because, unlike the previous models, the inverse Gamma process is a time-continuous and state-continuous model and does not require discretization of time and state. The conditional distribution of the deterioration growth over a generic time interval, the conditional distribution of the residual life and the residual reliability of the unit, given the current state, are provided. Point and interval estimation of the parameters which index the proposed process, as well as of several quantities of interest, are also discussed. Finally, the proposed model is applied to the wear process of the liners of some Diesel engines which was previously analyzed and proved to be a purely state-dependent process. The comparison of the inferential results obtained under the competitor models shows the ability of the Inverse Gamma process to adequately model the observed state-dependent wear process.

Keywords: State-dependent degradation process; Inverse time process; Conditional distribution of degradation growth; Wear; Cylinder liner of diesel engines (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832013000896
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:120:y:2013:i:c:p:72-79

DOI: 10.1016/j.ress.2013.03.013

Access Statistics for this article

Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares

More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().