Technometrics· 2013Q1
The Inverse Gaussian Process as a Degradation Model
- 545citations
- Q1SCImago
- 2013year
Short summary
The inverse Gaussian (IG) process is proposed as a flexible and physically interpretable model for product degradation, outperforming the widely used Gamma process.
AI-generated from the title and abstract; the full text is not read.
Key points
- The inverse Gaussian (IG) process is presented as an effective degradation model with a clear physical interpretation.
- The IG process is a limiting compound Poisson process and the first passage process of a Wiener process.
- It offers greater flexibility than the Gamma process in accounting for random effects and explanatory variables in degradation analysis.
- Statistical inference methods for random effects models and model selection are discussed.
AI-generated from the title and abstract; the full text is not read.
Abstract
This article systematically investigates the inverse Gaussian (IG) process as an effective degradation model. The IG process is shown to be a limiting compound Poisson process, which gives it a meaningful physical interpretation for modeling degradation of products deteriorating in random environments. Treated as the first passage process of a Wiener process, the IG process is flexible in incorporating random effects and explanatory variables that account for heterogeneities commonly observed in degradation problems. This flexibility makes the class of IG process models much more attractive compared with the Gamma process, which has been thoroughly investigated in the literature of degradation modeling. The article also discusses statistical inference for three random effects models and model selection. It concludes with a real world example to demonstrate the applicability of the IG process in degradation analysis. Supplementary materials for this article are available online.
The authors' abstract, as published at the source. Technometrics, 2013 · DOI ↗
Continue with a free account
Ask the paper: 3 free questions a day about this paper; save it, get its citation, new summaries every day for your field. Takeaways are Premium.
Continue free on the webSign in with Google or Apple; no card needed. You come back to this paper.
On your phone:
Field: Safety, Risk, Reliability and Quality
Safety, Risk, Reliability and QualityEngineering