Non-parametric Bayesian modeling of hazard rate with a change point for nanoelectronic devices

Chia-Han Yang, Tao Yuan, Way Kuo and Yue Kuo

IISE Transactions, 2012, vol. 44, issue 7, 496-506

Abstract: This study proposes a non-parametric Bayesian approach to the inference of the L-shaped hazard rate with a change point, which has been observed for nanoelectronic devices in experimental studies. Instead of assuming a restrictive parametric model for the hazard rate function, this article uses a flexible non-parametric model based on a stochastic jump process to describe the decreasing hazard rate in the infant mortality period. A Markov chain Monte Carlo simulation algorithm that implements a dynamic version of the Gibbs sampler is developed for posterior simulation and inference. The proposed approach is applied to analyze an experimental data set, which consists of the failure times of a novel nanoelectronic device: a metal oxide semiconductor capacitor with mixed oxide high-k gate dielectric. Results obtained from the analysis demonstrate that the proposed non-parametric Bayesian approach is capable of producing reasonable estimates of the hazard rate function and the change point. As a flexible method, the proposed approach has the potential to be applied to assess the reliability of novel nanoelectronic devices when the failure mechanisms are generally unknown, parametric reliability models are not readily available, and the availability of data is limited.

Date: 2012
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1080/0740817X.2011.587864 (text/html)
Access to full text is restricted to subscribers.

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:taf:uiiexx:v:44:y:2012:i:7:p:496-506

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/uiie20

DOI: 10.1080/0740817X.2011.587864

Access Statistics for this article

IISE Transactions is currently edited by Jianjun Shi

More articles in IISE Transactions from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().