EconPapers    
Economics at your fingertips  
 

Design of optimum multiple-stress accelerated life testing plans based on proportional odds model

Elsayed A. Elsayed and Hao Zhang

International Journal of Product Development, 2009, vol. 7, issue 3/4, 186-198

Abstract: Accelerated Life Testing (ALT) is used to obtain failure time data quickly under high stress levels in order to predict product life and performance under the design stress. Most of the previous work on designing ALT plans is focused on the application of a single stress. However, as components or products become more reliable due to technological advances, it becomes more difficult to obtain significant amount of failure data within a reasonable amount of time using single stress only. Multiple-stress ALTs have been employed as a means of overcoming such difficulties. In this paper, we design optimum multiple-stress ALT plans based on the Proportional Odds (PO) model. The optimum combinations of stress levels and the number of test units allocated to each combination are determined such that the variance of the reliability prediction of the product over a pre-specified period of time is minimised. The proposed ALT plan is illustrated by a numerical example.

Keywords: accelerated life testing; ALT plans; multiple stress; proportional odds model; failure time; product life; product performance; reliability prediction. (search for similar items in EconPapers)
Date: 2009
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.inderscience.com/link.php?id=23317 (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:ids:ijpdev:v:7:y:2009:i:3/4:p:186-198

Access Statistics for this article

More articles in International Journal of Product Development from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().

 
Page updated 2025-03-19
Handle: RePEc:ids:ijpdev:v:7:y:2009:i:3/4:p:186-198