Design of validation experiments for life prediction models

Dan Ao, Zhen Hu and Sankaran Mahadevan

Reliability Engineering and System Safety, 2017, vol. 165, issue C, 22-33

Abstract: This paper proposes a novel validation experiment design optimization (VEDO) method for the assurance of life prediction model, which is one of the key steps in guaranteeing the reliable design of products in meeting the target service life. Life testing data collected from experiments are important for the validation of time-dependent models. However, directly collecting life data for model validation at the operating stress level is usually time-consuming and expensive. In order to overcome this challenge, the accelerated life testing (ALT) method is employed in the proposed method to collect data for model validation. The connection between ALT and model validation is established first; then a VEDO model is developed using the prior information obtained from the computer simulation model. In the VEDO model, the information gain for model validation is maximized within the testing budget and available testing chamber constraints. The obtained optimal number of tests and testing stress levels are designed to maximize the confidence in the validation results. Various sources of uncertainty such as prediction uncertainty, uncertainty of prior information, and observation errors are included within the optimization process in order to improve the robustness of validation experiment design. A composite helicopter rotor hub component is used to demonstrate the effectiveness of the proposed VEDO method.

Keywords: Model validation; Life prediction; Experimental design; Accelerated life testing; Information theory (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832016302009
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:165:y:2017:i:c:p:22-33

DOI: 10.1016/j.ress.2017.03.030

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 ().