Reliability inference for field conditions from accelerated degradation testing

  1. Haitao Liao1,
  2. Elsayed A. Elsayed2,*

Article first published online: 18 MAY 2006

DOI: 10.1002/nav.20163

Issue

Naval Research Logistics (NRL)

Naval Research Logistics (NRL)

Volume 53, Issue 6, pages 576–587, September 2006

Additional Information

How to Cite

Liao, H. and Elsayed, E. A. (2006), Reliability inference for field conditions from accelerated degradation testing. Naval Research Logistics, 53: 576–587. doi: 10.1002/nav.20163

Author Information

  1. 1

    Industrial and Manufacturing Engineering Department, Wichita State University, Wichita, KS 67260, USA

  2. 2

    Department of Industrial and Systems Engineering, Rutgers, State University of New Jersey, Piscataway, NJ 08854, USA

*Department of Industrial and Systems Engineering, Rutgers, State University of New Jersey, Piscataway, NJ 08854, USA

Publication History

  1. Issue published online: 17 JUL 2006
  2. Article first published online: 18 MAY 2006
  3. Manuscript Accepted: 14 APR 2006
  4. Manuscript Revised: 6 APR 2006
  5. Manuscript Received: 6 APR 2005

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Keywords:

  • reliability prediction;
  • stochastic stress exposure;
  • approximation;
  • Brownian motion with drift;
  • Itô calculus

Abstract

Accelerated degradation testing (ADT) is usually conducted under deterministic stresses such as constant-stress, step-stress, and cyclic-stress. Based on ADT data, an ADT model is developed to predict reliability under normal (field) operating conditions. In engineering applications, the “standard” approach for reliability prediction assumes that the normal operating conditions are deterministic or simply uses the mean values of the stresses while ignoring their variability. Such an approach may lead to significant prediction errors. In this paper, we extend an ADT model obtained from constant-stress ADT experiments to predict field reliability by considering the stress variations. A case study is provided to demonstrate the proposed statistical inference procedure. The accuracy of the procedure is verified by simulation using various distributions of field stresses. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006.

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