TY - JOUR
T1 - Design of statistically and energy-efficient accelerated life testing experiments
AU - Zhang, Dan
AU - Liao, Haitao
N1 - Funding Information:
Haitao Liao is an Associate Professor of Systems and Industrial Engineering and Director of the Reliability & Intelligent Systems Engineering Laboratory at the University of Arizona, Tucson, Arizona. He received his Ph.D. degree from the Department of Industrial and Systems Engineering at Rutgers University in 2004. He also received M.S. degrees in Industrial Engineering and Statistics from Rutgers University. His research interests focus on modeling of accelerated testing, probabilistic risk assessment, maintenance models and optimization, spare part inventory control, and prognostics. His research has been sponsored by the National Science Foundation, Department of Energy, and U.S. Nuclear Regulatory Commission. He is a member of IIE, INFORMS, and IEEE. He is a recipient of the National Science Foundation CAREER Award in 2010 and the winner of the 2010 & 2013 William A. J. Golomski Award.
Funding Information:
This work is supported in part by the National Science Foundation under grant CMMI-1245463.
PY - 2014/10/3
Y1 - 2014/10/3
N2 - The basic idea of Accelerated Life Testing (ALT) is to expose a limited number of test units of a product to harsher-than-normal operating conditions to expedite failures. Based on the failure time data collected in a short time period, an ALT model incorporating the underlying failure time distribution and life-stress relationship can be developed for predicting the reliability of the product under the normal operating condition. However, ALT experiments often consume significant amounts of energy due to the harsher-than-normal operating conditions created and controlled by test equipment. In this article, a new ALT design methodology is developed that has the objective of improving the statistical and energy efficiency of ALT experiments. The resulting statistically and energy-efficient ALT plan depends not only on the reliability of the product to be evaluated, but also on the physical characteristics of the test equipment and its controller. Particularly, the statistical efficiency of each candidate ALT plan needs to be evaluated and the corresponding controller capable of providing the required stress loadings must be designed and simulated to evaluate the total energy consumption of the ALT plan. In this article, mathematical formulations, computational algorithms, and simulation tools are provided to handle such complex experimental design problems. Numerical examples are provided to demonstrate the effectiveness of the proposed methodology in energy reduction in ALT. © 2014
AB - The basic idea of Accelerated Life Testing (ALT) is to expose a limited number of test units of a product to harsher-than-normal operating conditions to expedite failures. Based on the failure time data collected in a short time period, an ALT model incorporating the underlying failure time distribution and life-stress relationship can be developed for predicting the reliability of the product under the normal operating condition. However, ALT experiments often consume significant amounts of energy due to the harsher-than-normal operating conditions created and controlled by test equipment. In this article, a new ALT design methodology is developed that has the objective of improving the statistical and energy efficiency of ALT experiments. The resulting statistically and energy-efficient ALT plan depends not only on the reliability of the product to be evaluated, but also on the physical characteristics of the test equipment and its controller. Particularly, the statistical efficiency of each candidate ALT plan needs to be evaluated and the corresponding controller capable of providing the required stress loadings must be designed and simulated to evaluate the total energy consumption of the ALT plan. In this article, mathematical formulations, computational algorithms, and simulation tools are provided to handle such complex experimental design problems. Numerical examples are provided to demonstrate the effectiveness of the proposed methodology in energy reduction in ALT. © 2014
KW - Accelerated life testing
KW - energy consumption
KW - optimum experimental design
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U2 - 10.1080/0740817X.2013.876127
DO - 10.1080/0740817X.2013.876127
M3 - Article
AN - SCOPUS:84903536468
SN - 0740-817X
VL - 46
SP - 1031
EP - 1049
JO - IIE Transactions (Institute of Industrial Engineers)
JF - IIE Transactions (Institute of Industrial Engineers)
IS - 10
ER -