Abstract
Accelerated Life Testing (ALT) is an efficient approach to obtain failure observations by subjecting the test units to stresses severer than design stresses and utilize the test data to predict reliability at normal operating conditions. ALT is usually conducted under constant-stresses which need a long time at low stress levels to yield sufficient failure data. Many stress loadings, such as ramp-stresses obtain failure times faster than constant-stresses but the accuracy of reliability predictions based on such loadings has not yet been investigated. We develop test plans under different stress applications such that the reliability prediction achieves equivalent statistical precision to that of the constant-stress. The research shows indeed there are such equivalent plans that reduce the test time, minimize the cost and result in the same accuracy of reliability predictions.
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Notes on contributors
Yada Zhu
Yada Zhu received her doctoral degree from the Department of Industrial and Systems Engineering, Rutgers University. Her research interests include accelerated life testing, risk analysis, condition-based maintenance and quality control in a data rich environment. Currently she is a postdoc fellow with IBM T. J. Waston Research Center.
Elsayed A. Elsayed
Elsayed A. Elsayed is Professor of the Department of Industrial Engineering, Rutgers University. He is also the Director of the NSF/Industry/University Co-operative Research Center for Quality and Reliability Engineering, Rutgers-Arizona State University. He is a co-author of Quality Engineering in Production Systems, McGraw Hill Book Company, 1989. He is also the author of Reliability Engineering, Addison-Wesley, 1996. These two books received the 1990 and 1997 IIE Joint Publishers Book-of-the-Year Award respectively.