Lognormal distribution is commonly used in engineering.It is also a life distribution of important research values.For long-life products follow this distribution,it is necessary to apply accelerated testing techniques to product demonstration.This paper describes the development of accelerated life testing sampling plans(ALSPs)for lognormal distribution under time-censoring conditions.ALSPs take both producer and consumer risks into account,and they can be designed to work whether acceleration factor(AF)is known or unknown.When AF is known,life testing is assumed to be conducted under accelerated conditions with time-censoring.The producer and consumer risks are satisfied,and the size of test sample and the size of acceptance number are optimized.Then sensitivity analyses are conducted.When AF is unknown,two or more predetermined levels of accelerated stress are used.The sample sizes and sample proportion allocated to each stress level are optimized.The acceptance constant that satisfies producer and consumer risk is obtained by minimizing the generalized asymptotic variance of the test statistics.Finally,the properties of the two ALSPs(one for known-AF conditions and one for unknownAF conditions)are investigated to show that the proposed method is correct and usable through numerical examples. Lognormal distribution is commonly used in engineering. It is also a life distribution of important research values. For long-life products follow this distribution, it is necessary to apply accelerated testing techniques to product demonstration. This paper describes the development of accelerated life testing sampling plans (ALSPs) for both normal production under time-censoring conditions. ALSPs take both producer and consumer risks into account, and they can be designed to work whether acceleration (AF) is known or unknown. to be conducted under accelerated conditions with time-censoring.The producer and consumer risks are satisfied, and the size of test sample and the size of acceptance number are optimized. sensitivity readings are conducted. WHEN AF is unknown, two or more predetermined levels of accelerated stress are used.The sample sizes and sample proportion allocated to each stress level are optimized ies producer and consumer risk is obtained by minimizing the generalized asymptotic variance of the test statistics. Finaally, the properties of the two ALSPs (one for known-AF conditions and one for unknownAF conditions) are investigated to show that the proposed method is correct and usable through numerical examples.