Sampling plans designing with simulation when life time distributed the logistic distribution
Keywords:
Sampling design plan, Cumulative Function, Logistical Distribution, Probability density function (;)Abstract
Sampling design is a very important topic; it is the most efficient when it comes to costs and convenience. Time live distribution should be identified to give the best estimator of sampling plans. This research discuses designing sampling plans when life time follow logistic distribution, so we can use distribution parameters to calculate the required sample size and number of groups. This will enable us to decide to accepting or rejecting the whole lot. The findings of this research show the specific number of group and the specific size of these samples that give the lowest costs for accepting or rejecting the lot. Future research papers could be done on other distributions to investigate how sampling plans can be affected by distributing life time. Designing sequent and multiplied sampling plans can guarantee the decision of accepting or rejecting the lot through hiring the less numbers of groups and smallest size of the sample.
References
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. C. H. Jun, S. Balamurali, and S. H. Lee, “Variables sampling plans for Weibull distributed lifetimes under sudden death testing,” IEEE Trans. Reliab., vol. 55, no. 1, pp. 53–58, 2006.
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