The spacing of inspection times in intermittent inspection is of great interest, and several ways for the determination of inspection times have been proposed. In most inspection schemes including equally spaced inspection and optimally spaced inspection, the best inspection times in each inspection scheme depend on the unknown parameter, and we need an initial guess of the unknown parameter for practical use. Thus it is evident that the efficiency of the resulting inspection scheme highly depends on the choice of the initial value. However, since we can obtain some information about the unknown parameter at each inspection, we may use the accumulated information and adjust the next inspection time. In this paper, we study this sequential determination of the inspection times in optimally spaced inspection.
In this paper, we decompose the whole likelihood based on grouped data into conditional likelihoods and study the approximate contribution of additional inspection to the efficiency. We also combine the conditional maximum likelihood estimators to construct an approximate maximum likelihood estimator. For an exponential distribution, we see that a large inspection size does not increase the efficiency much if the failure rate is small, and the maximum likelihood estimator can be approximated with a linear function of inspection times.
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