On Designing Unknown-Sigma Sampling Plans Based on a Wide Class of Non-Normal Distributions

Abstract

The theory of acceptance sampling by variables based on non-normal populations has been recently developed in various directions, as seen in an interesting survey by Owen [9]. In the present paper we shall confine ourselves to the design problem of the unknown-sigma sampling plans (including the corresponding known-sigma ones) based on a fairly wide class of non-normal distributions. We shall propose here an approximate (but a general) solution for this problem, by which one can readily obtain the desired sampling plans tailor-made to a particular non-normal distribution with known skewness and kurtosis. The general solution proposed is illustrated for the classes of the gamma, Weibull and Burr distributions with some numerical examples.

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