Design and Evaluation of Single Sampling Plans

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Bol Sampling plans are, in general, classified under two categories, viz., lot-by-lot sampling by attributes and lot-by-lot sampling by variables. Lot-by-lot sampling by attributes is applied when the quality characteristic under consideration is an attribute. When the quality characteristic is measurable on a continuous scale, the associated sampling plan is known as lot-by-lot sampling by variables. In lot-by-lot inspection by variables, one or more samples of items are drawn from a given lot; the measurements of a quality characteristic in each sampled item are taken; and the decision of acceptance or rejection of the lot is made as a function of such measurements. The theory of inspection by variables is applicable when the quality characteristic of sampled items is measurable on a continuous scale and the functional form of the probability distribution is assumed to be known. The measurement data obtained from a production process will exhibit any kind of probability distribution. This study focuses on the design and evaluation of such sampling plans under both normal and non-normal lifetime distributions.

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Sampling plans are, in general, classified under two categories, viz., lot-by-lot sampling by attributes and lot-by-lot sampling by variables. Lot-by-lot sampling by attributes is applied when the quality characteristic under consideration is an attribute. When the quality characteristic is measurable on a continuous scale, the associated sampling plan is known as lot-by-lot sampling by variables. In lot-by-lot inspection by variables, one or more samples of items are drawn from a given lot; the measurements of a quality characteristic in each sampled item are taken; and the decision of acceptance or rejection of the lot is made as a function of such measurements. The theory of inspection by variables is applicable when the quality characteristic of sampled items is measurable on a continuous scale and the functional form of the probability distribution is assumed to be known. The measurement data obtained from a production process will exhibit any kind of probability distribution. This study focuses on the design and evaluation of such sampling plans under both normal and non-normal lifetime distributions.


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