Data - Acceptance Sampling by Attributes
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This command allows you to create single attribute sampling plans or to compare multiple attribute sampling plans; therefore, you will not enter specific raw data into Minitab, but will enter information regarding your process into the dialogs.

·    AQL and RQL - represent specific points of interest on the OC curve. The consumer and supplier should agree to the poorest level of quality that would be acceptable as a process average (AQL) The consumer and supplier should also agree to the poorest level of quality that the consumer will tolerate in an individual lot (RQL)

·    Sampling risk - represents the probability of accepting a poor lot (consumer's risk) and rejecting a good lot (producer's risk)

·    Lot size - represents the entire population of units that the sample will be taken from. Lots should be homogeneous. They should be packaged and shipped in sizes that are well-managed by both the consumer and supplier, and in a way that allows easy selection of samples. It is usually more economical to inspect larger lots rather than smaller lots.

Keep in mind that the units to be inspected should be selected randomly and should be representative of all the items in the lot. This may require extra effort such as numbering each item and drawing random numbers or stratifying the lot and sampling from each strata or layer; however, this process is necessary for the effectiveness of the sampling process.