This rule is apparently not statistically motivated nor is it mentioned by sampling theorists and practitioners.They decide which lots of product to accept and release and which lots to reject and either rework or discard.Ideally, a sampling plan should reject all bad lots while accepting all good lots.However, because the sampling plan bases its decision on a sample of the lot and not the entire lot, there is always a chance of making an incorrect decision.
The behavior of a sampling plan is described by the sampling plans Operating Characteristic (OC) curve. To select a statistically valid sampling plan, the objective of the inspection should be determined based on past performance, other controls that are in place, potential failure modes and so on. Then the Acceptable Quality Level (AQL) of the sampling plan should be documented to demonstrate that the sampling plan meets this objective. Hence a correct sampling plan will provide a better protection on decision making. This course is designed to meet such protection where participants will learn the correct way of taking sampling. Two Sampling Plans namely, Inspection by Attributes (ANSIASQ Z1.4) and Inspection by Variables (ANSIASQ Z1.9) will be covered with application.
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