However, if there is one failure, the lot is rejected (fails) and should be segregated, labeled, and quarantined until addressed by the Material Review Board (MRB).
If all 42 randomly selected pieces are inspected and all of the pieces meet the inspection criteria (zero failures), the lot is accepted (passes). In this example, the acceptance number is 0 (c). For each lot inspected, we make an accept/reject decision with the accepted lots released to stock and the rejected lots segregated, labeled, and quarantined.įigure 2: Graphical representation of a lot (N), sample (n), and acceptance number (c)įor example, a lot containing 2,500 (N) pieces is inspected using an AQL of 1.0, which requires 42 (n) pieces to be randomly selected from the lot and inspected. A lot is a whole - every member of a group - and a sample is a subset of a lot. Type II Beta Error (β) Consumer’s Risk is the probability of accepting a bad lot.Īll sampling plans utilize the concept of a lot (N), sample (n) drawn randomly from the lot, and an acceptance number (c). Type I Alpha Error (α) Producer’s Risk is the probability of rejecting a good lot. These errors are referred to as Producer’s Risk and Consumer’s Risk. However, because sampling plans base decisions on a sample of the lot and not the entire lot, there is always a chance of making an incorrect decision.
Ideally, a sampling plan should reject all “bad” lots while accepting all “good” lots. The risks are defined by the margin of error and confidence intervals. Recall that variable data can be measured on a continuous scale and attribute data measures discrete data points, such as pass/fail, go/no-go, and things that can be counted.Īll statistical sampling is subject to risk. Sampling plans can be used for both variable and attribute data. Sampling plans are not a substitute for process control. Sampling plans are a means of identifying, not preventing,poor quality. Sampling plans are used when testing is destructive and all parts would be consumed during testing, leaving no parts for commercial use or distribution, the cost of 100 percent inspection is very high, or 100 percent inspection takes too long. Statistical sampling plans are a commonly used quality control technique for incoming, in-process, and final inspection. Basically, statistical sampling plans are used to make decisions on whether to accept or reject products. Probability sampling is based on the fact that every member of a population has an equal chance of being selected.
(If not, they should!) However, most individuals just follow the requirements of the procedure without fully comprehending how sampling plans actually work. Most organizations have a statistical procedure that specifies a certain acceptable quality level (AQL) based on risk. Sampling plans are used extensively throughout organizations regulated by the FDA. By Mark Durivage, Quality Systems Compliance LLC
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