What does AOQL mean?
AOQL – Average Outgoing Quality Limit. AOQL – Average Outgoing Quality Limit. The AOQL of a sampling plan is maximum value on the AOQ curve. It is applicable for defective units, defects per unit, and defects per quantity.
What is AQL and AOQL?
Single sampling plans are investigated for variables indexed by acceptable quality level (AQL) and average outgoing quality limit (AOQL) under measurement error.
How do you calculate Aoq?
Classic Formula (Equation 2): N x Pd x Pa = 30 x 0.100 x 0.430 = 1.290 << when divided by Pa, this value equals the average number of defectives that existed in an average lot (accepted and rejected, combined) prior to IQC sampling = 1.291 / 0.430 = 3.000.
What is Aoq curve?
The AOQ curve shows how outgoing quality (y-axis) depends on the incoming quality (bottom axis). The average outgoing quality is only applicable to the characteristics defective units, defects per unit, and defects per quantity and assumes rejected lots are 100% inspected and all defectives/defects are removed.
Why is AOQL important?
The average outgoing quality limit (AOQL) represents the maximum %defective in the outgoing product. When incoming quality is very bad, the entire lot is rejected. Therefore, the outgoing quality is also very good because the lot will be rejected and the bad parts won’t get through.
What is OC curve in statistics?
The Operating Characteristic (OC) curve describes the probability of accepting a Lot as a function of the Lots quality (where a Lot is a batch or section of continuous work). The shape of the curve is dictated by the Acceptance Constant (K) and the number of samples (n).
What is Aoq in statistics?
Average Outgoing Quality (AOQ): The expected average quality level of an outgoing product for a given value of incoming product quality. AOQ plot represents the relationship between the quality of incoming and outgoing materials. When incoming lots are very good, the outgoing quality will be good.
What is average sample number?
In sequential procedures for statistical estimation, hypothesis testing or decision theory, the number of observations taken (or sample size) is not pre-determined, but depends on the observations themselves. The expected value of the sample size of such a procedure is called the average sample number.
What does OC curve reveal?
The operating characteristics (OC) curve tells us how good our samples are and the probability of accepting defects. The steeper the curve, the better the sampling plan.
What is the importance of OC curve?
The operating characteristic (OC) curve depicts the discriminatory power of an acceptance sampling plan. The OC curve plots the probabilities of accepting a lot versus the fraction defective. When the OC curve is plotted, the sampling risks are obvious.