Manufacturer : User Solutions, Inc
Acceptance sampling is a procedure for screening lots of incoming material. We decide whether to accept or reject the entire lot based on the results of a sample. A sampling plan is defined by two parameters: sample size and acceptance number. The acceptance number is the maximum number of allowable defects in the sample. If the sample contains this number or fewer defects, the lot is accepted without further inspection. If the sample contains more than the maximum number of defects, the lot is rejected and a 100% inspection is conducted.
The sample size and acceptance number determine the risks faced by the producer and consumer of the lot. The producer's risk is the probability that a "good" lot will be rejected by the sampling process. Lots are defined as good if they contain no more than a certain level of defectives called the acceptable quality level (AQL). The consumer's risk is the probability that a "bad" lot will be accepted. Lots are called bad if they contain more than a certain level of defectives called the lot tolerance percent defective (LTPD). Using the binomial distribution, the ACCEPTSA worksheet computes the producer's and consumer's risks, given the lot size, sample size, acceptance number, AQL, and LTPD.
Operations Manager
MR-CHART Overview
Control chart for mean and range (MR-CHART)
The basic idea in all quality control charts is to select a sample from a production process at equal intervals of time and record some quality characteristic. The most common quality characteristic is the mean of each sample. If the process is under control, the series of sample means should vary about the population mean in a random manner. That is, we should expect some natural variation in any process and there should be no real assignable cause to this variation. If the process is in control, almost all sample mean values should fall within control limits, almost always defined as the mean plus or minus 3 standard deviations. The standard deviation is a measure of the variation of a process. If all sample observations are constant, the standard deviation is zero; as variation increases, the standard deviation grows. The control charts do not measure the standard deviation directly. Instead, the range (high value minus low value) of each sample is used as a simpler measure of variation. To establish control limits, the range is automatically converted to a standard deviation.
It is important to understand that the control chart is a management-by-exception tool. If a sample mean falls outside the control limits, there is a very small probability that this happened due to randomness or chance alone. In fact, with control limits set at 3 standard deviations, the probability is less than 1% that the sample mean occurred due to chance. There is a very large probability, more than 99%, that the sample mean is due to an assignable cause and an investigation should be conducted.
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