Acceptance sampling is a method used to determine if items meet certain standards. It involves testing a random sample of a batch to avoid discarding the entire batch. Companies can determine the percentage of defects they will accept and the sample size. Statistical operations can help determine the required sample size. The degree of quality is based on determining an acceptable level of error.
Acceptance sampling is a method used to determine whether merchandise or other items meet certain standards. This type of sampling is employed at different manufacturing sites and is generally favored as it can provide manufacturers with specific control over what type of standards to enforce. Several methods are used to determine how to sample batches, what percentage of error is acceptable, and when to discard batches based on the location of too many errors.
One of the reasons acceptance sampling is useful is because it avoids taking an entire batch of product, testing it, and then discarding it. Once tested, many items are no longer salable and must be discarded. When testing part of a lot, determined with random sampling, simple random sampling, or another form of selection that guarantees random selections, most of the lot may still be used if found acceptable.
The easiest way to illustrate acceptance sampling is through example. Company Z wants to test its candy hearts to ensure that no more than 10% of the product manufactured is broken. With a lot of hearts, they determine that they will randomly select 5% of that lot and see if any of the hearts are broken. If that smaller sample has more than 10% broken hearts, Company Z will discard the entire batch. With less than 10% broken hearts, the batch is considered good, packaged and shipped to stores.
There are a few things to note about this example. Company Z decides the percentage of defects it will accept. It could easily accept up to 20% of broken hearts, or set a stricter standard and only accept 3%. The company also determines how to select batch samples and the sample size. Many companies perform this sampling on every batch they produce for consistent quality control.
There are specific statistical operations that can help companies determine the required sample size that is representative of the lot. In other words, companies must select a size that is large enough to truly represent their population or the lot they come from. This number is small enough that there are still a lot of salable parts left in the lot.
Acceptance sampling can be a very good way to determine the quality of a lot, taking into account the sample size and after setting a reasonable percentage of quality. There are circumstances when companies draw a bad random sample, which could mean scrapping a batch or selling a product with more flaws than expected. More often than not, the sample is representative of the lot and will serve as a good way to test quality.
The degree to which this means a company delivers a quality product is really based on determining an acceptable level of error. With higher allowable error percentages, the quality will be worse. Using lower error limits means that most of the batches produced are of better quality. On any type of extremely delicate equipment, companies can set low percentages for batch error in acceptance sampling.
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