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What is Attribute Sampling?

Malcolm Tatum
By
Updated May 17, 2024
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Attribute sampling is a strategy that is used to determine whether or not a given product meets the standards of a buyer or seller. Companies often use this approach as a means to evaluate raw materials for use in the production of goods and services, as well as a mechanism for making sure those finished goods meet the quality standards set by the manufacturer. There are several benefits to this type of inspection process as well as a couple of potential liabilities.

An attribute sampling follows a basic approach that involves randomly selecting samples from each lot of goods that is under consideration. The exact number of samples will vary, based on the type of goods under consideration and the number of units included in the lot. Typically, the idea of an attribute sampling plan is to include enough units to develop a good sense of the overall quality of the lot. By assessing each of the samples and deciding if each one is acceptable or defective, it is possible to determine if the lot is good enough for sale or should be rejected.

Employing an attribute sampling approach works very well in a manufacturing environment. Businesses like textile firms depend on the use of quality raw materials in order to produce their lines of finished goods. In the event those raw materials are not up to the standards set by the company, the products produced will also be less than first quality. This in turn means the units must be sold as seconds or off-quality goods at greatly reduced rates, which means the manufacture makes very little profit on those reduced quality goods. By taking random samples of the raw materials before they are actually introduced into the manufacturing process, it is possible to minimize the production of second quality products and produce more first quality items that can be sold at a greater profit per unit.

While attribute sampling is a quick and efficient way to evaluate lots for purchase or sale, there is one disadvantage to keep in mind. By choosing to go with this approach rather than a full inspection of all the goods in question, there is the possibility of overlooking one or more units that are obviously inferior. This can result in causing a number of quality issues during the production process, as well as harming customer relations in the event the defective goods produced are actually shipped to customers. For this reason, many manufacturers employ a dual approach that begins with the attribute sampling and progresses to a complete evaluation of the entire lot, if a certain percentage of defective units are found during the random sampling.

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Malcolm Tatum
By Malcolm Tatum , Writer
Malcolm Tatum, a former teleconferencing industry professional, followed his passion for trivia, research, and writing to become a full-time freelance writer. He has contributed articles to a variety of print and online publications, including About Mechanics, and his work has also been featured in poetry collections, devotional anthologies, and newspapers. When not writing, Malcolm enjoys collecting vinyl records, following minor league baseball, and cycling.

Discussion Comments

By discographer — On Apr 24, 2011

The disadvantage of overlooking faulty products is a good point. I can also think of a disadvantage of a full inspection though. I would imagine that if every single item was hand checked, there might be damage like scratches and so forth done to the product as well. That would also impact the consumers negatively.

So I don't think that a full inspection is a better alternative to attribute sampling.

By ysmina — On Apr 22, 2011

I think that this kind of sampling can also be used to oversee inspections.

If an inspector reports that the materials and product are of top quality but the sampling result says differently, you know that the inspector is not doing their job right.

Malcolm Tatum

Malcolm Tatum

Writer

Malcolm Tatum, a former teleconferencing industry professional, followed his passion for trivia, research, and writing...
Learn more
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