Six-Sigma17 - Attribute Control Charts What are Attributes...

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Attribute Control Charts What are Attributes Control Charts? The Shewhart control chart plots quality characteristics that can be measured and expressed numerically. We measure weight, height, position, thickness, etc. If we cannot represent a particular quality characteristic numerically, or if it is impractical to do so, we then often resort to using a quality characteristic to sort or classify an item that is inspected into one of two "buckets". An example of a common quality characteristic classification would be designating units as "conforming units" or "nonconforming units". Another quality characteristic criteria would be sorting units into "non defective" and "defective" categories. Quality characteristics of that type are called attributes. Note that there is a difference between "nonconforming to an engineering specification" and "defective" -- a nonconforming unit may function just fine and be, in fact, not defective at all, while a part can be "in spec" and not function as desired (i.e., be defective). Examples of quality characteristics that are attributes are the number of failures in a production run, the proportion of malfunctioning wafers in a lot, the number of people eating in the cafeteria on a given day, etc.
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Use of p-Charts The data are collected in samples, each sample may have unequal number of ‘Inspection unites’. Each inspection unit can be either classified as ‘pass’ or ‘failure’. For each sample, the ‘rate of pass’, or ‘rate of failure’, p, is calculated. A control chart will be calculated and kept for , p. P-chart is based on 3-Sigma limits, it is based on Binomial distribution.
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Proportions Control Charts p is the fraction defective in a lot or population The proportion or fraction nonconforming (defective) in a population is defined as the ratio of the number of nonconforming items in the population to the total number of items in that population. The item under consideration may have one or more quality characteristics that are inspected simultaneously. If at least one of the characteristics does not conform to standard, the item is classified as nonconforming. The fraction or proportion can be expressed as a decimal, or, when multiplied by 100, as a percent. The underlying statistical principles for a control chart for proportion nonconforming are based on the binomial distribution. Let us suppose that the production process operates in a stable manner, such that the probability that a given unit will not conform to specifications is p . Furthermore, we assume that successive units produced are independent. Under these conditions, each unit that is produced is a realization of a Bernoulli random variable with parameter p . If a random sample of n units of product is selected and if D is the number of units that are nonconforming, the D follows a binomial distribution with parameters n and p
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* The p chart reflected in % The best use of an attribute chart is to: . Follow trends and cycles . Evaluate any change in the process
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This note was uploaded on 05/09/2010 for the course IE IE7610 taught by Professor Dr.kaiyang during the Winter '10 term at Wayne State University.

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Six-Sigma17 - Attribute Control Charts What are Attributes...

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