Control Charts for Variables: A number of samples of component coming out of the process are taken over a period of time. Each sample must be taken at random and the size of sample is generally kept as 5 but 10 to 15 units can be taken for sensitive control charts. Control Charts for Attributes In the previous types of charts, measurement data was the process variable. This data is often continuous, and the charts are based on theory for continuous data. Attribute Charts. Attribute Charts are a set of control charts specifically designed for Attributes data (i.e. counts data). Attribute charts monitor the process location and variation over time in a single chart. The family of Attribute Charts include the: Np-Chart: for monitoring the number of times a condition occurs, Attribute Control Charts Overview Yes/No Data: p and np Control Charts. With this type of data, you are examining a group of items. Binomial Distribution. The p and np control charts involve counts. You are counting items. Counting Data: c and u Control Charts. We just looked at yes/no type of Attribute charts are a kind of control chart where you display information on defects and defectives. Helps you visualize the enemy – variation! There are four types of Attribute Charts: Evaluates the stability of a process when we are evaluating the proportion of defectives vs in good order as a percentage. Control charts are simple but very powerful tools that can help you determine whether a process is in control (meaning it has only random, normal variation) or out of control (meaning it shows unusual variation, probably due to a "special cause"). Sometimes, businesses want to track how well something works over a period of time. When this need arises, many turn to control charts for attribute data.

## Attributes control charts for binomial data Values for binomial data are classified into one of two categories such as pass/fail or go/no-go. Binomial data are often used to calculate a proportion or a percentage, such as the percentage of sampled parts that are defective.

The classic control charts for attribute data (p-charts, u-charts, etc.,), are based on assumptions about the underlying distribution of their data (binomial or Control Chart for Fraction Nonconforming. Fraction nonconforming is based on the binomial distribution. n: size of population. p p p: probability of 9 Jul 2019 Randomly selected products are tested for the given attribute or attributes the chart is tracking. Different types of quality control charts, such as X- Part 8: Attributes Control Charts. Our focus for the prior publications in this series has been on introducing you to. Statistical Process Control (SPC)—what it is,

### 16 May 2013 Understand the statistical basis of control charts for attributes. 2. Discuss when to use the different types of attribute control charts. 3. Construct

Control charts for attribute data are used singly. When to use a control chart; Basic procedure; Create a control chart; Control chart resources. Control Chart Control Charts for Variables vs. Charts for Attributes. Sometimes, the quality control engineer has a choice between variable control charts and attribute control For example, when an item is to be classified as conforming to quality standards or nonconforming, attribute control charts are often used. The p-chart is an