# Control Charts

Now that we know the difference between process control and process capability, we must try to understand better what actually a control chart is and how to use it.

Basically, a control chart is a tool used to determine if a process is under statistical control or not. We have different kinds of control charts, some uses attribute data, variable data or both. However for this tutorial purpose, we are going to focus only on few of them.

Prior to introducing those control charts, we must know the difference between variable data and attribute data, which is below:

Variable Data: Continuous scale - measures (weight, distance ...)

Attribute Data: Classified - Good/Bad, Acceptable/Unacceptable …

As well as, we must have in mind some useful definitions:

Defect: Item fails to meet a specification.

Defective: Item with one or more defect.

Number of defectives: In a sample, how many are defective (d out of n).

Number of defects: In a sample total number of defects (c).

Fraction defective: Number of defective items/total number of items (p = x out of n).

To explain better those control charts, we need some amount of data collected, because of that, we are going to use some simple examples to briefly understand each control chart, as well as, show how to interpret them and finally a case study will be provided to help explain actually how to use them.