A control chart is a statistical tool used to monitor process variation. A control chart is a graphical representation of data over time. It is used to detect and correct deviations from the desired condition.

## What Is a Control Chart?

The Control Chart is one of the Seven Basic Quality Tools.

A control chart is a graphic display of data that shows how well a process or system performs over time. The control chart displays the performance of a process in terms of its ability to meet specifications.

Control charts help determine if a process is working correctly, identify trends, and take necessary corrective action before it is too late.

## What is a Control Chart Used for?

Control Charts can be used to:

• Determine whether a process is operating within acceptable limits

• You can use control charts to spot unusual patterns in the process

• You can use them to determine whether there is any trend in the data

## What Are the Ten Good Features of a Control Chart?

The following ten features make a Control Chart an excellent visualization tool.

Control Chart is a great way to visualize the process over a period of time. That makes it easy to spot trends and anomalies.

**2. Trend Identification**

You can see where the process has been trending over time. If the trend line goes up or down, this indicates that something may need to change.

**3. Statistical Significance**

When a control chart is plotted, you focus on the outliers (the points that fall outside the upper and lower control limits). There is a 99.73% probability that the point will fall within control limits if the process is in control. The likelihood of a point falling outside the control limits is rare (0.27% probability) and needs to be investigated, and appropriate corrective action should be initiated.

**4. Process Improvement**

When using a control chart to improve a process, you want to look at the upper and lower control limit values. If the upper control limit (UCL) is higher than the upper specification limit (USL), or the lower control limit (LCL) is less than the lower specification limit (LSL), then the process needs improvement.

It shows that the process is not capable of meeting the specification limits.

**5. Outliers**

If any point is outside the control limits, it indicates that the process should be investigated. These could be due to equipment failure, operator error, or other causes.

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## Types of Control charts

Depending on the type of data (continuous vs Discrete) and the sub-group size, we have different control charts.

**Continuous Data**

For continuous data, you could use Xbar-R, Xbar-s or an I-MR type of Control Chart depending upon the subgroup size.

**Discrete Data**

For discrete data, depending upon whether the data is related to the count of defects or the count of defectives, and also whether the subgroup size is constant or varying, you could use c Chart, u Chart, np Chart or p Chart.

The below diagram shows the appropriate control chart for various scenarios.

**Tools for creating a Control Chart**

Various tools can be used to create a histogram.

1. **Manual: **Using a pen and paper: This is how Control Charts were used historically. However, with the availability of computer power, you would hardly see this approach being used.

2. **Microsoft Excel: **This is one of the common tools used to create a control Chart. However, it has its limitations.

3. **Minitab:** Minitab is advanced statistical software Six Sigma professionals use. You can draw a control chart using Minitab.

**4. Other Commercially Available Tools:** Various tools available can help in data collection and process control. For example, Trendable by Argolytics.

**Conclusion**

Control Charts are a powerful tool for monitoring processes. They provide valuable insights into the performance of a process. As such, they are widely used across industries.