### Table of contents

### Full Guide To Six Sigma Control Charts

Six Sigma Control Charts are known as process behavior charts. This allows us to see how the process behaves over time. In Six Sigma studies, we read Control charts in the Control phase, like the statistical process contcontrol chart (SPC chart). A control chart is used in the initial stage to observe the process behavior and to determine the Voice of Process (VoP). Only when the process is stable can we then start to run the project. Otherwise, it is essential to make the process work first. It is one of the seven most effective quality tools.

If the process is stable, it means all data points are within the control limits. There is no other reason that makes the process unstable.

### What is a Control Chart?

We have variations everywhere. No process is the same. This means there cannot be any common cause variation. These control charts show how the variations affect our process over time. They also indicate whether or not our process will remain within control. This variation can be visualized using control charts. The control charts have a central line, or the mean line (average), then there is the Upper Control Limit and Lower Control Limit (UCL), respectively. The center line on both the upper and lower control limits is three standard deviations. You can also have the lower warning limit and the upper warning limit. The question now is: Which standard deviation is greater than the central line? This is the one that alarms us when data points exceed this limit. It can cause the process to become unstable.

### Significance and Objective of Six Sigma Control Chart

To see any special cause variation, we use a control chart. The negative side of a process does not always show up in special cause variation. Sometimes it is a positive indicator. We can take preventive measures to avoid process variation if there is a special reason. We could also take preventive measures to avoid situations like a flat tire making us late. Because the special cause can be avoided, the assignable cause is unavoidable.

A control chart can be used to determine whether the process is stable. If it is unstable, then we should work to improve the process. The control chart can also help you distinguish between assignable and unassignable reasons for variations. The control chart is designed to simplify the process while omitting assignable causes.

This allows you to determine the average process and estimate the variation (the histogram’s spread). It is important to realize that the process under control is more important. You must also understand what the process means. All data points should be within the Upper and the Lower Control Limits. This will allow us to determine if our process is capable enough and what we want to do.

**How can we verify the Process Capability using Cp and K?**

The control chart can be used to see process improvements, and the average process. We can also compare the results with the previous process mean. This will give us information about the control of our process. As a control chart, the rules are the same as for a normal chart. 68% should be under the first standard deviation. 95% should be within 2nd standard deviation. 99.7 percent data should be within 3rd.

### How to make and use a Control Chart

Minitab can be used to create control charts. To do this, enter the data into Minitab and then use the control chart according to data types.

Minitabs are not required to make this calculation in Excel. We need to enter all data points in Excel and subtract the average. Then we can calculate the standard deviation using the standard deviation formula. Then we continue until we reach the third standard deviation. Finally, we can use the graph.

This is a simple IMR chart that we can create and use for continuous data types.

### When is a Control Chart appropriate?

- A Control Chart can be used at the beginning of a project, or anytime we need to see the VoP. You can also see the VoP to determine the purpose of the project.
- A Control Chart at the end of a project can help us see improvements in the process control chart (SPC chart). This could also be used to determine if the project is a success.
- The Control Chart is also useful in checking process stability, verifying that the statistical process control chart (SPC chart) can be improved, and making necessary improvements where needed.

**Four Process States within a Control Chart**

Below are the 4 process states of a Control Chart.

- The
**Ideal**State: This is the state where all data points are within the control limits. Non-conformance is not possible. - The
**Threshold**status: While data points are under control or the process is stable at all times, there may be some non-conformance over time. - The
**Brink Of Chaos**state is where the process is under control, but it is also at the edge of making mistakes. - The fourth stage is when we are
**out of control**and have unpredicted non-conformance.

### Types of control charts

Control charts can be of seven types depending on the data type. Three types of Control Charts can be used if we have continuous data. **IMR Chart, XBar R Chart,** and Bar S Chart.

We can use 4 types of Control charts if we have a distinct data type: C, Np, and **U Charts**. These types are listed below:

**I- MR Chart**

The I-MR charts are used when subgrouping is not possible.

**XBar R Chart**

Continuous data is when there are more than two subgroup sizes. Standard charts for variables data, X bar and R charts are used to help determine whether a process is predictable and stable. The X-bar chart shows X as the mean of all subgroups, while R is the range.

The X Bar S chart is used to determine the mean and variation of subgroups. It can be used to determine the size of more than two subgroups and it can also be used to determine the number of subgroups.

These charts can be used to display continuous data. Let’s now discuss discrete data. We have four types of charts for discrete data. This is because discrete data can be divided into two parts (i) defects or (ii), and the size of each subgroup will determine how it changes.

The Np and P charts are used to identify defective data. They can be used to verify statistical process control chart (SPC chart) stability and see the data points. The difference between Np and P charts is that P is used for sample sizes that vary, while Np chart is used for constant samples.

**U Control Charts**

The C and U charts can be used to determine the stability of a single unit that might have multiple defects. The number of defects found in a pen, for example. We can also see the defects in the same sample, or on different samples.

C Control Chart can be used when more than one defect is present and the sample size has been fixed. U Control Chart can be used to fix more than one defect, and for smaller samples.

### How is a Control Chart used as a Tool for Analysis?

The Six Sigma Control Chart can be used to monitor, control, and improve process performance over time. It examines variation and its source.

Control charts are used to monitor and detect process variations over time. This helps us keep track of the process variation over time. It shows the quantity and variation of the statistical process control chart (SPC chart), as well as the current capabilities of the process. It also allows us to identify particular events that might disrupt normal operations. Control Charts can be used in the Improve phase to monitor the process improvement.

Control Charts and Run Charts are able to show the progress made during the project’s execution. They are one of the most useful tools for analysis.

It helps monitor the progress of the process, and allows you to quantify its capability and identify the causes that are causing it. It is usually part of the process management system.

It can also be used to distinguish between common and special causes. We’ve already covered in detail the use and limitations of control charts. Below are some tips that can be helpful when using Control Charts.

#### Have you used a Control Chart for one of your projects?

Tell us your experience in the comments below.