Factors For Computing Control Chart Limits 3 Sigma
Control charts are a tool used in statistical process control to monitor the output of a process over time. The chart allows you to identify changes in the process that may indicate a need for adjustment. The control chart consists of a central line, which represents the average value of the process output, and two limit lines, which define the range of acceptable variation.
What is 3 Sigma?
3 Sigma is a statistical term that refers to the standard deviation of a process. It is a measure of the amount of variation that is expected to occur in the output of the process. The 3 Sigma limit lines on a control chart define the range of variation that is acceptable for the process output. Any data points that fall outside of this range are considered to be outliers and may indicate a problem with the process.
Factors for Computing Control Chart Limits 3 Sigma
There are several factors that are taken into account when computing the control chart limits for 3 Sigma. These include:
- The size of the sample
- The standard deviation of the process
- The mean of the process output
- The type of control chart being used
- The desired level of statistical significance
The size of the sample is an important factor in computing the control chart limits. A larger sample size will result in tighter control limits, while a smaller sample size will result in wider control limits. The standard deviation of the process is also an important factor. A process with a higher standard deviation will have wider control limits, while a process with a lower standard deviation will have tighter control limits.
The mean of the process output is used to calculate the central line of the control chart. The central line represents the average value of the process output, and is used to monitor changes in the process over time. The type of control chart being used is also an important factor. Different types of control charts have different formulas for computing the control limits.
The desired level of statistical significance is another factor that is taken into account when computing the control chart limits. A higher level of statistical significance will result in tighter control limits, while a lower level of statistical significance will result in wider control limits.
Conclusion
The factors for computing control chart limits 3 Sigma are important to understand when implementing statistical process control. By taking these factors into account, you can ensure that your control charts are accurate and effective in identifying changes in your process over time. By monitoring your process output with control charts, you can make adjustments to your process to improve quality and efficiency.