Last Updated on 13 September 2023
Control charts, also known as Shewhart charts or process-behavior charts, serve as a powerful tool to determine whether a process is in a state of control. By plotting data about your process along with upper and lower control limits, you can visualize and analyze variations, helping you distinguish between common-cause and special-cause variations.
Why are Control Charts Important?
Control charts are integral in a Six Sigma project for many reasons:
- They provide a simple and efficient way of analyzing and interpreting the performance of your process over time.
- They enable you to forecast your process performance, helping to identify trends or shifts before causing significant damage.
- They can help you identify root causes of problems in a process, speeding up your improvement efforts.
How To Use a Control Chart?
Creating a control chart can be broken down into four steps:
- Choose the appropriate control chart for your data: Different charts serve different types of data. Some common types include the X-Bar and R-Charts (for continuous data) and P-charts (for attribute data).
- Gather Data: Collect data from your process. While the control chart type will determine the specific data needed, most will require measurements over time.
- Calculate Control Limits and Plot the Data: Calculate your upper and lower control limits and then plot your collected data, average, and control limits on the chart.
- Analyze the Chart: Look for patterns, trends, or points outside the control limits. These can suggest your process is out of control and help identify key areas to start investigating.
Establishing a control chart isn’t a one-time task. Instead, it’s a continuous monitoring tool. The nature of data in Six Sigma projects isn’t static and events like process improvements may affect your control limits, and thus, require a recalculation.