U Chart Maker

You can easily create a U Chart online here! Simply copy your data into the table and select the measurements.

The U Chart will then be created for you online.

Create a U Chart online

In Statistical Process Control, a U Chart is a type of control chart used to monitor the count of defects or nonconformities in a process per unit of measurement when the sample size varies. It is particularly useful when the data being collected consists of discrete counts and the sample size for each observation is not constant.

How It Works:

• Data Collection: The U Chart collects data on the number of defects or nonconformities observed in each unit of measurement.
• Plotting the Chart: On the U Chart, the counts of defects or nonconformities are plotted over time or by sample number on the horizontal axis. Unlike the C Chart, where each data point represents a fixed sample size, the U Chart accommodates varying sample sizes.
• Center Line and Control Limits: A center line is drawn on the chart to represent the average or mean number of defects per unit of measurement. Upper and lower control limits are also calculated based on the variability of the defect counts and are typically set at a certain number of standard deviations from the center line.
• Interpreting the Chart: Similar to other control charts, when the defect counts fall within the control limits and show random variation around the center line, it indicates that the process is stable and under statistical control. Any data points falling outside the control limits or showing non-random patterns suggest that the process may be experiencing special causes of variation, necessitating further investigation and corrective action.

The U Chart app is commonly used in quality control and process improvement efforts. It is designed for use in manufacturing, healthcare, and service industries, helping users visualize and manage variations in defect rates over time. More specifically, it monitors the number of defects per unit of measurement, allowing organizations to identify trends, patterns, and potential issues in their processes. This enables teams to take appropriate actions to maintain quality standards and enhance overall process performance.