What is a U-Chart?

The attribute chart is also known as a control u-chart or defect per-unit chart. The chart is used to monitor data counts when the sample size exceeds one. The u chart can track the average number per unit of defects, whether there is a single defect type or multiple types. It assumes that the data are similar to the Poisson distribution.

The number of defects in a single unit or lot is shown on the y axis. The centerline (u), is the number of defects divided by the number of items inspected in a sampling.

Selecting Control U-Chart

The Control Chart can be used to track the evolution of a process. The control chart has three lines: a central line representing the average, a top line for upper control limits, and a bottom line for lower control limits. The control limits are within +-3s of the centerline.

Control charts mapping is not complete without a suitable control table. Otherwise, the control limits will be inaccurate.

X- and R-charts can be used to represent measurable quantities, such as weight, height, and length. Attribute Control Charts are for attribute data. The data used to count the number or defects per unit. The number of tubes that failed in a shop, for example. For attributes, unlike variable charts, there is only one chart.

When and why do you use a U-Chart?

The u chart is a quality control chart that monitors the number of defects in a unit.

Use a U chart to monitor stability of processes over time, and the impact of process improvements before and after. The u chart is used to monitor process stability over time and track the effects of before and after improvements. It calculates control limits using the Poisson Distribution.

There are four types of control charts for attribute data. p charts show the percentage of defective products, while np charts are for the total number of defectives. The c chart is the number of defectives, and the U chart is the average number per unit.

How to Create a U-Chart

  • Calculate the size of subgroup. The subgroup must be large enough to fit on the c chart. Otherwise, the control limits estimated using the data may not be accurate.
  • Count the defects on each unit.
  • Calculate the u-value for each lot. u= number defects per lot/lot size.
  • Calculate centreline u= total defects / total samples =Sc/Sn.
  • Calculate the lower control limit (LCL) and upper control limit. The control limits will vary between sample intervals if the sample sizes are not equal.
  • The graph should be plotted with lots on x-axis and the number of defects on y-axis. Draw the centerline and the UCL and LCL. These limits can be used to track the number of defects in the future.
  • Interpret the data to determine if the process is under control.