Control Chart (C Chart) - Explained

What is a Control Chart?

What is a Control Chart?

The Control Chart or C-chart is a type of control chart that is used in the monitoring of count-type data which is usually the total number of conformities per unit. It is also sometimes used in monitoring the sum of events occurring in a given unit of time.

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When to use a Control Chart

When the control chart indicates that the process under monitoring is not under control, the analysis derived from the chart can be useful in determining the sources of this variation because it might cause a degraded performance of the process. A stable process that operates outside the desired limits of specifications needs to be improved through an intentional effort aimed at understanding the causes of the current performance and improve it fundamentally. The control chart is among the seven basic tools used for quality control. Usually, the control charts are used in the time-series data, but they can also be used for data having logical comparability if there is a desire of comparing the samples that are all taken at the same time, although the type of chart to be used in this case needs a lot of consideration. Control charts constitute the following:

• The points which represent a statistic of the measurements of a quality characteristic type present in the samples that are taken at different times of the process.
• The mean of the statistic in the above step is calculated using all the samples, e.g., the mean of the ranges, the mean of the proportions, and the mean of the means.
• A center line which is drawn at the value of the mean of the statistic.
• The standard error of the statistic is also determined with the use of all the samples.
• The upper control limits and the lower control limits, also known as the natural process limits, indicate the threshold point at which the output of the process is sometimes considered unlikely statistically and then drawn at three standard errors that occur from the central line drawn.

Types of Control Chart

The control chart builder easily makes the control charts. When creating the chart, it is not necessary to know its name or structure. One only needs to select the column of variables that are to be charted and then drop them in their respective zones. Anytime a data column gets dragged into the workspace the control chart builder begins working on it creating an accurate and relevant chart based on the data type and sample size given. When the chart has been created, the required changes in type, format or statistics of the chart can be made using the various menus and options.

Control Charts for Variables

These can be classified per the statistic of subgroup summary plotted on the chart.

X Chart, R Chart, S Chart

X-chart indicates subgroup averages, R chart shows subgroup ranges and the S chart displays the subgroup standard deviations. A specific analysis makes clear the process mean and its variability together with a mean chart aligned above its corresponding S- or R- chart for the characteristics of quality to be measured on a continuous scale.

Individual Measurement Charts

These are used to display the measurements individually although they are only appropriate in use at places where only one measurement is made available for every sample or subgroup. When the individual measurements are changed, then the chart also displays above the corresponding moving range chart to it. These moving range charts display the ranges in the movement of two successive measurements.

Pre-summarize Charts

In case data contains repetitive measurements of the same unit process, they can be combined into one measurement for the unit. However, this is only recommended when the data contains repetitive measurements for every measurement unit or process. These charts summarize the process columns into standard deviations based on the sample size or the chosen label of the sample and then chart the summarized data based on the selected options in the window.

Levey Jennings Charts

These show a mean process that is based on a long term sigma with control limits. These control limits are placed in such a way that the distance between them and the center line is 3s'. These charts' standard deviation s' is calculated similarly to the standard deviation in the distribution platform.