Correct control chart selection is a critical part of creating a control chart. If the wrong control chart is selected, the control limits will not be correct for the data. The type of control chart required is determined by the type of data to be plotted and the format in which it is collected. Data collected is either in variables or attributes format, and the amount of data contained in each sample (subgroup) collected is specified.
Variables data is defined as a measurement such as height, weight, time, or length. Monetary values are also variables data. Generally, a measuring device such as a weighing scale, vernier, or clock produces this data. Another characteristic of variables data is that it can contain decimal places e.g. 3.4, 8.2.
Attributes data is defined as a count such as the number of employees, the number of errors, the number of defective products, or the number of phone calls. A standard is set, and then an assessment is made to establish if the standard has been met. The number of times the standard is either met or not is the count. Attributes data never contains decimal places when it is collected, it is always whole numbers, e.g. 2, 15.
Sample or subgroup size is defined as the amount of data collected at one time. This is best explained through examples.
- When assessing the temperature in a vat of liquid, the reading is measured once hourly; therefore the sample size is one per hour.
- When measuring the height of parts, a sample of five parts is taken and measured every 15 minutes; therefore the sample size is five.
- When checking the number of phone calls that ring more than three times before being answered, the sample size is the total number of phone calls received, which will vary.
- When checking 10 invoices per day for errors, the sample size is 10.
Once the type of data and the sample size are known, the correct control chart can be selected. Use the following “Control chart selection flow chart” to choose the most appropriate chart.