Different Methods of Using Control Chart Control chart is a graphical representation of process data over a time period. As per assignment helper, There are different methods of 
creating and using control charts. Most of the methods are similar, but control charts for variables are different from control charts for attributes. Some of them are discussed below – P-charts: This method is useful to create control charts when attributes are sampling that are classified as defective or non-defective. Under this method, limits of control charts are based on binomial distribution and calculated by using following equations. UCL = p + ?*? LCL = p – ?*? Where, p = Mean proportion ? = Number of standard deviates ? = Standard deviation of the sampling distribution.
R-charts: It is a type of process control chart that helps to track the range within the sample. Under this method, following steps are useful to create a control chart.
- Determine quality characteristic
- Take an adequate number of samples to establish a baseline.
- Choose the appropriate control chart
- Compute mean line and control limits (Breyfogle, 2003).
- Establish a location to display the control chart
- Interpret control chart
- Plot data on control charts
- Analyze results of each sample
Setting Range Chart Limit: Along with these, the control charts can construct or use by setting range limits. For example, if the average range of a process is 53 and sample size is 5 then control chart is created by determining the upper and lower control charts limits. This method is applicable when variables are used in sampling (Render, Stair & Hanna, 2009).
Interpreting Control Chart: The interpretation of control chart begins with the examination of range portion of a chart. To interpret the data of control chart, one should look for sign to indicate that process is not in statistical control. Along with this, it should also ensure that control limits including upper control limit and lower control limit randomly distributed about the mean or average of observation. In addition, it also requires that out-of-control situation, as well as potential causes of this situation, should be identified in order to effectively use control chart to monitor quality. To interpret control chart, it is also required to use the appropriate method according to sampling for constructing and using control chart in quality control.
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