The X bar chart controls limits that are derived from the R bar (average range) values.To correctly interpret an X bar R chart, always examine the R chart first.How to Interpret the X Bar R Control Charts When the collected data is continuous (ie Length, Weight), etc.The X Bar S Control chart is to be considered when the subgroup size is more than 10.An X bar R chart is for a subgroup size of more than one (for an I-MR chart the subgroup size is one only), and generally, it is used when rationally collecting measurements in a subgroup size between two and ten observations.When the data is assumed to be normally distributed.An X bar R chart will help to identify the process variation over time Even a very stable process may have some minor variations, which will cause the process instability.

$6 x tables chart$

This monitors the spread of the process over time. R-chart: The range of the process over time from subgroups values. The control limits on the X-Bar bring the sample’s mean and center into consideration. X-bar chart: The mean or average change in a process over time from subgroup values. The cumulative sum ( CUSUM) and the exponentially weighted moving average ( EWMA) charts also monitor the mean of the process, but the basic difference is unlike the X bar chart, they consider the previous value means at each point. These combination charts help to understand the stability of processes and also detect the presence of special cause variation. It is actually two plots to monitor the process mean and the process variation over time and is an example of statistical process control. You can also use them to collect data from subgroups at set time periods. X bar R chart is used to monitor the process performance of continuous data. Selection of the appropriate control chart is very important in control chart mapping, otherwise, you will end up with inaccurate control limits for the data. X Bar R charts are the widely used control chart for variable data to examine the process stability in many industries (like Hospital patients’ blood pressure over time, customer call handle times, length of a part in a production process, etc).