In Analyze phase, they collected 20 sets of plate thickness samples with a subgroup size of 4. In a manufacturing industry the plate thickness is one of the important CTQ factor, during Measurement phase, project team performed the process capability study and identified that the process is not capable (less than 2 sigma). I will use a case study to make it easier to understand : When the collected data is in continuous (ie Length, Weight) etc. Xbar chart, the probability of having a point that is outside either the upper control limit or the lower control limit is 0.0013499.When the data is assumed to be normally distributed.To Collect measurements in subgroup size is between 2 and 10 observations.To identify the process variation over the time.In general, X - Bar Control Chart is used : Transcribed image text: 4.1 Use MINITAB, construct X-bar chart and R chart for the data in Hotel2 file (10 pts) Interpret the results (which are in the. This chart monitors the spread of the process over the time. R-chart: The range of the process over the time from subgroups values. The control limits on the X-Bar brings the sample’s mean and center into consideration. X-bar chart: The mean or average change in process over time from subgroup values. The same is true if your results are reported as a function of an independent capability study.X - Bar R Chart is a statistical process control tools that widely used to examine the process stability in many industries. If you are reporting the GR&R as a percent of the total tolerance you can still achieve a decent GR&R value, but caution must be taken because your sample of parts did not cover the entire tolerance of the specification. Ways to avoid this are to ensure that your sample parts represent the distribution of the process you are measuring. If you do not have points (> 50%) out of control on the X-bar chart your graph is telling you that you cannot distinguish one part from the other and that your part variation is too small. For the X-bar chart, there should be shift in the mean due to the fact that we are measuring a different part which is a special cause of variation. We would not expect a violation of the control on the range chart because the only variation in the system is measurement variation. From the average Range (R Bar) the upper and lower control limits for both the Range and Average chart are calculated. The range is based on measuring one part multiple times. Switching parts is a special cause of variation. The process we are reviewing is the measurement process. The X-bar chart should show many points out of control because there are special causes of variation not inherent to the process. Therefore, we expect to see the points plotted in the averages chart to be out of control. The additional element that is added into the equation now is part-to-part variation. So, the UCL and LCL of the Xbar chart are in fact the variation expected from the measuring process (people, device, process, environment). As I’m sure you realize the upper and lower control limits of the average chart are a function of the range chart. So, the control limits in the range chart are a function of the following elements: operator, measuring device, procedures, and environmental factors going on through the Gage R&R process. When these measures area assessed, via the control chart, and they are in control and random in nature we can claim a ‘stable’ measuring process and from the estimate of standard deviation, Rbar/d2, we can generate an estimate of the variability of the measurement process. When we set up the Gage R&R, specifically for the range section, we are taking multiple readings, by the same person, with the same measuring device, over a relatively short time frame. The range chart, providing insight into the concept of repeatability, ultimately becomes an estimate of the variability component contributed by the measurement process. In a Gage R&R the Xbar and R chart provide many facets for the analysis of the Measrement process.
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