It contains all individual measurements to judge the range and trends. We suppose that the data are normally distributed.įinally, the run chart is displayed. In the Q-Q plot we see that the data are close to the first bisector line. All the 4 tests conclude that the Hypothesis H0 of normal distribution can be accepted. In the next section the results of 4 different normality tests and a Q-Q plot are displayed. The group means values are always between the lower and upper control limits.įurther it is interesting to know, if the data follows a normal distribution and therefore the common rules for control charts and process capabilities can be applied. Summing up the conclusions made above, you can discover the different things suggested by the X bar control chart. The data has a good quality with respect to this issue. The next table contains the details for the special cause rules. Like the X-bar chart, the data of the R chart are always inside the control limits and no special causes are present.īoth control charts let us conclude that the process is “statistically under control”. The central line (CL), the lower (LCL) and upper (UCL) control limits, and the lower and upper zone limits for the B and C areas are displayed for each group. The following chart represent the X-bar control chart including the different control limits and central lines. The process is not capable according to the specifications. It’s interesting to see that the Cp indicator tells the process is "not adequate". Then, the process capability figures together with a chart and the X-bar control limits are displayed. The first results that are displayed are the estimated mean and the standard deviation. Interpret the results of the subgroup chart Then click on the OK button, the computations start. The given values for the USL, LSL and the target are entered. In the Options tab, you can activate the options Process capabilities to display the process key figures. In the General tab, select the chart type, choose the combination X-Bar – R chart, and the data. Setting up the dialog box for generating a subgroup chartĪfter launching XLSTAT, click the Statistical Process Control button on the ribbon and select subgroup charts. Note 3: If you have measurements as qualitative values (for instance ok, not ok, conform not conform), then use the control charts for attributes.ĭuring this tutorial an X-bar chart together with an R chart are generated. Note 2: If you have only one measurement for each point in time, then please use the control charts for individuals. Note 1: If you want to investigate smaller mean shifts, then you can also use CUSUM group charts which are often preferred in comparison to the subgroup control charts, because they can detect smaller mean shifts. The S chart draws the standard deviation of the process and the S² chart draws the variance (which is the square of the standard deviation).
R: An R chart (Range diagram) is useful to analyze the variability of the production.Mean shifts are easily visible in the diagrams. The subgroup charts tool offers you the following chart types alone or in combination: - X bar: An X bar chart is useful to follow the mean of a production process. There is a variety of different control charts that can be used for different aims. The control charts are an efficient method to decide if a process is statistically under control or not. The data are from and correspond to 25 inspections each having 5 measurements of a production process. Dataset for the analysis of a subgroup chart
#XBAR CHART IN EXCEL HOW TO#
This tutorial shows how to compute and interpret a subgroup control chart on quantitative data in Excel using XLSTAT software.
0 kommentar(er)
