What does it mean if a single data point appears above the upper specification limit on a control chart?
Control limits distinguish control charts from a simple line graph or run chart. They are like traffic lanes that help you determine if your process is stable or not. Control limits are calculated from your data. Control limit formulas are complex and differ depending on the type of data you have. Show
You can try and calculate control limits yourself, but ...
In a stable process: How do you calculate control limits?
Why are there so many formulas for sigma?The formula for sigma depends on the type of data you have:
Each type of data has its own distinct formula for sigma and, therefore, its own type of control chart.There are seven main types of control charts (c, p, u, np, individual moving range XmR, XbarR and XbarS.) Plus there are many more variations for special circumstances. As you might guess, this can get ugly. Here are some examples of control limit formulas:
p Chart formula
Individual Moving Range Chart formula
X bar R Chart formula * "Introduction to Statistical Quality Control," Douglas C. Montgomery * The secret formula to ignoring all other formulas. QI Macros SPC Software!QI Macros is an easy to use add-in for Excel that installs a new tab on Excel's toolbar.Just select your data and QI Macros does all of the calculations and draws the control chart for you. QI Macros calculations are tested and accurate. QI Macros built in code is smart enough to: FREE QI Macros 30-Day Trial QI Macros Also Makes it Easy to Update Control Limit CalculationsOnce you create a control chart using QI Macros, you can easily update the control limits using the QI Macros Chart Tools menu. To access the menu, you must be on a chart or on a chart embedded in a worksheet. Here's what you can do with the click of a button:There are also options to easily re-run stability analysis after changing data or control limit calculations. Why Choose QI Macros Control Chart Software for Excel?
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We often hear control limits and specification limits discussed as if they are interchangeable. But control limits and specification limits are completely different values and concepts. What is the relationship between control limits and specification limits? Usually there is no relationship whatsoever. Control limits are calculated from process data for a particular control chart. An X-bar chart and an Individual measurements chart will have different limits. Specification limits are chosen in numerous ways. They generally apply to the individual items being measured and appear on histograms, box plots, or probability plots. The table below contrasts control limits and specification limits:
Even using specification limit values on an Individuals chart leads to problems. Unless the specification and control limit values are identical, one of two errors occurs:
How about showing specifications on the control charts in addition to the control limits? The leading SPC solutions allow this, but it's generally not a good idea. Additional limits risk confusing customer demands with process behavior. The additional limits void the wonderful ability of control charts to give clear guidance. The only good use of specification limits on a control chart that I've seen is to make a point when the process is operating nowhere near the specifications. Concerning specifications appearing on an X-bar chart, the X-bar chart below illustrates the problem. The subgroup size is two, and the Target and Specifications (rather than Center Line and Control Limits) have been added to the chart. All of the subgroup averages (the "O"s) are within the specifications. But all of the measurements making up the subgroups (the "+"s) are outside the specifications. The items are all either too large or too small; but on the average they're just right! In summary, use only control limits on control charts; specification limits belong on histograms, box plots, and probability plots.
Info Center Collateral Types Quality Glossary Definition: Control chart Also called: Shewhart chart, statistical process control chart The control chart is a graph used to study how a process changes over time. Data are plotted in time order. A control chart always has a central line for the average, an upper line for the upper control limit, and a lower line for the lower control limit. These lines are determined from historical data. By comparing current data to these lines, you can draw conclusions about whether the process variation is consistent (in control) or is unpredictable (out of control, affected by special causes of variation). This versatile data collection and analysis tool can be used by a variety of industries and is considered one of the seven basic quality tools. Control charts for variable data are used in pairs. The top chart monitors the average, or the centering of the distribution of data from the process. The bottom chart monitors the range, or the width of the distribution. If your data were shots in target practice, the average is where the shots are clustering, and the range is how tightly they are clustered. Control charts for attribute data are used singly.
Control Chart Example When to Use a Control Chart
Basic Procedure
Create a control chartSee a sample control chart and create your own with the control chart template (Excel). Control Chart ResourcesYou can also search articles, case studies, and publications for control chart resources. BooksThe Quality Toolbox Innovative Control Charting Improving Healthcare With Control Charts Case StudiesUsing Control Charts In A Healthcare Setting (PDF) This teaching case study features characters, hospitals, and healthcare data that are all fictional. Upon use of the case study in classrooms or organizations, readers should be able to create a control chart and interpret its results, and identify situations that would be appropriate for control chart analysis. Quality Quandaries: Interpretation Of Signals From Runs Rules In Shewhart Control Charts (Quality Engineering) The example of Douwe Egberts, a Dutch tea and coffee manufacturer/distributor, demonstrates how run rules and a Shewhart control chart can be used as an effective statistical process control tool. ArticlesSpatial Control Charts For The Mean (Journal of Quality Technology) The properties of this control chart for the means of a spatial process are explored with simulated data and the method is illustrated with an example using ultrasonic technology to obtain nondestructive measurements of bottle thickness. A Robust Standard Deviation Control Chart (Technometrics) Most robust estimators in the literature are robust against either diffuse disturbances or localized disturbances but not both. The authors propose an intuitive algorithm that is robust against both types of disturbance and has better overall performance than existing estimators. VideosControl Chart Excerpted from The Quality Toolbox, ASQ Quality Press. |