SPC FAQs

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What control chart should I use?

The latest version of the QI Macros has a control chart wizard which will select the right type of chart for you. If you have an older version of the QI Macros, you can buy an upgrade at qimacros.com/orderup.html. The right chart is based on the type of data, attribute (counted) or variable (measured), and the sample size. For attribute (i.e., integer or counted defects) data use np, p, c and u charts

• If you are counting defective items (e.g. incorrect orders)
  • use a np chart if the sample size is constant
  • use a p chart if the sample size varies
  If you are counting the number of defects (e.g. number of errors on an order)
  • use a c chart if the sample size is large or not available
  • use a u chart if the sample size varies
• If you are using a ratio of defects/period (e.g., patient falls/1000 patient days) - use the XmR chart
  

For variable or measured data (i.e., decimal) such as time, cost, length, weight, etc. use XMR, XbarR, and XbarS Charts

• If the sample size is one use an XMR chart If the sample size is 2-10 use an XbarR chart
• If the sample size is 11-25 use an XbarS chart
  

These rules are summarized and shown pictorially in our SPC Quick Reference Card and Control Chart article. The QI Macros pull down menu also contains a control chart selector to help you choose the right chart. If you still need more help understanding which chart to use you might consider:

• SPC Simplified 1 hour Training Video (item #267 - choose between Healthcare and Manufacturing and DVD).
  

Why are some lines and points red?

The QI Macros performs stability analysison your data and turns unstable points and conditions red. These red points should be investigated.

Why don't the UCL/LCL equal +3*Standard deviations?

Standard deviation only works for populations of "normal" data. Control charts use different formulas based on sample size and the type of distribution. For a more complete explanation see our formulas page.

Why can't I change the UCL and LCL

Control limits are calculated statistically from your raw data. They can't be specified. Don't confuse them with Specification limits which are provided by your customer.See these instructions to add a target or goal line to your control chart.

My Cp and Cpk are different from the QI Macros

You're probably using standard deviation (stdev) to calculate Cp and Cpk, not Sigma estimator (Rbar/d2).Stdev is used to calculate Pp and Ppk. Compare the QI Macros Pp and Ppk to your Cp and Cpk; they'll probably match. See our formulas at http://www.qimacros.com/formulas.htmlYou may have sorted your data which prevents the proper calculation of Cp and Cpk using Rbar.We also offer telephone coaching for $95 for 30 minutes. Call 888-468-1537 to schedule a time.

My Cp and Cpk look wrong

There are two possible problems:

1. You sorted your data before you ran a histogram. Cp and Cpk calculations include Rbar (the Average of the Ranges). If your sample is sorted, Rbar will be distorted and your Cp and Cpk will be incorrect. Solution run your histogram on unsorted data.
2. You may have an error in your data (e.g. .001 is .01).

We also offer telephone coaching for $95 for 30 minutes. Call 888-468-1537 to schedule a time.

My Cp and Cpk are wildly different from Pp and Ppk

If Cp and Cpk differ from Pp and Ppk by 0.5 or more, then one of three things may be the problem:

1. You sorted your data before you ran a histogram. Cp and Cpk calculations include Rbar (the Average of the Ranges). If your sample is sorted, Rbar will be distorted and your Cp and Cpk will be incorrect. Solution run your histogram on unsorted data.
2. Your process is unstable (e.g., trending upward or downward). Run a control chart on your data and eliminate any special causes of variation. Then return to capability analysis.
3. If you have several rows and columns of data, you may need to "flip" your data using copy then paste special transpose.

We recently created a whitepaper on histograms and capability analysis. It's $20. You can order and download it on our shopping cart.We also offer telephone coaching for $95 for 30 minutes. Call 888-468-1537 to schedule a time.

The GageRR chart says my system needs improvement

Yes it does. That is what the Gage RR is meant to do. If you don't think the results are correct then double check the way you input your data. For free articles on how to use and interpret the GageRR see our QI Macros Tips Articles.

My Gage RR results look wierd.

Many people input dummy data into the Gage RR to try it out and then wonder why the results look wierd. The answer is Garbage In Garbage Out. For free articles on how to use and interpret the GageRR see our QI Macros Tips Articles.

Why don't the percentages add up to 100%?

The Gage RR formulas were verified using AIAG Measurement Systems Analysis 3rd Edition. Per page 115 and 116 "The percent consumed by each factor will not equal 100%." To obtain a copy go to http://www.aiag.org/publications.

What are the formulas?

Click on a cell or move your cursor over many of the cells in the GageRR to read notes about the formulas.The Gage RR formulas were verified using AIAG Measurement Systems Analysis 3rd Edition. To obtain a copy go to http://www.aiag.org/publications.

Why are the sigma lines on my p, u, XbarS chart wavy instead of straight?

Varying sample sizes in p, u, and XbarS chart data will cause the sigma lines to be wavy. If you or your audience want straight lines on your u or p chart data, you can calculate a ratio (numerator/denominator) and graph the ratios using an XmR chart.

How do I run a chart for defects per 1000?

Create a new column in your Excel Spreadsheet. Create a formula = numerator/denominator*1000. Copy the formula down for all rows of your data. Select the cells in the formula column and run an XmR chart.