Statistical Process Control (SPC) Resource Center



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Statistical Process Control (SPC) Resource Center

What You Need to Know About Statistical Process Control (SPC)

Statistical Process Control, or SPC for short, has been around since the 1920s although it didn't really gain widespread use in industry until the 1980s.  Many people are immediately turned off of SPC just because it has "statistical" in its name.  However, by simply understanding a few basic concepts of variation (why things are not ALWAYS made exactly the same) you will be able to leverage the concepts of SPC to monitor and control your manufacturing processes. 

Variation:  The Heart of SPC

  • Variation exists in everything
  • When we’re manufacturing products with customers that expect and demand high quality and consistency in our goods, variation can become a big problem.
  • Too much variation leads to rework, scrap, or customer problems.
  • A perfect process would be one with no variation. They don’t exist.
  • As the variation in our processes is reduced, the output of our processes will be improved.
  • That’s our goal with SPC-to reduce the variation in our processes and then monitor the process to make sure the variation doesn’t increase.

Our Statistical Process Control (SPC) Resource Center has lots of helpful information for people just learning about SPC as well as some interesting information that folks who have been using SPC for years should find interesting.

Basic SPC Resources

Advanced SPC Resources

Statistical Process Control Checklists and Forms

Many of these forms can be downloaded as Excel Spreadsheets or Word Docs

Formulas and Tables Used for SPC

Variable Control Chart Formats

Which is better?  In-Spec or In-Control?

Is there a difference between being in-control and in-spec? Yes there is, and it is a big difference. You can be in-spec but not in-control. And you can be in-control but not in-spec.

So, if you can have only one, which is better - being in-spec or in-control? Some may say “in-spec of course.” But unless the spec is very generous and forgiving, you will always be better off with a process that is in-control, but not completely in-spec. Obviously neither is the ideal situation - but there is a fundamental problem with a process that is in-spec, but not in-control. The problem is that you never know from one minute to the next if it will go out-of-spec. This means that you must inspect every part or product that is made - otherwise, how will you know that the product is still in-spec?

So, what is the advantage of a process that is in-control but not in-spec? Let's assume that at least some of the product being made by this in-control process is in-spec. Given that some of the process output is in-spec and the process is in-control, we can actually statistically calculate how much of the product will be out-of-spec.

Of course, the goal is to have a process that is both in-control and in-spec - that is what we call a capable and centered process. What if you have a process that is in-control, but not in-spec? By using SPC, root cause analysis, and some common sense, an in-control process can usually be brought in-spec.

How do you know if your processes are in-control? A good first step to take is to create a histogram of your data and then analyze the pattern of variation to identify possible reasons for the pattern. A control chart is really just an extension of a histogram. Not only does it show you the pattern of variation, but it plots that pattern over time.










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