To err is human, but to really mess things up you need a statistician.

Have you ever met people who “do” statistical process control (SPC) only to get some screwy-looking control chart, and then text: OMG I H8 SPC! (If you don’t understand that, ask your nine-year-old child or grandchild.)

Last month we saw how it is not a failure of SPC, but rather an EBKAC (error between keyboard and chair). As I wrote in my last article, “Why Doesn't SPC Work?” perhaps they are not doing the measurement system analysis first, or perhaps autocorrelation in a continuous process. But you batch process folks are not off the hook, which is what this month’s article is about.

• spc
• statistical process control

The chart isn't strange, it's just misunderstood.

Over the past couple of articles, we have explored how an incomplete understanding of how SPC limits are calculated can lead to constructing control charts that look strange.  But using some of the things I mentioned, hopefully you can see that these “strange” control charts actually reveal quite interesting information about what is going on (and what to do about it).  In the last article I left you with a weird looking control chart to see if you could figure out what was going on in the process.  Instead of throwing out the chart and concluding that “SPC doesn’t work here,” let’s take a look at that and see what we could have learned about the process.

• spc
• statistical process control

Does this data make my shape look funny?

If you have been following my articles over the last few months, you have seen that even though statistical process control (SPC) charts are very powerful tools for examining a process, it turns out that there are a lot of ways to mess up SPC. This month, I am going to finish up with a few more things to watch out for as you use them, so you never have to ask, “Why doesn’t SPC work here?”

• spc
• statistical process control

Oh, the perils of mastering Six Sigma

I'm not saying that the following apply to you... really. But, you might be a Black Belt if...

• six sigma
• humor

'Cause I’m a nice guy, I’m going to give you articles that explain the basics of MSA.

You know how sometimes you think everyone knows a secret that they haven’t let you in on? Well, I had the opposite happen to me the other day. I assumed everyone knew the purpose for measurement system analysis (MSA), a.k.a. gauge repeatability and reproducibility; but I found out that a number of people have a completely mistaken impression of what they are for, much less how to do them correctly. So I thought I would give away, (free of charge) articles that explain the basics of MSA, as well as a cool MSA spreadsheet to help you learn how to do them, just because that’s the kind of guy I am. Selfless. And humble. Yep.

• measurement system analysis
• gauge
• gauge R&R
• potential study

Determining sources of variations

if you can’t trust your measurement system, you can’t do anything with the data it generates. Last month, in “ Letting You In On a Little Secret,” we talked about the purpose of measurement system analysis (MSA) and I gave you a neat spreadsheet that will do MSA for you, as well as some data (repeated after the jump) from the gauge you want to buy, the Hard-A-Tron. I also left you with a mysterious statement that this study was trickier than it appeared. This month I’ll start off answering a question I received, and then we will see how well the Hard-A-Tron did—and what mysterious thing was going on in the data. After that, if you are good, I’ll give you another set of data to further test a measurement device.

• measurement system analysis
• gauge
• gauge R&R