9 hours 53 minutes
Hi, guys. Welcome back. I'm Katherine MacGyver, and this is your lean six sigma green belt. So today we're gonna pick up the work that we have started on our control charts. So in our last module, we went over X bar. Are and this model, we're gonna go over our X bar,
m r charts. I mean, I want you to be able to understand the difference on the data required for an expert in arm.
So when we use an expert m r, compared to an expert are asked to do with moving range, so expire are is going to be your staple control chart. It's gonna be what you're doing
the majority of your time when we're using M R. That indicates moving range. What we're doing with that is is comparing batches. So this is going to be much more relevant
towards your process improvement work than an expert, our chart. So you want to look at like your pilot in your current state. So using this when you're doing your piloting data collection, or before and after measurement.
So if you do an intervention both in your domestic or your PDC A. But this is still going to be the same rules as you would for an expert are. So you wanna have continuous data and you want it to be time study. So your ex axes is always going to be a measure of time.
These look very, very similar to your expert are so your top chart is going to be your X bar. You're looking at your averages. You have your upper and lower control limits. Your bottom chart is now going to be looking at your average of your average or how much does your average change
from point to point.
So if you look at your measure number s 15 kind of right in the middle, you will notice that from a average perspective, you go from below the average lying to above the average line. But if you're looking at your moving range, so what? The average of the changes you'll see that there's a very large gap.
Generally speaking, when you are reading X bar M R charts,
you will see some synchronicity between the movement. If you do not see similarity between the graphs, that's where you're going to want to do your root cause analysis and try and figure out what the change or the discrepancy is.
So for moving range, you are measuring the difference in the average, whereas in your range, your expert are
you are merely reporting the range of the data in that sample size. So for this one, you're going to see, I would argue that Data Point s 18. You'll notice that there's a little bit of a trend in your moving range of averages where they're starting to behave
closer together. I would say that there was probably an intervention there where we can see that are averages are getting closer together. So our standard deviation or variants
is decreasing. Where is if you look reflectively in the, uh, expire part? Your averages chart the upper one. You can see that there's still some bouncing around. So indicative, Lee, we're looking at possibly an intervention that maybe didn't necessarily stabilize as much as we originally thought.
Or stabilization may be a leading measure.
So something that happens before you started seeing it manifest in your data sets. So with your ex bar in art, you are going to be looking at moving ranges. This is for
batch comparison, so um, if you do before and after is really where this is best at where you have we measured it this way. Now we're measuring it that way.
You're looking for interventions and you're looking for changes in the averages. So that's the moving range with the top bar, Of course, being the same where you're looking at your average is in your actual average of those samples sets. So with that, you now know when you're going to use your expert are
and you know how to read it. So when you're looking at your lower chart, you know that you are looking
at the variance between averages as compared to the absolute value range.
So with that, we're actually going to move over to our next type of charts. We're going to go attributes chart, which will wrap up our control charts, and then we'll talk a little bit more about how to read them and how to identify special costs. So I will see you guys there
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