In
this Issue
Using
Blank Rows to Make- Comparisons
Did you know
that if you add a blank row in your data before you run a control chart
macro it will calculate two different sets of control limits? One set
will be calculated using the data before the blank row and the
second set will be calculated using the data after the blank
row.
This functionality
is most commonly used to show a process change on a control chart.
However, many customers use it to compare two different processes
side by side. If you are in healthcare, you could compare data for
several different doctors, hospitals, floors, etc. If you are in manufacturing,
you could compare data from different machines, lots, batches, etc.
This functionality is illustrated in the following case study which
uses Dr. Sophronia Ward's Brain Teaser column in
the November 2005 issue of Quality Magazine.
Case
Study - Comparing Data from Different Machines
To read the complete November 2005 Brain Teaser in Quality Magazine
go to "Yield
Confusion"
Background
A production superintendent has 3 machines that polish chrome parts.
One of his customers has asked that he include a control chart for the
yield of their chrome parts to accompany each shipment. He has decided
to construct a control chart using the combined data from all three
machines even though the parts sent to this customer are only produced
on machine 1.
You can download the data for this example at: http://www.qimacros.com/free-excel-tips/yielddata.xls.
What does a control chart run on the combined data tell you? To determine
this, select the data in the Combined Yield column and run an XmR chart.
Note: The "Combined Yield" data in Dr. Ward's case
study does not represent the average of the yields from the three machines.
This is probably due to two reasons: The machine data is stated in percentages,
not actual yields, and the production on each machine varies from the
others. As a result, an XmR chart is run on the Combined Yield data
instead of an XbarR chart run on the data of the three machines.
The control chart shows an average combined yield of 89.13 with no
unstable points or conditions.
What problems might be encountered by using the combined data?
The problem with running this analysis on combined data is that problems
with each individual machine become invisible. High and low values between
machines offset each other and "average out". In this example,
the problem is magnified since the customer only received parts from
machine 1.
Since the parts are created using three different machines, the data
for each machine should be analyzed separately and compared to the other
two machines. There are several ways to do this using the QI Macros.
1. Run separate XmR charts on each set of
data.
This will give you the average, UCL and LCL values for each data set
but it is hard to see differences between the three machines.
2. Use the blank row function in the QI Macros
to show data for these machines side by side on the same chart. To do
this you will first need to reorganize your data. Use Excel's cut and
paste functions to move the machine 2 and machine 3 data below the machine
1 data in the same column. Leave a blank row between the data for each
machine.
Now select the data and run an XmR chart. Use the text box tool to
label the data for each machine.
These side by side charts make it much easier to compare machines.
You can easily see that the average yield for machine 3 is lower than
machines 1 and 2. You can also tell how much wider the control limits
are for machine 3. This means there is much more variation in the yields
for machine 3.
3. You can also use the Box and Whisker Chart
to compare the machines side by side.
To run a Box and Whisker Chart, the data for each machine must be in
a separate column. Select the data for all 3 machines and then select
Box and Whisker from the QI Macros pull down menu.
Here's
the Point
If you are analyzing data in the aggregate, don't stop there. Break
it apart by department, location, machine, doctor, teller, programmer,
etc. You'll be surprised at what you learn and you'll be more likely
to find the 4% of the problem that will deliver 50% of the benefits.
Remember you've got to drill down to find the hidden goldmine in your
business.
If you are looking for manufacturing case studies, a great resource
is Dr. Sophronia Ward's Brain Teaser column in Quality Magazine. You
can view back issues on the Quality
Magazine website.
If you need help analyzing your data, we offer data analysis services
via email. Just send us your data and a brief explanation of your process
and suspected problem. We will send you a quote to analyze your data
and create an actionable improvement project to focus on the 4% of your
process that causes 50% of the lost profit. Email your data to knowwareman@qimacros.com.
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for this series tell your friends to send an email to qimacros@aweber.com
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