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A9. Pareto Chart and the 80-20 Rule
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hi there we are now on the third
graphical analysis tool that we will
cover inside your Lean Six Sigma yellow
belt curriculum this time we will have
Pareto chart Pareto chart is mainly used
for priorities Ishod but let's look into
the details for us to better understand
how to use this new Pareto chart is a
set of bar charts where the bars are
arranged in descending order of
magnitude the bars may represent defect
categories locations departments and
others the problem-solving tool that
involves ranking of potential problem
areas or sources of variation according
to their contribution to Aust or total
variation typically 80% of the effect
comes from the 20% of the possible causes
causes
meaning 80% of the problem has accounted
to 20% of the causes or the factors so
efforts are best spent on this vital few
causes temporarily ignoring the trivial
many causes as said earlier it is a
prioritization tool now we're looking
for 80% of the problem which is
accounted to 20% of this factors let's
say you have 10 possible root causes
probably two or three among those 10
root causes is contributing around 80%
of the problem so you might want to
focus your energy in your efforts on
solving those problems that we call
vital view this is most commonly used
for a prioritization of resources and
also for validation of root causes now
let's study the anatomy of a Pareto
chart as you can see here this is the
category on the x-axis and this contains
the bar chart the data which is arranged
in descending order containing the
frequency of the categories and this one
is the cumulative line cumulative
percentage line meaning we are adding up
the contribution of this one to get this
point and this one and this one to get
this point this one this one and this
one to get this point
so on and so forth until it reaches the
100% summation of contribution so we're
finding the 80% of cumulative
contribution of the factors that is
being presented here so let's practice
Pareto chart using it is study about
floss pin floss a quality engineer for
an automotive supply company wants to
decrease the number of car door panels
that are rejected because of paint flaws
the engineer wants to determine whether
a relationship exists between the type
of paint floss and the ship during which
the door panels are mean but in this
case we will use Pareto chart to
determine what particular type of paint
flow is affecting the operations now
let's go to the worksheet and then let's
click flow our data is represented by
log data meaning there is a lock for one
scratch one scratch pill deal not
summarized so you don't have to worry
just copy it and go to Minitab create
another new worksheet and then you can
close this paste your data so you have a
data that that's in-text okay now we
want to go to Pareto chart so click that
and then find quality tools then you
will see para to chart on the second level
level
click para to child in a Pareto chart
you will be asked to provide at least
the number of defects or attribute data
and the frequency now because we don't
have any frequency so you can see here
if we click this field there will be no
data that can be assigned to this but if
you can click this one there will be the
flaws so you only have to do is double
left-click floss okay now there is an
option here that will ask you if there
are too many factors that are available
let's say 50 but the other factors don't
have any value that is significant
can actually combine them into the 95
percent remaining cumulative percentage
or if you don't want to do that just
click don't combine visually we click
combine so that we can consolidate those
none significant factors so click OK
then there is your palette a chart by Flo
Flo
so let's study the output palette to
chart again this axis talks about the
frequency of problems this is the
cumulative percentage line and this axis
talks about the categories of the
problem we have ill scratch other and
smudge because we only have four
categories then we don't need the other
consolidated factor here ok so let's
focus on the numbers we have 15 for pill
13 for scratch 6 for other and smudge 6
so we have here the individual
percentage contribution and here is the
cumulative percentage contribution so 37
bring down 37 here 37 plus 32 0.5 will
give you 70 70 plus 15 will give you 85
and 85 plus 15 will give you 100 now
this is the cumulative percentage using
Pareto chart we are asked to determine
the 80 percent of contribution that is
accounted to 20 percent of the factors
in Pareto chart analysis we can use
three possible algorithms or heuristics
as to decide which are the vital few
factors first we can check on the
cumulative percentage and look for the
cumulative percentage that is near 80
percent so for this case we have 85
maybe we have 85 therefore we can say
that the vital few factor includes till
scratch and other okay but as you can
see if we will use this for
prioritization it's a little bit weird
because 3 out of 4 has been
now if you will look into the cumulative
line if you will look closely to this
there is what we call the breaking point
here they the breaking point
it breaks the tone of your cumulative
line just like what happened here
meaning even the closest to 80 is 85
here you have to consider the breaking
point here it tells you that inside out
including this one the other you have to
stop here on pill and scratch because it
gives you the idea of the majority of
the problem surrounded to minority so
for you to be able to satisfy the rule
of thumb or the arbitrary points that is
being given to us when you use Pareto
chart analysis so far now we will focus
on this pill and scratch as are vital
few causes it so happened that we have
the breaking point that is why we
haven't chosen 85 pass the start of our
vital view so when we have this you will
refer to this and then get whichever is
in close to the left so that is scratch
and then pill okay so that is how you
prioritize and how you use Pareto chart
for prioritization purposes
now let's look at another example we
have a clothing manufacturer traveler
number and type of defects in a line of
clothing so our source data could be
found including defect so let's go to
excel this one then you have to copy
this all of these columns and then we
have to create another worksheet and
then close this one okay okay we have to
copy paste now we will be doing another
set of Pareto charts so we have to go to
stat let then quality tools we have
Pareto chart here you have to erase
floss okay so we are asked to where is
the data of defects or attribute data in
the defect categories is in c1
so you have to double-click see one now
we are asked where are the frequencies
so we have the count of each defects on
c2 so we have to click see two and down
then choose okay now we have our title
chart scroll down little okay now let's
focus on the categories we have each
count here the data is here the
percentage and the cumulative percentage
we want to understand how we can
prioritize the problem-solving
initiative therefore you have to figure
out the vital few causes we have to find
on the cumulative percentage a
percentage that is near 80 so we found
out that it's eighty two point five
eighty two point five so that's third
one two three
meaning the vital few causes include
missing button stitching errors in loose
thread okay
we don't have any clear breaking point
here so we have to use another method so
eighty two point five now we can use the
method that is by tracing on the
cumulative percentage line so on the
cumulative percentage line you have to
pick 80 and then chase it to the left
until it reaches or it touches the
cumulative percentage line when it
intersects with document the percentage
line trapped it down to what particular
causes will it fall it fell on loose
trail so our right of yukos's now is
missing but on stitching errors in loose
thread meaning eighty percent of the
problems on to almost 20% of the causes
or lesser so this is how you use Pareto
chart for your prioritization activities
there are cases that frequency is not
enough for prioritization let's see what
if those who has higher frequency only
reflects less cost to the organization
and those who have smaller frequency has
higher causing back into the
organization so this is where
the value of this particular people here
will come into the picture as you can
see the defect categories provided as
well as the heart are this is the usual
data table that we have for a Pareto
chart but in case that we want to check
the cost contribution then you have to
put cost per accordance on the third
goal loop and then get the product of
count times cost that is 217 times point
17 which will give you 36 point 89 and
then you reach 180 1.89 for hemming
errors okay so this is now total cost
rather than frequency now let's create
another control chart so if you want to
rerun a function you just have to click
we just have to hold ctrl and press E
and then the last dialog box will appear
so let's replace count this time we want
to check the Pareto effect using total
cost that is c4 so you have to replace
count by c4 and then you just have to
click OK now we have this now what do we
see we have a different type of vital
view now we have a different set of
vital fuel now now if we want to have a
side-by-side comparison we just have to
click this chart and then click this
drop down button and then click layout
tool let's reduce the number of columns
to 1 and let's get this chart okay so we
now have two charts here and then finish
now we have two charts this is the first
chart that we did and this is the second
chart that we need comparing them we
have different sets now of vital view we
will based on frequencies the vital few
are missing but on stitching errors in
whose thread but if we will use total
cost it is different now we have fabric
floss hemming error and stitching errors
now using that particular example we
have seen the effect of combining
frequency and cost
now in actual application you have to be
very careful in doing Pareto chart of
course is a critical component to what
you are doing so this is how you use for
at a chart in analyzing and prioritizing
your problem categories or your sources
of problem later on when you do your
case study you can also use this
whenever you want to prioritize your
list of potential root causes now when
using Pareto chart there are things to
consider data collected during a short
period of time specially from an
unstable process may lead to incorrect
conclusions because the data may not be
reliable you may get a misleading idea
of the distribution of defects and
causes when the process is not in
control the causes may be unstable at
the vital few problems may change from
week to week short periods of time may
not be representative of your process as
a whole so before you get the data we
have to check first the process
stability so for you to have a more
clear picture of the problem now if you
are dealing with data collected during
long periods of time there can be
changes examine the data for
certification are changes in the problem
distribution over time if there has been
a change then you move that data and
start a new choose categories carefully
if your initial predator analysis does
that yield useful results that is you
cannot see any potato child effect that
would help you then rerun it and ensure
that your categories are meaningful and
that your other category is not too
large this is the combined category
because if that's the case maybe there
is something that is wrong with the data
collection or the analysis itself choose
weighing criteria carefully for example
we use cost per gear cost me be a more
useful measure for prioritization the
number of occurrences
especially when the cost of various
defects differ concentrating on the
problems with the highest frequency
should decrease the total number of
items needing rework concentrating on
the problems with the highest score
should increase the financial benefits
of the improvement so you have the
balance between the two there are always
work around and just have to figure out
what are those for you to find the
balance last the goal of a Pareto
analysis is to obtain maximum reward
from the quality efforts but that
doesn't mean that small this whole
problem should be ignored until the
larger problems are so so this is by
applying quick Queens so that during the
analysis period until we are reading the
major improvements to be done we are
doing something for us to improve little
by little so that our tips that you have
to consider when you're using Pareto chart
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