On the left side if you see this is the Pareto chart which we plotted earlier and based on that we concluded 2
that working on loose caps and wrong labels if we remove these two problems 72 percent problems will 3
be resolved but once we split that in two different categories, different types of bottles 300 ml. 4
bottle at the top, 500 ml. bottle in the middle and 1000 ml. bottles 5
at the bottom. 6
So now if you look at the chart you'll see a different trend. 7
You see the loose caps which you saw as a 50 percent problem if in the combined one loose caps was contributing 8
to 50 percent of the problems. 9
But if you look at 1000 ml. bottles there the loose cap is contributing to more than 80 percent 10
of the problems. 11
That means the problem of loose cap is more prominent in that particular type of bottles that type of 12
machine might be giving that problem. 13
So the machine which is producing the caps for 1000 ml. bottles that might be a problem. 14
So no your focused has changed rather than looking at the big picture. 15
Now you are looking at the focus thing. 16
And if you see that 300 ml. bottles instead of loose caps wrong 17
label is a big problem there. 18
So maybe now what you need to do is you need to check the labeling machine for that 300 ml. bottles. 19
You need to look at the loose caps problems in 500 ml. and 1000 ml. bottles. 20
So that's how you seggregate data. 21
You break data into small pieces. 22
If your data is coming from multiple sources. 23
So with this we completed Seven Basic Quality Tools. Learn these quality tools and see where you can implement 24
that. 25
I'm sure many of you would have already implemented one or many of these tools in your processes 26
earlier as well. 27
If you have done that share that in question and answer forum, so with this we complete our discussion on 28
Seven Basic Quality Tools.