7 qc toools LEARN and KNOW how to BUILD IN EXCEL

7QC TOOLS

7 TOOLS used to CONTROL the QUALITY of the product

7QC TOOLS

1.) STRATIFICATION2.) CHECK SHEET/TELLY SHEET 3.) HISTOGRAM4.) PARETOGRAM5.) CAUSE AND EFFECT DIAGRAM6.) SCATTER DIAGRAM7.) CONTROL CHARTS

1). STRATIFICATION

• It simply mean the GROUPS of considerations.• Or give a GROUP NAME, to considerations, on

which study is based.

Before to study any process , you must have to make some GROUPS on which your study will depends.

like:- time, type, reason, machine, shift, person, effects…..etc

2.) CHECK SHEET/ TELLY SHEET

• A check sheet is a FORM/TABLE, on which data is recorded systematically. Like---below

DATE SHIFT OPERATOR DEFECTED PRODUCT

1st Sam 20mack 0arun 12





5/11/2013

6/11/2013

7/11/2013

8/11/2013

9/11/2013

Here, in this Form we are trying to find number of

Defected Product made by Operators in 1st shift of each

day.

You just have to build a FORM, with

taking GROUPS (stratification), on which you want to

make investigation.

Stratification

3 4 5 6 7 8 9 10 112 3 4 5 6 7 8 9 10

0

2

4

6

8

10HISTOGRAM

Lower limit

Upper limit

Trend line

It is used to observe that , how is the process going. Or we can say, use to predict future performance of a process. Any change in process. It is simply a bar chart, from which we get, info of the process- how its going, it is in limits or not.

3). HISTOGRAM

3 4 5 6 7 8 9 10 112 3 4 5 6 7 8 9 10

0

2

4

6

8

10

dia

3 4 5 6 7 8 9 10 112 3 4 5 6 7 8 9 10

0

2

4

6

8di

a

1 2 3 4 5 6 7 8 9 10 110 1 2 3 4 5 6 7 8 9 10

0

2

4

6

8

10

dia

3 4 5 6 7 8 9 10 11 12 13 14 152 3 4 5 6 7 8 9 10 11 12 13 14

0

2

4

6

8

dia

Process is varying all over in/out of range Process is Within Limits

Process is moving towards Upper Limit

Process is moving towards Lower Limit

Lower limit

Upper limit

Lower limit

Upper limit

Lowerlimit

Lowerlimit

Upper limit

Upper limit

Different Histograms showing different Processes

How to build HISTOGRAM in Excel.(with example)

1.) 1st we have to Study/Collect specifications like -diameter (Data) for 24 products.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24D DIA 6 5 7 10 9 8 4 7 5 6 7 7 8 6 8 7 5 7 8 6 7 7 8 8

2.) Calculate RANGE.RANGE= Maximum value - Minimum valueSo here , maximum value= 10, Minimum value = 4So RANGE = 10- 4 =6

3.) Now decide the NUMBER OF CELLS. Data Points Number of Cells

20 -50 6 51-100 7101-200 8201-500 9501-1000 10Over 1000 11-20

We have 24 data points , and it fall in 1st group ,

so- No of cells = 6

4.) Calculate the approximately cell width.Cell width= RANGE/ NO OF CELLS = 6/6 =1

5.) Round Off the cell width.If cell width come in a complicated manner, like 0.34, 0.89 or else , then round off it to , one you want, like : 0.50 or 1 or else.

Go to yellow block, type, =frequency( D1:D24, B1:B10), and press Enter. Then select yellow block and all sky blue blocks, press F2, and press CTRL , SHIFT, ENTER. ( frequency formula will get implement in all sky blue blocks as in yellow block )And you will get frequency of data values in each group, As in group (7 – 8) , frequency is 6.

6.) Now construct the Cell Groups with keep in mind cell width( cell width=1)

2 33 44 55 66 77 88 99 10

10 1111 12

Cell width=1

Cell width same for all cell groups =1

7.) Now find number of data values/ Frequencies in each Cell Group.You can do this manually , by counting itself or by using formula .(frequency formula) Mean how many values fall in each group.

A B Cfrequency

1 2 3 02 3 4 13 4 5 34 5 6 45 6 7 86 7 8 67 8 9 18 9 10 19 10 11 010 11 12 0

cell groups (D1:D24) values are on previous page)

8.) Now we got frequency data in each group, now we can build Histogram.

frequency data is our final data.

now select this data a build a bar chart. That’s it.

3 4 5 6 7 8 9 10 112 3 4 5 6 7 8 9 10

0

2

4

6

8

10

Dia (mm)

Freq

uenc

y

Group 4 - 5, show values from 4.1 to 5Group 5 - 6, show values from 5.1 to 6

So this rule for all groups.

Trend line – also give an visual idea of moving

process.

In short how to build histogram

1. Study / collect data.

2. Find Range.( range =max value - min value)

3. Find Number of cells.

4. Calculate Cell width ( cell width= range/no of cells)

5. Round off , if needed.

6. Create cell groups, using cell width

7. Find frequency.

8. Plot bar chart.

4). PARETOGRAM

Example- you have a high waste , and you have many causes for that, so you have to work, first on those causes, which are most responsible for the waste.

• By this we can separate , most important causes from less important causes for a problem.

So Paretogram help us to find these, most responsible causes for a problem.

So from this Paretogram, we got that by working on first 3 causes, we can reduce

waste up to 64%.

So first work on these causes, and after that go for other 10 causes, which are less

responsible, for waste generation (36%).

So paretogram, give us a clean view, of most important area, where we have to work first

to solve the current problem.

A B C D

Waste typeswaste in

kg percentage

cumulative percentage

1 cal wrinkle ply 400 26.83 26.8

2 roll end 320 21.46 48.3

3 /coat off 234 15.69 64.0

4 angle change 140 9.39 73.4

5 splice press 90 6.04 79.4

6 passenger short pices87 5.84 85.2

7 damaged bands 65 4.36 89.6

8 mechanical waste 60 4.02 93.6

9 bead wrap edges 45 3.02 96.6

10 scorchy 23 1.54 98.2

11 short piece 11 0.74 98.9

12 chaffer 9 0.60 99.5

13 passenger ply 7 0.47 100.0TOTAL 1491

How to build a Paretogram in Excel

A B C D

Waste typeswaste in

kg percentage

cumulative percentage

1 cal wrinkle ply 400 26.83 26.8

2 roll end 320 21.46 48.3

3 /coat off 234 15.69 64.0

4 angle change 140 9.39 73.4

5 splice press 90 6.04 79.4

6 passenger short pices87 5.84 85.2

7 damaged bands 65 4.36 89.6

8 mechanical waste 60 4.02 93.6

9 bead wrap edges 45 3.02 96.6

10 scorchy 23 1.54 98.2

11 short piece 11 0.74 98.9

12 chaffer 9 0.60 99.5

13 passenger ply 7 0.47 100.0TOTAL 1491

1.) Collect data For a problem. Example- waste problem, so collect what are causes, and how much waste is coming because of each cause. ((its down in table))2.) Sum Up(Total) Sum all wastes from all causes. ((its down in table)

3.) Calculate The Percentage of each individual Find individual percentage of waste by each cause contributing in all total waste.(Individual waste/total)*100 ((its down in table))

4.)Calculate the cumulative percentage. ( mean take 1st percentage, and add 1-by-1, all percentage to that) mean :- D1=C1,

D2=D1+C2,D3=D2+C3D4=D3+C4D5=D4+C5,D6=D5+C6,D7=D6+C7,D8=D7+C8,D9=D8+C9,D10=D9+C10,D11=D10+C11,D12=D11+C12,D13=D12+C13,

5.) That’s it now let build paretogram.

6.) Insert a bar chart ( taking data, B1:B13 and D1:D13) ( from previous page) you will get below chart.

0

100

200

300

400

waste (Kg)

cumulative %

0

100

200

300

400

waste (Kg)

cumulative %

7.) Now click on cumulative bars (Red bars), right click and go to change chart type, and select a line chart , and you will get below chart.

8.) Now select line chart (Red line), right click , go to format data series, and you got two option primary axis and secondary axis, click on secondary axis, and you will get below graph.

cal w

rinkle

ply

roll e

nd

/coat o

ff

angle c

hange

splic

e pre

ss

passenger s

hort pice

s

damaged b

ands

mech

anical w

aste

bead wra

p edges

scorc

hy

short

piece

chaffe

r

passenger p

ly0

100

200

300

400

0.020.040.060.080.0100.0120.0

paretogram

waste (Kg)cumulative %

9.) that’s it , now study this graph , and make some decisions about , on which area you have to work first, to solve a problem. ( like if you work on 1st cause – you can reduce waste up to 26 % if you work on 1st and 2nd causes – you can reduce waste up to 48% if you work on 1st ,2nd and 3rd causes – you can reduce waste up to 64 %)

So from 13 causes, if you work on first three causes you can reduce waste up to 64 %.

5). CAUSE AND EFFECT DIAGRAM

• It give us relationship between Effects and its Possible Causes with

M-approach- ( man, method, material, machine)

6). SCATTER DIAGRAM It is used to study relationship between two variables.

0 1 2 3 4 5 601234567

X-axis

Y-ax

is

+ve relationship (Y-increase as X-increase )

0 1 2 3 4 5 601234567

X-axis

Y-ax

is

-ve relationship (Y- decrease as X-increase )

0 1 2 3 4 5 6 701234567

X-axis

Y-ax

is

No -Relationship

Example

• Let we have a product , and we have to study its life cycle with respect to temperature.

temp life

40 2545 2350 2055 1660 1065 435 2030 1825 1520 12

10 20 30 40 50 60 700

5

10

15

20

25

30

TEMP (DEGREE CELSICUS)

LIFE

(YEA

RS)

CONCULSION- product has maximum life at 400 C, and after on increasing or decreasing of temperature , Life of product get decrease.

7). CONTROL CHARTS

• Control charts in itself a big topic.• Many Calculations.

Control charts are Trend Chards, for Analysis and Presentation of data.

Type of Control Charts

Variable

X and MR

chart

X and R chart

X and S chart

X and σ chart

defectivedefects

attribute

C - chart P - chartnP- chartU - chart

We will study here only these important charts

(X - bar) and R chart.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 154.9

55.15.25.35.45.5

X-bar Chart

X-barUCLLCLcenter line

1 2 3 4 5 6 7 8 9 10 11 12 13 14 150

0.20.40.60.8

1

R chartRUCLLCLcenter line

It Simply tell us where the process is going.Is the process under control ?Are we have to increase the no of inspections ?

Lets build it. But 1st learn below things . -- X bar ( average) -- X double bar (average of average) (its also center line of X-bar chart) R – Average of Range (its also center line for R-bar chart)

UCLR – upper control limit for R chartLCLR – lower control limit for R chartUCLX – upper control limit for X-bar chartLCLX – lower control limit for X-bar chart

UCLR = D4 x R

LCLR = D3 x R

UCLX = X + A2 R

LCLX = X - A2 R

Formulas for -- R chart

Lets take an example- in which we will took a lot from, running line, after every 30 minute for inspection of weight of product.

In each lot we take 5 samples.

In these formulas, we have constants, D4, D3, A2, values of these constants we will get from table 1.1 ( last slide)

1.) Collect data. ( as in figure below).

sample lot 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

sample 1 5.5 5 5.4 5.2 5.1 5.1 5.4 5.5 5 5 5.2 5.7 5.4 5.2 5.2sample 2 5.1 5 5 5.2 5 5.2 5 5.1 5 5.1 5.4 5 5 5.2 5sample 3 5 5 5.1 5.4 5 5 5 5 5.5 5.1 5 5.2 5.4 5 5sample 4 5.2 5.5 5.3 5.5 5.1 5.2 5.5 5.4 5.1 5 5.3 5.5 5.2 5 5.1sample 5 5.4 5.1 5.4 5.4 5.1 5.5 5 5.2 5.2 5 5.1 5.4 5.4 5.1 5.4

2.) Now Calculate the (average) and R(range) for each lot. (as in figure below)

= (5.5+5.1+5+5.2+5.4)/5=5.24

R (range)= max- min = 5.5 - 5

= 0.5

sample lot 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15


Average(X bar) 5.24 5.1 5.2 5.3 5.1 5.2 5.2 5.2 5.2 5.04 5.2 5.4 5.28 5.1 5.1Range(R ) 0.5 0.5 0.4 0.3 0.1 0.5 0.5 0.5 0.5 0.1 0.4 0.7 0.4 0.2 0.4

As like for lot 1.

3.) Now Calculate . (average of average for X) (as in figure below)

4.) Now Calculate . R ( average of Range) ( as in figure below)

sample lot 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15


Average(X bar) 5.24 5.1 5.2 5.3 5.1 5.2 5.2 5.2 5.2 5.04 5.2 5.4 5.28 5.1 5.1 5.19Range(R ) 0.5 0.5 0.4 0.3 0.1 0.5 0.5 0.5 0.5 0.1 0.4 0.7 0.4 0.2 0.4 0.4

average

R 0.4 5.19So,

5.) Now Calculate , limits. as below

=2.114 x 0.4 = 0.8456

= 0 x 0.4 = 0

=5.19 + 0.577x 0.4 = 5.420

=5.19 – 0.577x 0.4 = 4.969

UCLR = D4 x RLCLR = D3 x R UCLX = X + A2 RLCLX = X – A2 R

Find constants values From table 1.1 for 5 samples, in a lot. ( last slide)

D4 = 2.114D3 = 0A2 = 0.577

6.) Calculations are now over, so plot the graph.1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Average(X bar) 5.24 5.12 5.24 5.34 5.06 5.2 5.18 5.24 5.16 5.04 5.2 5.36 5.28 5.1 5.14

Range(R ) 0.5 0.5 0.4 0.3 0.1 0.5 0.5 0.5 0.5 0.1 0.4 0.7 0.4 0.2 0.4

UCLR = 0.8456LCLR = 0

UCLX = 5.420LCLX = 4.969

1 2 3 4 5 6 7 8 9 10 11 12 13 14 154.9

55.15.25.35.45.5

X-bar Chart

X-barUCLLCLcenter line

1 2 3 4 5 6 7 8 9 10 11 12 13 14 150

0.20.40.60.8

1

R chartRUCLLCLcenter line

R = 0.4

= 5.19

X-bar and MR chartWhen we can’t take multiple samples, in a lot. We use X-bar and MR chart.

Processes like- chemical process, where the cost of test is so high, that we can’t get, multiple samples.Here

UCL MR = MR x D4

LCLMR = MR x 0 = 0

UCL X = X + 3( MR / 1.13)LCLX = X – 3( MR / 1.13)Central line = X

MR = difference between the value and value immediately proceeding.

As we have only 1 sample in each lot, so mean n=1 , for X bar chart.

But for MR chart , as MR is comes out, by differencing two samples, mean in each lot we have 2 samples, mean n=2, for MR chart.

D4 = 3.267 , for 2 samples, for MR chart, from table 1.1 (last slide).

X MR MR1 5.52 5 -0.5 0.53 5.4 0.4 0.44 5.2 -0.2 0.25 5.1 -0.1 0.16 5.1 0 07 5.4 0.3 0.38 5.5 0.1 0.19 5 -0.5 0.510 5 0 011 5.2 0.2 0.212 5.7 0.5 0.513 5.4 -0.3 0.314 5.2 -0.2 0.215 5.2 0 0

AVERAGE 5.26 0.2357

Make all values of MR +ve IN TABLE

UCL MR = MR x D4 = 0.235 x 3.267 = 0.767

LCLMR = MR x 0 = 0.235 x 0 = 0

UCL X = X + 3( MR / 1.13) = 5.26 + 3(0.235 / 1.13)= 5.883

LCLX = X – 3( MR / 1.13) = 5.26 – 3(0.235 / 1.13)= 4.636Central line = X = 5.26Central line = MR = 0.235

X = 5.26MR = 0.235

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15-0.10.10.30.50.70.9

MR -chartMRLCLUCLcenter lineX MR

1 2 3 4 5 6 7 8 9 10 11 12 13 14 154

4.55

5.56

X-bar chartXLCLUCLcentral line

P-Chart (fraction defective)• Ratio of number of items rejected to the number of items inspected is

known as fraction defective.

Total Number of Defected Samples Total Number of Samples Inspected

P = UCL = P + 3 P( 1- P )/n

LCL = P - 3 P( 1- P )/n

Lets take an example of studying n=100 samples each day for 10 days.

days (100 sample each day) 1 2 3 4 5 6 7 8 9 10

No. of defected items 11 10 12 15 7 11 10 14 10 10 110

fraction defective each day 0.11 0.10 0.12 0.15 0.07 0.11 0.10 0.14 0.10 0.10

Total number of defected samples = 110Total number of samples inspected = 100x10 =1000

So, P = 110/1000 = 0.11 UCL = 0.203866 ( after calculation)LCL =0.016134 (after calculation)

n= sample size

1 2 3 4 5 6 7 8 9 100

0.050.1

0.150.2

0.25

P-Chart

fraction defectiveUCLLCLcenter line

We calculated everything , so just build it.

C- Chart• We use it when , a defected product , is also accepted.• It depends on how many defects are there in the defected product.

Total number of defects in all . Total Number of Samples Inspected

C = UCL = C + 3 C

LCL = C - 3 C

Lets take an example, of studying GALASS ITEM, having number of bubbles, in that as defects. We studied 10 items.

1 2 3 4 5 6 7 8 9 10

No. of defects in each item 3 21 5 3 7 8 10 0 14 9 80

So , C = 80/10 = 8UCL = 16.484LCL = - 0.484 = 0 ( so if any defected item, has defects below 16.484, that item will we be accepted.)

If LCL, comes –ve, take it zero.

Now we calculated everything, so just build C-chart

1 2 3 4 5 6 7 8 9 10-327

121722

C - Chart

Series 1UCLLCLcenter line

Item Rejected ( because number of defects, in that item are more than UCL= 16.484 )

Don’t get confuse between P chart, and C chart.

P- chart, use for DEFECTED ITEMS.C- chart use for NUBER OF DEFECTS, IN EACH ITEM.

16.484

8.00

0.00

Sample LCL UPL LCL UCL

Size = N A2 A3 dn D3 D4 B3 B4

2 1.88 2.659 1.128 0 3.267 0 3.267

3 1.023 1.954 1.693 0 2.574 0 2.568

4 0.729 1.628 2.059 0 2.282 0 2.266

5 0.577 1.427 2.326 0 2.114 0 2.0896 0.483 1.287 2.534 0 2.004 0.03 1.97

7 0.419 1.182 2.704 0.076 1.924 0.118 1.882

8 0.373 1.099 2.847 0.136 1.864 0.185 1.815

9 0.337 1.032 2.97 0.184 1.816 0.239 1.761

10 0.308 0.975 3.078 0.223 1.777 0.284 1.716

11 0.285 0.927 3.173 0.256 1.744 0.321 1.679

12 0.266 0.886 3.258 0.283 1.717 0.354 1.646

13 0.249 0.85 3.336 0.307 1.693 0.382 1.618

14 0.235 0.817 3.407 0.328 1.672 0.406 1.594

15 0.223 0.789 3.472 0.347 1.653 0.428 1.572

16 0.212 0.763 3.532 0.363 1.637 0.448 1.552

17 0.203 0.739 3.588 0.378 1.622 0.466 1.534

18 0.194 0.718 3.64 0.391 1.608 0.482 1.518

19 0.187 0.698 3.689 0.403 1.597 0.497 1.503

20 0.18 0.68 3.735 0.415 1.585 0.51 1.49

21 0.173 0.663 3.778 0.425 1.575 0.523 1.477

22 0.167 0.647 3.819 0.434 1.566 0.534 1.466

23 0.162 0.633 3.858 0.443 1.557 0.545 1.455

24 0.157 0.619 3.895 0.451 1.548 0.555 1.445

25 0.153 0.606 3.931 0.459 1.541 0.565 1.435

X-bar Chart for sigma R Chart Constants S Chart Constants

Table 1.1

• 6SIGMA

• http://www.youtube.com/watch?v=kiUXCezYFTM• 7QC TOOL

• http://www.youtube.com/watch?v=2OdGNLEXtlI • HOW TO UPLOAD POWER POINT ON YOUTUBE• https://www.youtube.com/watch?v=WbSTsG2klWQ

That’s it .

• I Hope you got it.

• Have any question, please let me know.

http://www.youtube.com/watch?v=kiUXCezYFTM

http://www.youtube.com/watch?v=2OdGNLEXtlI

https://www.youtube.com/watch?v=WbSTsG2klWQ

https://www.youtube.com/watch?v=WbSTsG2klWQ

7 qc toools LEARN and KNOW how to BUILD IN EXCEL

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Transcript of 7 qc toools LEARN and KNOW how to BUILD IN EXCEL