CONTROL CHART FOR QUALITY CONTROL
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X-R CHART
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X-R chart is a pair of chart consisting of a average chart (X chart) and a
range chart (R chart). The X chart is used to control the mean value of the
characteristic and R chart is used to restrict the range of variations in the
values. This chart drawn when the characteristics are measurable. Each
chart consist of three values : a central line ; upper control limit & lower
control limit. The central line represents the arithmetic average of sample
means which equal to the mean of the population. The upper & lower control
limit are located at three standard deviation on either side of the central line.
PREPAERING X-R CHART
• The arithmetic mean of samples are distributed according to
normal distribution with sample mean X equal to the mean
of the population µ and std deviation of the sample mean σ
equal to √σ/n where σ is std deviation of the population and
n is the sample size.
The statistical limit of average X-chart in different situation is
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(i) X and σx known : _
Central line = CLx
__
=X
_ __ _
Upper control line = UCLx = X + 3σx
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_
Lower control line = LCLx = X – 3σx
CONTINUED…………….
•
(ii) µ and σ known :
_
Central line = CLx
(iii)
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=X
_
Upper control line = UCLx = µ + 3σ/√n
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Lower control line = LCLx = µ - 3σ/√n
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X and σ known :
_
__
Central line = CLx = X
_ __
Upper control line = UCLx = X + 3σ/√n
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Lower control line = LCLx = X - 3σ/√n
CONTROL RANGE CHART (R-CHART)
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•
Control limit = X + 3.σx
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•
= X ± 3.σ/√n
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= X ± 3.d`/√n * R
Now, 3.d`/√n expressed as a constant sample size and expressed as A2
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Upper control line = UCLx = X + A2.R
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Lower control line = LCLx = X – A2.R
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Central line = R ± 3. σR
PROBLEMS
•
Individual measurement of dia (mm)
SAMPLE
NO.
1
2
3
4
5
1
25.00
25.01
25.00
25.03
25.01
2
25.00
25.03
25.00
25.04
25.03
3
25.01
25.02
25.02
25.03
25.02
4
25.01
25.02
25.02
25.01
25.04
5
25.02
25.02
25.03
25.03
25.00
6
25.06
25.03
25.02
25.00
24.99
7
24.99
24.98
25.02
25.02
24.99
8
25.02
25.01
25.01
24.99
25.02
9
25.03
25.01
24.97
25.01
25.03
10
25.02
24.99
24.99
24.98
24.97
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•
•
Plot X & R chart and find out which of the given expression out of control.
Given constant
A2 = 0.5768 & D3= 0 and D4 = 2.114
SOLUTION
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•
THE mean of sample 1, mean X1
( X11 + X12 + X13 + X14 + X15 ) / 5
=( 25 + 25.01 + 25 + 25.03 + 25.01 )/ 5
= 125.05 / 5
= 25.01
For sample 1 highest measurement is = 25.03
lowest measurement is = 25.00
Range for sample1 = 25.03 – 25.00
= 0.03
Arithmetic mean & range of sample table
SAMPLE NUMBER
ARITHMETIC MEAN
RANGE
1
25.01
0.03
2
25.02
0.04
3
25.02
0.02
4
25.02
0.03
5
25.02
0.03
6
25.02
0.07
7
25.00
0.04
8
25.01
0.03
9
25.01
0.06
10
24.98
0.05
CALCULATION OF GRAND AVERAGE AND MEAN RANGE
• GRAND AVERAGE ( X DOUBLE BAR)
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• X = (25.01+25.02+25.02+25.02+25.02+25.02+25.00
+25.01 + 24.98 ) / 10
= 25.01
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Now, mean range R = (0.03+0.04+0.02+0.03+0.03+0.07+0.04
+0.03+0.06+0.05 ) / 10
= 0.04
Set up control chart for the average
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• 1. central line = CLx = X =25.01_
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• 2. upper control line
= UCLx
= X + A2.R
=25.01 + 0.5768 * 0.04
= 25.01 + 0.0231
= 25.03
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3. lower control limit =LCLx = X - A2.R
= 25.01 - .0231
= 24.99
Therefore average chart ( X - chart )
UCL
CL
LCL
Since the tenth average fallen outside the limit, so we can conclude process is not
under control so, tenth average should be deleted and again test the control limits.
Control limit with the remaining data is:
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•
X = ( 25.01+25.02+25.02+25.02+25.02+25.02+25.00
+25.01+25.01 ) / 9
= 25.01
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R = (0.03+0.04+0.02+0.03+0.03+0.07+0.04+0.03+0.06) / 9
= .039
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Now, revised control parameters of X-R chart :
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Central line = CLX = X = 25.01
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Upper control line= UCLX = X + A2.R
= 25.014 + 0.5768 * 0.039
= 25.014 + 0.022 = 25.036 = 25.04
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Lower control limit = LCLX = X + A2.R
= 25.014 – 0.022
= 24.99
Revised average chart ( X – chart )
UCL
CL
LCL
Since all the process within the control limit so, the X – chart represents the
process under control.
RANGE CHART ( R-CHART)
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•
•
•
Central line CLR = R = 0.039 = 0.04 _
Upper control limit = UCLR
=_ D3.R = 2.115 * 0.039 =0.08
Lower control limit = LCLR = D3.R = 0 * 0.039 = 0
The values of R for the
test data have been
plotted into the chart
within the control limit,
hence variability is
within under control.
UCL
CL
LCL
CONTROL CHART FOR ATTRIBUTE(p-CHART)
• Another form of inspection is where the items comprising the
sample are classified into two types : ‘acceptable’ & ‘nonacceptable’ such as inspection is known as “inspection by
attributes”.
• Inspection by attribute covers those situations where either :
(i) quantitative measurement are not possible as with the
inspection of damages, scratches, paint runs, matching of
colour against std. shade etc.
(ii) quantitative measurement consumes too much time.
The control chart which do this kinds of inspection is known as
control chart for fraction defectives ( p-Chart)
Basic theory underlying p-Charts
• The central line of fraction is determined by average _
percentage defectives ( average fraction defective )= p
_
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• Therefore control limit = p ± √ [p (1-p)] / n
• So, p is = no. of defectives / no. of pieces inspected
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• Therefore, p = ∑p / m
[ sample wise percentage defective / no. of sample ]
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Upper Control Limit = p + 3.√ [p (1-p)] / n
_
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Lower Control Limit = p - 3.√ [p (1-p)] / n
PROBLEM
• 10 Sample each of size 50, of a pipe were inspected in
pressure testing. The results of the inspection are given below:
Sample no.
1
2
3
4
5
6
7
8
9
10
No. of
defectives
2
3
2
0
2
3
2
1
2
3
• Draw a p-chart and state your conclusion.
SOLUTION………..
Sample no.
(1)
No. of defectives
(2)
Fraction defectives(p)
(3) = (2) / sample size
1
2
0.04
2
3
0.06
3
2
0.04
4
0
0.00
5
2
0.04
6
3
0.06
7
2
0.04
8
1
0.02
9
2
0.04
10
3
0.06
0.40
Sum of fraction defectives = 0.40
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Therefore, Average fraction defectives = 0.40 / 10 = 0.04 ( p )
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• (i) The central line = p = 0.04
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• (ii) Upper control limit = p + 3. √ [p (1-p)] / n
= 0.04 + 3. √[0.04(1-0.04)]/ 50
= 0.04 + 0.083
= 0.123
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• (iii) Lower control limit = p - 3.√ [p (1-p)] / n
=0.04 – 3. √[0.04 (1-0.04)]/50
=0.04 – 0.083
= -0.043 = 0
(since ve− control limit taken as 0)
UCL
CL
LCL