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VARIABLE CONTROL
CHARTS
Prepared by Mahmoud Eltaweel
Control
Charts
Variable
Xbar S
Nβ‰₯ 9
Xbar-R
2≀ 𝑁 ≀ 9
Moving
Range
N=1
Attributes
N= number of
observation in
one sample
Xbar- S charts
Data Given Standard Given
S chart
UCL
(upper control limit)
π‘ˆπΆπΏ! = 𝐡"
̅𝑆 π‘ˆπΆπΏ! = 𝐡# 𝜎$
CL
(center line)
CL= ̅𝑆 =
βˆ‘&
'
CL= ̅𝑆
LCL
(lower control limit)
𝐿𝐢𝐿! = 𝐡(
̅𝑆 𝐿𝐢𝐿! = 𝐡) 𝜎$
Xbar Chart
UCL π‘ˆπΆπΏ*+ = )𝑋 + 𝐴(
̅𝑆 π‘ˆπΆπΏ*+ = 𝑋$ + 𝐴𝜎$
CL CL= )𝑋 =
βˆ‘ *+
'
CL= )𝑋
LCL 𝐿𝐢𝐿*+ = )𝑋 βˆ’ 𝐴(
̅𝑆 𝐿𝐢𝐿*+ = 𝑋$ βˆ’ 𝐴𝜎$
β–  M= number of samples
β–  N= number of observations in one sample
β–  𝜎!=
Μ…#
$!
β–  S stands for standard deviation which can be calcuated by
S=
βˆ‘ &"' (& #
)'*
Steps to calcaute S using calcuator
1. Press on mode
2. Choose STAT then press AC
3. Press SHIFT then 1
4. Choose Data
5. Enter the sample data then press AC
6. Press SHIFT then 1 then Var
7. You can find the avg and S
8. Repeart steps from 3 to 7 for each
sample
Question 1
β–  The following table
presents the inside
diameter measurements
of forged automobile
engine piston rings. Each
sample or subgroup
consists of five piston
rings. Use these data to
construct !𝑿 and s charts.
Solution
From Table (factors for constracting
variables for control charts) @ n=5
B3= 0
B4= 2.089
A3= 1.427
Solution
S chartXbar chart
Solution
Question 2
β–  Samples of size n = 5 are collected from a process every half
hour. After 50 samples have been collected, we calculate %𝑋
= 20.0 and ̅𝑠 = 1.5. Assume that both charts exhibit control
and that the quality characteristic is normally distributed.
a) Estimate the process standard deviation.
b) Find the control limits on the )𝑋 and 𝑠 charts.
c) If the process mean shifts to 22, what is the probability of
concluding that the process is still in control?
Solution
C4 from the table
𝑍 =
π‘ˆπΆπΏ βˆ’ πœ‡,-.
𝜎
𝑛
𝑍 =
𝐿𝐢𝐿 βˆ’ πœ‡,-.
𝜎
𝑛
LCL UCL
20 22

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S chart

  • 2. Control Charts Variable Xbar S Nβ‰₯ 9 Xbar-R 2≀ 𝑁 ≀ 9 Moving Range N=1 Attributes N= number of observation in one sample
  • 3. Xbar- S charts Data Given Standard Given S chart UCL (upper control limit) π‘ˆπΆπΏ! = 𝐡" ̅𝑆 π‘ˆπΆπΏ! = 𝐡# 𝜎$ CL (center line) CL= ̅𝑆 = βˆ‘& ' CL= ̅𝑆 LCL (lower control limit) 𝐿𝐢𝐿! = 𝐡( ̅𝑆 𝐿𝐢𝐿! = 𝐡) 𝜎$ Xbar Chart UCL π‘ˆπΆπΏ*+ = )𝑋 + 𝐴( ̅𝑆 π‘ˆπΆπΏ*+ = 𝑋$ + 𝐴𝜎$ CL CL= )𝑋 = βˆ‘ *+ ' CL= )𝑋 LCL 𝐿𝐢𝐿*+ = )𝑋 βˆ’ 𝐴( ̅𝑆 𝐿𝐢𝐿*+ = 𝑋$ βˆ’ 𝐴𝜎$
  • 4. β–  M= number of samples β–  N= number of observations in one sample β–  𝜎!= Μ…# $! β–  S stands for standard deviation which can be calcuated by S= βˆ‘ &"' (& # )'* Steps to calcaute S using calcuator 1. Press on mode 2. Choose STAT then press AC 3. Press SHIFT then 1 4. Choose Data 5. Enter the sample data then press AC 6. Press SHIFT then 1 then Var 7. You can find the avg and S 8. Repeart steps from 3 to 7 for each sample
  • 5. Question 1 β–  The following table presents the inside diameter measurements of forged automobile engine piston rings. Each sample or subgroup consists of five piston rings. Use these data to construct !𝑿 and s charts.
  • 7. From Table (factors for constracting variables for control charts) @ n=5 B3= 0 B4= 2.089 A3= 1.427 Solution
  • 8.
  • 10. Question 2 β–  Samples of size n = 5 are collected from a process every half hour. After 50 samples have been collected, we calculate %𝑋 = 20.0 and ̅𝑠 = 1.5. Assume that both charts exhibit control and that the quality characteristic is normally distributed. a) Estimate the process standard deviation. b) Find the control limits on the )𝑋 and 𝑠 charts. c) If the process mean shifts to 22, what is the probability of concluding that the process is still in control?
  • 12. 𝑍 = π‘ˆπΆπΏ βˆ’ πœ‡,-. 𝜎 𝑛 𝑍 = 𝐿𝐢𝐿 βˆ’ πœ‡,-. 𝜎 𝑛 LCL UCL 20 22